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Open Access Article
1 - Investigation of the relationship between net radiation flux and environmental characteristics and land surface coverage using satellite image (case study: south of Kerman province)
Seyed Karim afshari poor saeed Hamzeh saman nadizadeh shorabehThe amount of earth's surface net radiation directly depend on surface temperature, land use, soil and topography. In the present study, Landsat8 satellite imagery is used to estimate net radiation flux. Then, with using systematic sampling at 500 m intervals, the value MoreThe amount of earth's surface net radiation directly depend on surface temperature, land use, soil and topography. In the present study, Landsat8 satellite imagery is used to estimate net radiation flux. Then, with using systematic sampling at 500 m intervals, the value of each surface layer for example The LST, NDVI, altitude, slope, aspect, soil type and land use at the sample points for analysis were extracted. Mono-Window algorithm has been used to extract LST. The results showed that there is a direct correlation between the increase in altitude and NDVI with net radiation flux. The linear correlation coefficients were also 0.68 and 0.19 respectively. There is also an inverse relationship with the linear correlation coefficient of 0.74 between net radiation flux and LST. And from survey the rate of net radiation flux in different geographical directions in the case study it was found that in the northwest with 637(w/m2) the highest net radiation flux and eastern orientation with 582.7 (w/m2) had the lowest rate of net radiation flux. The net radiation flux in these directions with the slope rate had a direct correlation with correlation coefficient 0.54. In addition, the rate of net radiation flux at water levels such as lake and reservoir dam with 817 (w/m2) has the highest rate of net radiation flux and saline lands with 509 (w/m2) of minimum net radiation flux. There is the highest and lowest rate of net radiation flux in inceptisols and badland areas, respectively. Manuscript profile -
Open Access Article
2 - Investigation of Soil Surface Moisture in Ardabil City Using Landsat 8 and Sentile 1 satellite Data
Sayyad Asghari Saraskanrod Fariba Esfandayari Darabad Elham Mollanouri Shiva SafaryBackground and Aim: Surface soil moisture is an important variable in nature's water cycle and can be affected by various factors, including temperature and soil characteristics. The use of ground sensors for measuring moisture can lead to spending time and expense and MoreBackground and Aim: Surface soil moisture is an important variable in nature's water cycle and can be affected by various factors, including temperature and soil characteristics. The use of ground sensors for measuring moisture can lead to spending time and expense and inappropriate distribution of samples on large scales. Therefore, Remote sensing observations can be an important tool in estimating soil moisture. The present study aims to use the TOTRAM model using Landsat 8 images and the SVR method using Sentile 1 images to estimate soil moisture.Methods: In the present study, two TOTRAM methods based on pixel distribution in LST- VI space and the SVR method were used to extract soil moisture using the SAR technique and Sentinel 1 data. To implement the TOTRAM method, Landsat 8 images related to 4/29/1398 and 5/30/1398 are downloaded and after extracting NDVI and LST maps, The correlation between the dependent variable of moisture and independent temperature variables and vegetation variables has been investigated using Geographically weighted regression (GWR). To implement the SVR method after acquiring Sentinel 1 images related to 31\/05\/1398 and 27\/04\/1398, Soil Moisture Data Product FLDAS and 500 meters product of Modis Satellite (MCD12q1) were called to classify land cover in the Google Earth Engine system, and maps related to soil moisture were extracted. After extracting the moisture maps the distribution of moisture using the local Moran index has been investigated. By defining this index, positive values for this index represent the cluster of distribution.Results: Examination of the soil moisture map obtained by the SVR method showed the concentration of moisture in areas with vegetation and water and the change in moisture status from July to August was visible. The humidity pattern has shown the reflection of the precipitation pattern so that maximum precipitation and humidity were observed in April and in summer both precipitation and humidity components decreased. Examination of the TOTRAM method and application of the GWR method has shown a complete correlation between NDVI LST and moisture. However, the correlation between LST and humidity with B (values) and standard error (SE) of 0.995 and zero corresponding to July and 0.981 and zero corresponding to August showed the highest correlation with vegetation variable with moisture dependence parameter, which this correlation In August, with increasing the coefficient of determination of R2 to 0.997 and a significant decrease of NDVI to the value of 0.415 in July, it has increased much more. Application of Moran local index with values less than 0.05 for p-value and positive values for z and near positive number 1 for Moran index showed the cluster distribution of moisture variable.Conclusion: The results of TOTRAM and SVR methods showed the dependence of soil moisture status on conditions and cluster moisture distribution. According to the correlation coefficients of geographical regression, there is a greater correlation between temperature and humidity variables, especially in August, due to the decrease in vegetation density. The results of the SVR algorithm maps showed that in areas with the presence of vegetation, especially dense vegetation, we see an increase and with increasing temperature, we see a decrease in humidity. Also, the coordination of moisture patterns of the SVR algorithm and precipitation showed a direct relationship between moisture and precipitation. Considering that the SVR method uses parameters such as radar scattering intensity and land cover classification, as well as the use of Sentinel 1 radar images by this algorithm, more accurate results can be expected from this algorithm.Keywords: LST, NDVI, Support vector regression, TOTRAMBackground and Aim: Surface soil moisture is an important variable in nature's water cycle and can be affected by various factors, including temperature and soil characteristics. The use of ground sensors for measuring moisture can lead to spending time and expense and inappropriate distribution of samples on large scales. Therefore, Remote sensing observations can be an important tool in estimating soil moisture. The present study aims to use the TOTRAM model using Landsat 8 images and the SVR method using Sentile 1 images to estimate soil moisture.Methods: In the present study, two TOTRAM methods based on pixel distribution in LST- VI space and the SVR method were used to extract soil moisture using the SAR technique and Sentinel 1 data. To implement the TOTRAM method, Landsat 8 images related to 4/29/1398 and 5/30/1398 are downloaded and after extracting NDVI and LST maps, The correlation between the dependent variable of moisture and independent temperature variables and vegetation variables has been investigated using Geographically weighted regression (GWR). To implement the SVR method after acquiring Sentinel 1 images related to 31\/05\/1398 and 27\/04\/1398, Soil Moisture Data Product FLDAS and 500 meters product of Modis Satellite (MCD12q1) were called to classify land cover in the Google Earth Engine system, and maps related to soil moisture were extracted. After extracting the moisture maps the distribution of moisture using the local Moran index has been investigated. By defining this index, positive values for this index represent the cluster of distribution.Results: Examination of the soil moisture map obtained by the SVR method showed the concentration of moisture in areas with vegetation and water and the change in moisture status from July to August was visible. The humidity pattern has shown the reflection of the precipitation pattern so that maximum precipitation and humidity were observed in April and in summer both precipitation and humidity components decreased. Examination of the TOTRAM method and application of the GWR method has shown a complete correlation between NDVI LST and moisture. However, the correlation between LST and humidity with B (values) and standard error (SE) of 0.995 and zero corresponding to July and 0.981 and zero corresponding to August showed the highest correlation with vegetation variable with moisture dependence parameter, which this correlation In August, with increasing the coefficient of determination of R2 to 0.997 and a significant decrease of NDVI to the value of 0.415 in July, it has increased much more. Application of Moran local index with values less than 0.05 for p-value and positive values for z and near positive number 1 for Moran index showed the cluster distribution of moisture variable.Conclusion: The results of TOTRAM and SVR methods showed the dependence of soil moisture status on conditions and cluster moisture distribution. According to the correlation coefficients of geographical regression, there is a greater correlation between temperature and humidity variables, especially in August, due to the decrease in vegetation density. The results of the SVR algorithm maps showed that in areas with the presence of vegetation, especially dense vegetation, we see an increase and with increasing temperature, we see a decrease in humidity. Also, the coordination of moisture patterns of the SVR algorithm and precipitation showed a direct relationship between moisture and precipitation. Considering that the SVR method uses parameters such as radar scattering intensity and land cover classification, as well as the use of Sentinel 1 radar images by this algorithm, more accurate results can be expected from this algorithm. Manuscript profile -
Open Access Article
3 - Landscape Metrics as Tool for Investigating the Relationship between Landscape Patterns and Land Surface Temperature in suitable scale(Case Study: Tehran City
Fatemeh Effati Abdolrassoul Salmanmahiny Fatemeh SHafie Khorshidi Saeed KarimiBackground and Objective: Tehran has experienced extensive population growth in the last decades, leading to a high rate of urban expansion. Land use/land cover (LULC) patterns have noticeably been changed to impervious surfaces that led to the changes in the thermal co MoreBackground and Objective: Tehran has experienced extensive population growth in the last decades, leading to a high rate of urban expansion. Land use/land cover (LULC) patterns have noticeably been changed to impervious surfaces that led to the changes in the thermal condition and forming heat islands in this city. So this study wants to evaluate the landscape and the Land surface temperature patterns via using the landscape metrics on a proper scale in Tehran. Material and Methodology: In this study, a combination of remote sensing, GIS and landscape ecology approach is used to explain the relationship between land use/cover patterns and land surface temperature in Tehran's urban area. We used ETM + Landsat satellite images of February 28, 2013 to create a five class LULC map of the area through Linear Spectral Mixture Analysis and the maximum algorithm methods. Also, Land Surface Temperature map were prepared according to the available methods for thermal band of the sensor and were presented in four zones. Then, the relationship between LST and land use/cover was investigated using 7 landscape metrics (e.g MPS, PAFRAC, COHESION). Findings: We found that impervious surface has the highest percentage of class and mean patch size, cohesion and aggregation, and landscape metrics very well described the LST zone II with impervious surface dominance. Also, the results showed that the 30 m pixel size is good enough for assessing the spatial and ecological characteristics of LULC patterns and their relationships with LST in Tehran Discussion and Conclusion: The results showed the possibility of assessing the relationship between LST and LULC based on the landscape metrics. The findings can be useful for urban planners and environmental managers to decrease urban heat pollution during urban sprawl and development. Manuscript profile -
Open Access Article
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علی رحیمی خوب مهدی کوچک زاده فرود شریفی جمال محمد ولی سامانی سید محمودرضا بهبهانی -
Open Access Article
5 - Comparison between land surface temperature estimation in single and multi-channel method using LandSat images 8
Parvaneh Asgarzadeh Ali Darvishi Boloorani Hossain Ali Bahrami Saeid HamzehLand surface temperature (LST) is a key parameter in environmental studies particularly for drought monitoring. Due to the ground limitations to measure the LST on a large scale, thermal remote sensing is a unique method for estimating LST. The aim of this article is co MoreLand surface temperature (LST) is a key parameter in environmental studies particularly for drought monitoring. Due to the ground limitations to measure the LST on a large scale, thermal remote sensing is a unique method for estimating LST. The aim of this article is comparing between LST estimation in single and multi-channel method using Landsat 8 thermal and reflective bands. Necessary ground data from meteorological stations Farabi (Khuzestan) and Karaj (Alborz) were taken to coincide with the dates and times of Landsat 8 overpasses. In this article Land surface emissivity and atmospheric water vapor content are major inputs for single and multi-channel LST estimation. After correction, processing and calculation of interest, LST were estimated. For result evaluation, statistical indices such as Root-Mean-Square Error (RMSE), Mean Absolute Error (MAE) and coefficient of determination (R2) were used. Results show the high value of R2 in all LST estimation method in comparison with ground measurement. In single channel using band 10 highest accuracy with MAE about 1.04 and 0.98 degrees in Karaj and Farabi station was seen respectively. The lowest and highest value of RMSE is in the single channel method (band 10) and multi-channel method (band 10 and 11) respectively. Study area conditions in terms of temperature; land cover and water vapor content affect the results and appropriate thermal band selection. Take-in consideration, especially using multi-band LST estimation method is suggested. Manuscript profile -
Open Access Article
6 - Investigating the relationship between temperature, net radiation flux by biophysical properties and lanuse using LandSat 8 satellite imagery
Mohammad Karimi Firozjaei Majid Kiavrz MogadamDue to high heterogeneity in the land surface properties including variation in the type of surface coverage, varied topography conditions and placement in different geographic locations, investigating the relationship between temperature and net radiation and listed pa MoreDue to high heterogeneity in the land surface properties including variation in the type of surface coverage, varied topography conditions and placement in different geographic locations, investigating the relationship between temperature and net radiation and listed parameters of properties has great importance. The aim of this study is to investigate the relationship between temperature and net radiation surface with Indexes biophysical properties and land use in the region. For this purpose, LandSat8 satellite image, MODIS water vapor product and digital elevation model map of the city of Sari are used. In order to calculate the surface temperature, single channel algorithm, net radiation from Surface energy balance algorithm for land (SEBAL) mountain algorithm and the extraction of different surface properties from Tasselled cap transformation (TCT) Indexes were used. also, the combination of Maximum likelihood classification methods and decision tree are utilized to classify Image. Net radiation has a direct relationship with Normalized difference vegetation index (NDVI), Greenness and Wetness parameters and inverse relationship with mean correlation coefficient 0.8 with NDBI, Albedo, Brightness and surface temperature parameters. In this study, the correlation coefficient of relationship between Wetness, Greenness and Brightness indicators and net radiation surface is 0.94. The Built up lands with an average 600.38 have the lowest net radiation and forest lands with an average 759.5 have the highest net radiation flux in the region. The results show that using remote sensing data and considering the TCT parameters related to biophysical properties of surface are very useful to assess the temperature and net radiation of the region. Manuscript profile -
Open Access Article
7 - Reconstruction of cloud-free time series satellite observations of land surface temperature (LST) using harmonic analysis of time series algorithm (HANTS)
Hamid Reza Ghafarian Malamiri Hadi Zare KhormizieLand surface temperature (LST) is an essential parameter in the energy exchange between the earth surface and atmosphere. It is widely used in various scientific fields, such as climatology, hydrology, agriculture, ecology, public health and environmental science where MoreLand surface temperature (LST) is an essential parameter in the energy exchange between the earth surface and atmosphere. It is widely used in various scientific fields, such as climatology, hydrology, agriculture, ecology, public health and environmental science where the time series analysis of LST is vital. One of the methods to estimate LST is to use thermal remote sensing technique and infra-red satellite imageries. But, the time series satellite data are commonly prone to miss data, outliers (spatially and temporally) due to clouds, aerosols, cloud masking algorithm malfunctioning and sensor errors. In this study, to solve the problem of missing data (gaps) and outliers Harmonic ANalysis of Time Series algorithm (HANTS) was used. The day and night MODIS LST products (MOD11A1) were used in 2015, with 1 kilometers and daily spatial and temporal resolution, respectively. The study area covers most part of Iran, Turkmenistan and the Caspian Sea, which belongs to an image frame that in the sinusoidal MODIS frame system has the horizontal and vertical number of 22 and 5 (h22v05), respectively. The quality evaluation of original data showed that on average 36.8 and 35.6 percentage of data was covered by a cloud by day and night time. The results of the HANTS algorithm illustrated that the Root Mean Square Error (RMSE) between the original and reconstructed data were 3.87 and 2.68 Kelvin during the day and night time. The results of this study indicate that HANTS algorithm can effectively solve the problem of gaps and outliers and improve the quality of data used in time series LST of MODIS. Manuscript profile -
Open Access Article
8 - Assessing the impact of urban expansion and land cover changes on land surface temperature in Shahrekord city
Ataollah Ebrahimi Elham Kiani SalmiUrban expansion and land use changes have a significant impact on land surface temperature (LST). According to the fact that the development of urban is currently one of the most important phenomena in global warming, it is possible to study and measure the temperature MoreUrban expansion and land use changes have a significant impact on land surface temperature (LST). According to the fact that the development of urban is currently one of the most important phenomena in global warming, it is possible to study and measure the temperature of the Earth's surface in urban areas in the shortest possible time with the rapid development of satellite technology. The purpose of this study was to investigate urban expansion and urban heat island (UHI) using remotely sensed data in Shahrekord city. In this study, Ratio vegetation index (RVI) and Normalized difference vegetation index (NDVI), and LST were calculated using multi-spectral and thermal bands of Landsat 7 and 8 satellite images. Land use map was extracted using the maximum-likelihood algorithm in TerrSet software. The overall kappa index was estimated at 0.82 and 0.93 for 2003 and 2016, respectively. By comparing two vegetation indexes (RVI and NDVI) and surface temperature during the 13 years (2003 to 2016), it was determined that with urban development, the surface temperature has increased to 2.210C (from 40.69 to 42.90 0C). The results showed that the correlation of NDVI index with the surface temperature map was negative but with positive RVI index. Moreover, these two vegetation indexes, RVI and NDVI, show a more significant relationship with LST in green areas than urban and bare lands. Due to, a significant effect of green areas on regulating LST we recommend that green areas should be expanded in accordance with the urban area expansion. Manuscript profile -
Open Access Article
9 - Downscaling TRMM satellite-based precipitation data using non-stationary relationships between precipitation and land surface characteristics
Bahareh Zanjani Hesam Seyed Kaboli Mohsen RashidianSatellite-based precipitation dataset has been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these datasets has limited their application in localized regions and watersheds. So, ha MoreSatellite-based precipitation dataset has been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these datasets has limited their application in localized regions and watersheds. So, having an accurate estimation of precipitation by satellites along with the adequate spatial scale in hydrologic studies is the main goal of this study. In this research, Geographically weighted regression (GWR) method was investigated to downscale the Tropical Rainfall Measuring Mission (TRMM-3B42 Version 7) over the DEZ river basin in the southwest of IRAN for 2010-2011. Downscaling was performed based on the non-stationary relationships between the TRMM precipitation and the Digital elevation model (DEM) derived products, the Normalized difference vegetation index (NDVI), the Enhanced vegetation index (EVI) and the Land surface temperature (LST). The result shows that the downscale precipitation at 1 km spatial scale had significantly improved spatial resolution, and agreed well with data from the rain gauge stations. For the 16-day precipitation, Mean square root means square error (RMSE) and absolute mean error (MAE) values are 22.7 mm and 7.45 mm, respectively. However, the accuracy of the model varies in a different location and depends on the vegetation condition. Manuscript profile -
Open Access Article
10 - Estimation of Ardabil land surface temperature using Landsat images and accuracy assessment of land surface temperature estimation methods with ground truth data
Hossein Fekrat Sayyad Asghari Saraskanrood Seyed Kazem AlavipanahBackground and ObjectiveOver the past two decades, the intense need for land surface temperature information for environmental studies and management and planning activities has made estimating the land surface temperature one of the most important scientific topics. On MoreBackground and ObjectiveOver the past two decades, the intense need for land surface temperature information for environmental studies and management and planning activities has made estimating the land surface temperature one of the most important scientific topics. On the other hand, different methods have been proposed to estimate the land surface temperature, each of which has resulted in different results for different regions. In this study, the algorithms that have had acceptable results in different studies have been selected and evaluated. In the field of thermal studies, what is considered as a major defect in monitoring the land surface temperature is the lack of sufficient meteorological stations to know the temperature values in places without stations and information limitations in preparing temperature data, especially for large areas. The study area is also facing this shortage, and this limitation further highlights the importance of the topic selected for this study to estimate the surface temperature using remote sensing technology. Verification and validation of results obtained from estimating the land surface temperature are other basic and discussed topics in thermal studies. The purpose of this study is an estimation of temperature in Ardabil city and evaluate the accuracy of the four single-channel algorithms, the improved mono-window, the Planck's inversion function method and the radiative transfer equation (RTE) method, to compare the accuracy of the two Landsat 5 and Landsat 8 satellites in estimating the land surface temperature. Materials and Methods Three types of data have been used in this study; Landsat 5 and 8 satellite images, data of two meteorological stations and ground data harvested with a digital thermometer. The images used are from the two satellites Landsat 5 and Landsat 8 with a time interval of 19 years. The meteorological data used were obtained from two synoptic stations in the study area. In addition to land surface temperature, relative humidity, minimum temperature and maximum temperature data of 24 hours were also obtained on two dates. Also, two points of the study area were selected and land surface temperature in the position of these two stations simultaneously with the satellite Recorded from two digital thermometers. MODTRAN web version calculator software version 6 has been used to model the radiation and the amount of atmospheric transmission. Emissivity with two methods of LSE methods based on NDVI and LSE NDVI Thresholds Method and land surface temperature with four algorithms: single-channel algorithms, An Improved mono-window, inversion of Planck’s function and radiative transfer equation using band 6 Landsat 5 and band 10 Landsat 8 bands. It was coded in MATLAB software for 2000 and 2019. Finally, the accuracy of the algorithms was evaluated using synoptic station surface temperature data and field sampling. Results and Discussion The collected data and results are analyzed and while presenting the output maps, the accuracy of the methods with terrestrial and meteorological data as well as the accuracy of Landsat 5 and Landsat 8 satellites in estimating the land surface temperature has been compared and evaluated. The results showed that for the three single-channel algorithms, the inversion of Planck’s function and RTE, the first method of emission and for the An Improved Mono-Window algorithm, the second method of emission had a higher accuracy. Land surface temperature data obtained from meteorological stations in 2000 differ by 12 minutes in terms of time and by 2019 differ by 4 minutes in terms of satellite transit time. The first meteorological station is located somewhat within the city limits and according to the results, it seems that the most important factor is the greater difference between the data of the first station and the estimated LST compared to the second station is the same factor because the heterogeneity of pixels and large changes in levels in urban areas interfere with a pixel value. And subsequently increases the likelihood of errors in estimating surface temperature within the urban anthropogenic range. For the ground station, two points with a homogeneous environment and outside the urban area with agricultural use (alfalfa) and barren use of the harvested product were selected and their surface temperature was measured at the same time as the satellite. The output results of land surface temperature estimation were compared and evaluated with two synoptic stations and two ground stations. In both histories, the single-channel algorithm showed the least difference with the temperature recording stations. Conclusion In this research, using Landsat 5 and Landsat 8 satellite images, four algorithms for estimating the land surface temperature of the earth, including single-channel algorithms, An Improved mono-window, inversion of Planck’s function and radiative transfer equation and land surface temperature maps of Ardabil city for two 2000 and 2019 were coded and extracted in MATLAB software environment. The band 6 Landsat 5 satellite was used for 2000 and the band 10 Landsat 8 satellite was used for 2019 due to less noise than the 11th band and the proximity of 9.66 (which is the highest radiation in this range). Comparison of land surface temperature maps obtained by the algorithms with synoptic and ground stations showed that in both 2000 and 2019, the single-channel algorithm was more accurate than the other methods. Comparison of the results of the single-channel method with the stations shows a difference of +2.5 and 2- with stations 1 and 2 for the year 2000 and a temperature difference of +3.3, +0.9, 1- and -0.9. Shows stations 1, 2, 3 and 4 for 2019, respectively. It seems that the direct use of atmospheric transmittance coefficients in the single-channel method process has been effective in the high accuracy of this method. In terms of accuracy, after the single-channel algorithm, the An Improved Mono-Window method, the RTE algorithm, and finally the Planck function inverse correlation algorithm were placed, respectively. The results of comparing the output of all four algorithms with the data of stations 1, 2, 3 and 4, show that the ground stations harvested with a digital thermometer are more accurate than the data of meteorological stations. One of the reasons for this is the location of meteorological stations (especially, Station_1) in the urban area due to the heterogeneity of the urban environment and the possibility of pixel interference and temperature interference of land uses, while ground stations from the out-of-town area. And was selected from an environment with homogeneous pixels (barren and agricultural). Also, the results of all four algorithms extracted from the Landsat 8 image show more accuracy compared to the results of the four algorithms obtained from the Landsat 5 image, and due to the improved spatial resolution of the TIRS sensor compared to the TM, the TIRS sensor output is more accurate, It was predictable. Manuscript profile -
Open Access Article
11 - Quantifying the effect of surface parameters and climatic conditions on land surface temperature using reflective and thermal remote sensing data
Naeim Mijani Saeid Hamzeh Mohammad Karimi FirozjaeiThe land surface temperature (LST) plays a vital role in a wide range of scientific researches including climatology, hydrology, natural resources and etc. There are some determining factors which affect the land surface temperature, such as the kind of surface elements MoreThe land surface temperature (LST) plays a vital role in a wide range of scientific researches including climatology, hydrology, natural resources and etc. There are some determining factors which affect the land surface temperature, such as the kind of surface elements, topography and environmental conditions and also the amount of incoming radiation to the surface. The objective of this study is to investigate the effect of topographic parameters, climatic conditions and downward radiation on land surface temperature using remote sensing data. For this purpose, the Landsat 8 satellite image, ASTER digital elevation model, MODIS water vapor product (MOD07) on 24 July 2018, topography and climate map of Kerman province were used. To calculate the LST and downward shortwave and longwave radiation to surface the single channel and SEBAL energy balance algorithms were used, respectively. Finally, using statistical analysis the relationship between LST and independent variables, including elevation, slope, aspect, vegetation cover index and downward radiation to the surface were studied. The results of the study shown that the correlation coefficient between the LST and each of the independent parameters is more than 0.7. Also, the relationship between LST and topographic, normalized difference vegetation index (NDVI) and downward radiation parameters at the 95% level was significant. The results of the mean of LST values in climatic conditions, including extra-dry, dry, semi-dry, Mediterranean, semi-wet and wet indicate that climates classes with higher LST relative to climates classes with lower LST have means of elevation, NDVI lower and mean longwave downward radiation to surface higher. Manuscript profile -
Open Access Article
12 - An investigation of the relationship between land surface temperatures, geographical and environmental characteristics, and biophysical indices from Landsat images
Abbasali Vali Abolfazl Ranjbar Marzieh Mokarram Farideh TaripanahLand surface temperature (LST) is an important indicator of habitat quality assessment for a local and global scale. In the present study, the effects of multiple factors on land use, geological formations, topographical and climate factors on LST in Kharestan region we MoreLand surface temperature (LST) is an important indicator of habitat quality assessment for a local and global scale. In the present study, the effects of multiple factors on land use, geological formations, topographical and climate factors on LST in Kharestan region were investigated. To this end, images of July Landsat 7 and 8 satellites during the period 2000-2017, digital elevation model, geological map and topography were used. The surface temperature was extracted using a split-window method and also land use extracted from the supervised classification method which has been done in 2017. The correlation between surface temperature and elevation, aspect, slope, vegetation, soil moisture, and air temperature variables was investigated using statistical methods. The results indicated that the surface temperature average was 43 °C, Normalized difference vegetation index (NDVI) was 0.144 and Normalized difference moisture index (NDMI) was 0.068. According to the classification of images with an overall accuracy of 99.96% and kappa coefficients of 0.96, pasture and horticultural land cover the highest and lowest area, respectively. The highest surface temperature, 53 °C was observed in bare soil and residential areas and the lowest 29 °C in horticultural land. Moreover, the highest and lowest surface temperatures were related to Pabdeh-Gurpi and Asmari formations, respectively. In sunny slopes, the highest correlation, R2>0.5 was observed between surface temperature, elevation, temperature, vegetation, and surface moisture. Furthermore, in shady slopes, the surface temperature had the highest correlation, R2>0.5 with elevation, temperature, and vegetation. Among the above factors, elevation and temperature had the most influence on surface temperature. In addition, the correlation between vegetation index and a normalized moisture index with inverse surface temperature was >0.9. Also, the correlation between surface temperature and the air temperature was positive. Therefore, land use, geology, topography, vegetation, soil moisture, and air temperature are important factors in ecosystem temperature equilibrium. Manuscript profile -
Open Access Article
13 - The effect of Meighan wetland environmental changes on land surface temperature of surrounding areas by using Landsat satellite data
Saeed Mahmoodi Behrouz Sari Saraf Majed Rezaei Banafsheh Hashem RostamzadeWetlands are one of the most important aquatic zones that affect the climate of the surrounding areas and are also one of the most fragile natural phenomena. Therefore, it is very important to detect changes in the environment around the wetlands. The purpose of this st MoreWetlands are one of the most important aquatic zones that affect the climate of the surrounding areas and are also one of the most fragile natural phenomena. Therefore, it is very important to detect changes in the environment around the wetlands. The purpose of this study, the land use change detection, the normalized vegetation index, land surface temperature patterns in the surrounding of the Meighan wetland, were analyzed using Landsat TM multi-time sensor data for 30 May 2002, and 5 June 2010. Supervised classification algorithms with maximum likelihood were used to extract land use changes. The results of classification accuracy, using the Kappa coefficient for 2002 and 2010 were 99.13% and 98.93% with 98 and 97 kappa coefficients, respectively. The results of land use changes showed that the barren lands increased by 100 km2 and, in contrast, vegetation areas were reduced by 84 km2. The average of the normalized vegetation index was not significantly changed and the maximum and minimum values in 2002 were 0 and -0.52, and in 2010, -0.05 and -0.58, respectively. The warmer temperature classes in the regional temperature pattern in 2010 were more extensive than in 2002. The minimum, average and maximum temperature in 10 km of surrounding of Meighan wetland in 2002 were 16.72, 27.35 and 36.4°C with a standard deviation of 3.2, and in 2010, 15.5, 29.8 and 37°C with a standard deviation of 3.5. Manuscript profile -
Open Access Article
14 - Study of the relationship between land use and vegetation changes with the land surface temperature in Namin County
Azad Kakehmami Ardavan Ghorbani Sayyad Asghari Sarasekanrood Ehsan Ghale Sahar GhafariBackground and ObjectiveRapid development of cities due to extensive changes in land use and land cover has had negative effects on global environmental quality. Land cover and land use changes, and the development of urban and agricultural regions and deforestati MoreBackground and ObjectiveRapid development of cities due to extensive changes in land use and land cover has had negative effects on global environmental quality. Land cover and land use changes, and the development of urban and agricultural regions and deforestation are changing the regional and local temperature regime. Knowing the land surface temperature degrees contribute significantly to a wide range of issues relating to the Earth science such as urban climate, global environmental changes, and the study of the interaction of human and the environment. The lack of sufficient meteorological stations to be aware of temperature values in regions lacking a station is considered as a major flaw in monitoring the land surface temperature. Due to the information limitations, collecting data especially to a large extent, is associated with many problems and obstacles, and the real-time access is difficult or impossible. Therefore, the need to use remote sensing technology with time conditions along with the feature of continuity and data collection in wide ranges can be very effective. The purpose of this study is to investigate the land surface temperature of Namin county in a period of 28 years and to compare the obtained results with land use and vegetation changes. Materials and MethodsThe data used in this study included Landsat 8 satellite image of the OLI sensor in order to extract land use map and TIRS sensor image to extract land surface temperature for the year 2015. Moreover, Landsat 5 satellite image of the TM sensor were used to extract land use map by using visible and infrared bands, and also to extract land surface temperature by using thermal bands for the year 1987. Images were taken in late spring and early summer due to the lack of high cloudy and snowy covers , as well as the high intensity of sunlight. The eCognition8.9 software was used for object-based classification. Classification in five classes (dry and irrigated farming, rangeland, forest and residential) and six classes (dry and irrigated farming, rangeland, forest, residential and water bodies) were selected for the years 1987 and 2015 respectively. To assess the accuracy and comparison of the obtained maps, the error matrix, overall accuracy, and kappa statistics were used. Split-Window method was used to extract the land surface temperature of the study area. Finally, in order to analyze the relationship between land surface temperature with vegetation index, the correlation coefficients between land surface temperature and vegetation index were calculated based on land use types in the years 1987 and 2015. Results and Discussion The highest land use area in the years 1987 and 2015 belongs to the rangeland use with 43781 and 34114 hectares respectively and the second land use area belongs to dry farming use with 23854 and 33277 hectares respectively. Moreover due to the lack of water use , the lowest land use area in 1987 belongs to residential use with 1301 hectares, while in 2015 with the construction of water structures, water use with an area of 86 hectares has the lowest land use area. The highest land use area increase was in the dry farming with 9423 hectares, which is a significant increase compared to 1987. The highest recorded temperature for Namin county in 1987 and 2015 was related to dry farming use (34°C and 27°C, respectively), indicating the concentration of heat in these regions. This type of land use has the highest temperature due to the factors such as the dryness of the products at this time and the harvest of the products. In 1987, dry farming use had the highest temperature (34°C), but in 2015 it experienced a decrease in temperature (27°C), despite the fact that it had the highest land surface temperature compared to other types of land uses in 2015. The reason can be attributed to the factor of harvesting crops. Due to the fact that the rainfed crops in the study area are mostly wheat, and at this time of the season, most of the wheat is ripe or harvested, so the transpiration of these products is insignificant. The lowest recorded temperatures in Namin county are related to the uses of water bodies (21°C), forest (21°C) and irrigated farming (22°C), respectively. Since water has a high heat capacity, it has the greatest effect on reducing the temperature. In forest and irrigated farming land uses, due to the higher vegetation density, the land surface temperature has the lowest value (23°C and 24°C in 1987 and 21°C and 22°C in 2015 respectively) compared to the other land use types. Agricultural land use in this area has the lowest land surface temperature (24°C in 1987 and 21°C in 2015) after forest areas. Due to the fact that the crops cultivated in this area are plants such as potatoes and these plants have more water needs, therefore these plants have a high greenness value at June to early July, which has led to more transpiration in the area where they are cultivated than other areas, thus it has been very effective in keeping the land surface temperature cool. The rangeland use has had high land surface temperatures (27°C and 25°C, respectively) in the two study years, and there is little difference between the two years. According to the study season which was late June to early July, the high temperature of this land use type is due to the increase in the areas lacking canopy cover or areas having low or scattered vegetation. Due to the fact that in August, most of the leaves and brunches of the existing plants are dry and the transpiration is low, high temperatures are also recorded. The relationship between land surface temperature and vegetation index in rangeland use in the two study years had the highest correlation (0.91 in 1987 and 0.83 in 2015), while the correlation coefficient of the forest use was the lowest (0.46 in 1987 and 0.23 in 2015). Conclusion Land use type and land use and vegetation changes have a significant effect on land surface temperature changes. However, areas without vegetation have a higher land surface temperature than the areas with vegetation. The results showed that there was no significant correlation between vegetation cover and land surface temperature, which is mainly due to sufficient vegetation. In general, the results showed that in most areas with lower temperatures, there is high density vegetation indicating an inverse relationship between vegetation index and land surface temperature. Manuscript profile -
Open Access Article
15 - Evaluating the types of split window algorithms for calculating the land surface temperature to determine the best algorithm for MODIS sensor images
Mohammad Kazemi Garajeh Behnam Salmani Bakhtiar FeizizadehBackground and ObjectiveIn recent years, the study of climate changes as well as their effects, has become a constant topic in the scientific fields of many countries. One of the main features of these changes is the increase in air temperature over the last 5 decades c MoreBackground and ObjectiveIn recent years, the study of climate changes as well as their effects, has become a constant topic in the scientific fields of many countries. One of the main features of these changes is the increase in air temperature over the last 5 decades compared to the last 500 years. Statistics show an increase of one degree centigrade in air temperature over the last 5 decades. The land surface temperature means the radiant temperature of the earth's crust and the amount of pure energy that is balanced on the earth's surface under climatic conditions and depends on the reached the amount of energy, surface emissivity, humidity and atmospheric airflow. Land surface temperature is considered as one of the key variables in climate and environmental studies of the Earth’s surface. It is also one of the basic parameters in the physical features of the earth's surface at all scales from local to global. Currently, the most important sources of climatic data are meteorological stations, and these stations provide climatic statistics for certain points, while the temperature may alter at different intervals stations and decrease or increase compared to the desired station. Therefore, it is necessary to have a technology that can eliminate the shortcomings of meteorological stations in calculating the temperature at sampling intervals and in impassable places where it is not possible to build a meteorological station. In recent years, new sciences such as remote sensing have provided new ways to monitor the environment and acquire, evaluate, and analyze environmental data, and can provide a wide range of parameters relating to the environment. This technology is considered as an important and increasing source of information for studying climate change that has a direct impact on global warming. Over the past two decades, 18 algorithms have been developed to calculate the land surface temperature. These algorithms fall into four categories: emissivity-dependent models, two-factor models, complex models, and radio-based models. The results of the comparisons between different algorithms shows that different algorithms perform differently in different situations with different geographical climates. Therefore, the present study aims to compare the types of LST calculation algorithms for MODIS sensor images and determine the best algorithm for East Azarbaijan province. Materials and Methods Convert digital numbers (DN) to spectral radiation. The following equation was used to convert the numerical values to spectral radiation for thermal bands of MODIS sensor images. Planck's equation was used to convert spectural radation to spectral reflection when the radiant power of thermak data of MODIS sensor is considered to be a maximum of one. In order to estimate the surface emissivity, the Normalized Difference Vegetation Index (NDVI) thresholding method is used. The radiant power is divided into three categories to determine the soil characteristics in each pixel and to calculate the emissivity rate and emissivity difference; 0.2>NDVI, it is considered as dry soil and its radiant power is considered to be equal to 0.978. 0.5 NDVI, it is related to pixels with higher vegetation density and its radiant power is considered 0.985. 0.5>NDVI<0.2, it is based on a combination of pixels relating to vegetation and soil and the radiant power for them can be calculated. The vegetation ratio, that its value can be calculated. The value of each scientific finding depends on its accuracy. To compare the obtained results from the algorithms used to calculate the land surface temperature with the recorded temperature in meteorological station. Results and DiscussionThe results of the present study show that among the 18 algorithms for the land surface temperature estimation for MODIS sensor images, the Sobrino algorithm with RMSE value of 1.79 has the highest accuracy, Cole Casillas and Prata algorithm with RMSE value of 2.85 is in the second position, and also the Salisbury and Sobrino algorithms with RMSE values of 2.39 have the third place for LST calculation among the other algorithms. The Qin algorithm with a RMSE value of 5.28 has the lowest accuracy for LST estimation. Conclusion A review of the data obtained from comparing split-window algorithms shows the overall compliance of the calculated temperatures with the topographic conditions of the region, so that almost the lowest temperature values in all algorithms are related to the parts having more height (mountainous) and green cover of the region and also, temperature values have risen in low-lying areas lacking dense vegetation. Manuscript profile -
Open Access Article
16 - Assessing the relationship between land surface temperature with vegetation and water area change in Arsanjan county, Iran
Ali Ebrahimi Baharak Motamedvaziri Seyed Mohammad Jafar Nazemosadat Hassan AhmadiBackground and ObjectiveLand cover and soil moisture changes have a significant impact on land surface temperature (LST). Therefore, LST can be used to study land cover and desertification changes. Arsanjan County, which is located in the northeast of Fars province, has MoreBackground and ObjectiveLand cover and soil moisture changes have a significant impact on land surface temperature (LST). Therefore, LST can be used to study land cover and desertification changes. Arsanjan County, which is located in the northeast of Fars province, has a relatively good forest and rangeland. Unfortunately, excessive harvesting of the groundwater resources and also reduced precipitation in this area caused to decrease water levels and dried up many wells in this area during recent years. So the area of the farmland and Bakhtegan Lake has decreased in this region during the last decades. However, so far, the condition of the LST and its relationship with land cover changes has not been assessed in Arsanjan County. In this study, spatial-temporal changes of LST and its relationship with vegetation and the water area of Bakhtegan Lake have been studied. Materials and Methods The eleven images related to Level-1 data of Landsat satellite was taken from 2003 to 2018. Since the vegetation situation in the study area is in the best vegetation and water area condition in April and May, so the images related to these months were selected to check the fluctuation of vegetation cover and water level of Bakhtegan Lake. The data pre-processing was performed in three sections: geometric, radiometric and atmospheric correction by ENVI software. The FLAASH algorithm, which is one of the best methods of atmospheric correction, was applied for atmospheric correction. In this study, NDVI was used to estimate the amount of vegetation. The Planck algorithm method was applied to calculate the LST. The change detection process was done using the index differencing method. To classify the LST map and the temporal-spatial changes, the LST difference map was normalized. Then, the normalized image was categorized using the standard deviation parameter in five temperature classes. Results and Discussion In the present study, 11 Landsat images were examined to investigate the spatial-temporal changes in land coverage and LST and the relationship between these two parameters from 2003 to 2018. The NDVI mean value was 0.25 in 2003, which decreased to 0.18 in 2018. On the other hand, the LST mean value had an upward trend as it increased from 29℃ in 2003 to 41.7℃ in 2018. The NDVI mean value was 0.66 in the farmland in 2003, however, its value reached to 0.33 in 2018. In contrast, LST mean value increased in the farmland from 20.9℃ in 2003 to 39.5.5℃ in 2018. Also, the LST mean value in the lake area increased from 20.1℃ in 2003 to 36.5 in 2018. Based on the results, the NDVI mean value in the rangeland and farmland decreased by 0.07 and 0.33, respectively, in 2018. However, due to the positive relationship between NDVI and LST in water-covered areas, the NDVI mean value increased by 0.39 in Bakhtegan Lake area in 2018. In contrast, the LST mean value in the rangeland, farmland and Bakhtegan Lake increased by 12.7℃, 18.6℃ and 16.4℃, respectively, in 2018 compared to 2003. The results indicated a negative relationship between NDVI and LST (R2= 0.862). The LST value decreases by increasing NDVI value in the vegetated area. In contrast, there was a positive correlation between NDVI and LST in salt-marshes and barren areas. According to the results, the highest negative correlation was obtained for the farmland, which was -0.94. The reason for this high correlation can be related to the high density of vegetation cover in agricultural areas. The low negative correlation between NDVI and LST in the rangeland indicates the low vegetation density in rangeland and forest area. In order to study the area of decrease or increase of LST in the farmland, rangeland and water classes, the LST difference map was classified to five categories including very low temperature, low temperature, medium temperature, high temperature and very high temperature. According to the result of LST classification, the highest area was related to the moderate temperature class in all land covers, so that the highest area of this temperature class was associated with the rangeland by 86733 hectares. Since the vegetation density, especially in the farmland, had a significant decrease in 2018 compared to 2003, the area of high and very high-temperature classes increased in 2018, so that their area reached to 4625 ha and 7192 ha, respectively, in the farmland. Also, since the water area of the lake decreased in 2018 compared to 2003, the area of high and very high-temperature classes in these classes reached to 1824 ha and 3919 ha, respectively. Conclusion According to the results, the NDVI mean value in 2018 decreased in the farmland and rangeland and increased in the Bakhtegan Lake area. In contrast, the LST increased in the mentioned areas. The results of the LST classification showed that the highest amount of LST change is related to the moderate temperature class. Since the vegetation density, especially in the agricultural area, had a significant decrease in 2018 compared to 2003, the results showed that the area of high and very high temperatures had a higher increase than low and very low temperatures. Also, since the lake's water level decreased in 2018 compared to 2003, the area of high and very high temperatures in these classes increased. The findings show that there is a negative correlation between vegetation and land surface temperatures. Manuscript profile -
Open Access Article
17 - Extraction of soil moisture index (TVDI) using a scatter diagram temperature/vegetation and MODIS images
Salah Shahmoradi Hamid Reza Ghafarian Malamiri Mohammad AminiBackground and Objective Soil moisture is an important parameter in controlling many processes of the climate system, one of the basic parameters of the environment and its direct impact on the plant, animal and microorganisms, its importance in the global cycle of MoreBackground and Objective Soil moisture is an important parameter in controlling many processes of the climate system, one of the basic parameters of the environment and its direct impact on the plant, animal and microorganisms, its importance in the global cycle of water, energy and carbon, the energy exchange between air and soil is known for its natural water cycle (especially in the distribution of rain between surface runoff and infiltration) and the management of water and soil resources. Soil moisture plays an important role in the interactive processes between the atmosphere and the earth and global climate change. Triangular and trapezoidal methods combining thermal and visible data are the most commonly used methods for determining the amount of soil surface moisture. The aim of this study is to estimate the surface moisture of the soil (TVDI), by the triangular method in the south of West Azerbaijan province using land temperature index (LST) and vegetation index (NDVI), during 2010, 2014 and 2018. Materials and Methods The present study using MODIS timing series images, NDVI index and LST index, to estimate the surface moisture index (Temperature–Vegetation Dryness Index, TVDI), in three time periods including; the first time period from 1 January 2010 to 30 December 2010 and the second period is from 1 January 2014 to 30 December 2014 and the third period is from 1 January 2018 to 30 December 2018. During each period, 12 images were used on the 15th day of each month. Also, surface moisture was estimated by two methods, one was to establish a high regression relationship and remove the minimum temperature, and the second method was to establish a high and low regression relationship of the pixels. To evaluate the accuracy of these two methods, a regression correlation between the results of these methods with the soil surface moisture content of the Agricultural Jihad (30 points) at a depth of 5 to 15 cm was used. The reason for choosing these three years is due to the difference in high rainfall in some months of the studied years. This study was conducted in the south of the province of West Azerbaijan, which is part of the western region of Iran. Results and Discussion The evaporative triangle diagram consisting of the vegetation index and the surface temperature of the earth in 2010 from January to December month has seen many temperature changes. These same changes in the Earth's surface temperature have caused that the graphs have many changes. During the 2010 year, according to the chart, the maximum temperature was August and the minimum was January, and the maximum vegetation was May and the minimum was December. In 2014, the maximum temperature in August and the minimum in January and the maximum vegetation in May and the minimum in January and also this year were relatively warmer and drier than in 2010. The evaporative triangle chart in 2018 is rainier than the other two years studied, and the amount of vegetation and according to the graphs in this year, the maximum temperature in July and the minimum is January and the maximum vegetation is May and the minimum in January. The surface moisture level of the soil in 2010 for the western region of Iran, which is the maximum moisture level in May and the minimum in August. In most of the 2010 moisture index maps, the maximum humidity in the west and the lowest in the South of this region. The results of the moisture index maps in 2014 this year have been relatively drier than in other years studied. In 2014 has little rainfall and vegetation. Humidity changes this year are lower than in 2010. The maximum and minimum humidity in 2014 was between 0 and 0.6. The maximum humidity is June and the minimum is August. The TVDI moisture index maps for 2018 have had more moisture indicators this year than in the other two years. In 2018, heavy rains caused the vegetation to increase and the ground temperature to decrease, and this has led to an increase in the moisture index compared to 2010 and 2014. In 2018, the vegetation reached 0.89. But in other years it has been studied up to 0.7. This year, the high humidity is in May and the lowest in August. The maximum humidity during this year is in the west and the lower is in the south. The results of the TVDI index for 2010, 2014 and 2018, using the second method, the general results of this method are similar to the first method. Based on the results obtained from the accuracy of both methods, we conclude that the accuracy of the first method is better and generally simpler than the second method. In 2018, in May, according to the first method, the amount of R2 = 0.67, and also according to the second method, the amount of R2 = 0.41. Conclusion Estimation of surface soil moisture is essential for optimal management of water and soil resources. Surface soil moisture is an important variable in the water cycle of nature, which plays an important role in the global balance of water and energy through its impact on hydrological, ecological and meteorological processes. Examination of the two methods used indicates that the first method, which was also used in this research in general, has higher accuracy than the terrestrial fields due to the results of image accuracy. In 2010, the months of May and August, according to the first method are R2 = 0.61 and 0.57. In 2010, the amount of R2 according to terrestrial data and the use of the second method in May and August are R2 = 0.43 and 0.47. Also, in 2018, the value of R2 using the first method in May is 0.66. In 2018, the value of R2 using the second method in May is 0.41. The results of the soil surface moisture index, in this study, showed that this model is able to estimate the amount of soil moisture in large geographical areas with acceptable accuracy. http://dorl.net/dor/20.1001.1.26767082.1400.12.1.3.4 Manuscript profile -
Open Access Article
18 - Monitoring land use changes and its relationship with land surface temperature and vegetation index in the southern areas of Ardabil province (Case study: Kiwi Chay catchment)
Shirin Mahdavian Batool Zeinali Bromand SalahiBackground and Objective Irregular and unplanned urban expansion is known as urban sprawl and is characterized by low-density, transport-driven development, spreading out over large swathes of land towards the fringes of established urban centers. It is generally held t MoreBackground and Objective Irregular and unplanned urban expansion is known as urban sprawl and is characterized by low-density, transport-driven development, spreading out over large swathes of land towards the fringes of established urban centers. It is generally held that morphological modification of the urban landscape results in rising urban temperatures and the urban heat island (UHI) phenomenon. The biophysical properties of the urban space are determinants of the local urban climate. When there is significant alteration such as the replacement of vegetation and evaporating surfaces with impervious surfaces, the surface energy budget experiences fluxes which leads to warming at the local scale. Most scientists believe that the Earth's temperature has been rising since the 19th century. Meanwhile, a phenomenon called heat island in metropolitan areas (UHI) has caused a faster rise in temperature in these micro-climates, and in the coming years, the rapid urbanization trend will also increase the slope of temperature rise in cities. According to statistics provided by the United Nations, by 2025, more than 80% of the world's population will live in cities, and this will worsen the situation as cities become warmer. Surface temperature (LST) is one of the most important environmental parameters that is affected by land use change. The purpose of this study is to analyze the land use change in the two periods of 1987 and 2019, to estimate and study the changes in LST and NDVI in the same period, and to analyze the impact of land use change in LST and NDVI and the relationship between all three parameters.Materials and Methods In this study, Landsat 8 satellite images were used from the OLI sensor to extract the land use map and vegetation index, and the TIRS sensor was used to extract ground surface temperature for 2019 also Landsat 5 OLI sensor image was used to prepare land use map and vegetation index. Using visible, near-infrared, and infrared bands, the TM sensor was used to extract the surface temperature using thermal bands for 1987. Ecognition software was used to classify the object. Error matrices and related statistics (overall accuracy, kappa coefficient, user and Producer accuracy of each class) were used to evaluate the classification accuracy. Finally, Pearson correlation analysis was used to analyze the correlation between LST and NDVI, and the Contribution index was used to evaluate the impact of land use on surface temperature.Results and Discussion Investigating land use changes and their relationship with land surface temperature and vegetation index requires determining the type of land use and accurate estimation of land surface temperature and vegetation index. Preparing a satisfied land use map using Landsat satellite images and applying the object classification method Oriented has a relatively high accuracy. The accuracy of land use map classification in 1987, 82.5, and in 2019, 96.1 shows the high accuracy of the land use classification method and land use map. The study of land use changes in 1987 and 2019 in the Givi Chay catchment showed that rangeland use with an area of 1224.18 and 10469.59 square kilometers is the dominant land use, while in 1987, residential use with an area of 66.63 square kilometers and in 2019, water use with an area of 3.77 square kilometers had the lowest area. Also, the most modified use of rangeland use was dryland agriculture (181 square kilometers), which indicates the destruction of rangelands. The results of surface temperature during the 33-year period were evaluated which showed that the average surface temperature in 1987 from 28.39 °C to 38.86 °C and in 2019 from 34.35 °C to 46.62. The temperature has increased so that the average temperature of the whole study area in 33 years has increased by about 7.11 degrees Celsius. This indicates the urban development in the study area. The highest temperature recorded in both periods belongs to dryland agricultural use (38.86 and 46.62 ° C, respectively), which indicates the concentration of heat in these areas. Dryness and harvest at this time can be the main cause of high temperatures of this use. Garden, forest, and water uses showed lower surface temperatures in both periods than other uses. Vegetation areas due to evapotranspiration have a temperature-moderating role and have areas with a minimum temperature in both periods. Water use also has a great effect on reducing the temperature due to its high heat capacity. The use of residential areas compared to rainfed and pasture agricultural uses showed a lower temperature, which can be due to the existence of parks, and gardens that cause evaporation and cooling of the city, as well as factors such as roofing, felt in The reflection of radiant energy has a great share. Rangeland use had high temperatures (36.57 and 44.81 °C, respectively) in both years under study. The reason for the high temperature of this land, according to the study season, which is late June and early July, is an increase in areas free of vegetation or vegetation that is small and scattered. There was also a large negative correlation between LST and NDVI in the two study periods. Rainfed and rangeland agriculture with higher LST have lower NDVI, while vegetation and water have higher NDVI. Aquatic agricultural use, which was mostly observed in the areas around the Givi Chai River, showed lower temperatures due to the presence of moisture and evapotranspiration due to vegetation density. In the study area, suburban areas (gardens) and irrigated arable lands along the Givi Chai River and forests have the highest amount of vegetation index (NDVI) due to their relatively high green biomass, while irrigated areas, rainfed lands, Residential areas, and pastures have the lowest vegetation index. The results of vegetation index analysis for each land use class showed that forests, rainfed agriculture, and rangelands with the highest LST values and the lowest NDVI values while the lowest LST values and higher NDVI values were observed in forest and garden classes. Replacement of vegetation and forests with residential areas causes the conversion of wet soils to impenetrable surfaces, which leads to reduced surface evaporation. Absorbed solar radiation is converted to heat and reflected with higher values of LST. Increased vegetation has reduced the earth's surface temperature, and this is due to the fact that more vegetation leads to more evapotranspiration and transfer of part of the temperature and cooling of the earth's surface. Finally, the calculation of the participation index for each land use class in 1987 and 2019 showed that dryland agricultural use in 1987 and rangeland use in 2019 had the largest share in increasing surface temperature in the study area. According to the time of the selected images, the main reason for this participation can also be attributed to the time of harvest of dryland agricultural products and drying of pastures.Conclusion The results confirm the increase in surface temperature between different land use classes. Rangeland and dry agricultural uses showed higher LST values compared to forests and irrigated agriculture and water areas. High-temperature areas also had low NDVI values. Conversely, low-temperature areas such as vegetation and water had higher NDVI values. In addition, a high negative correlation was observed between LST and NDVI in both study periods. It has also been shown that rangeland and irrigated agriculture have a positive effect on LST, while forests and water have a cooling or moderating effect. Manuscript profile -
Open Access Article
19 - Study and prediction of land surface temperature changes of Yazd city: assessing the proximity and changes of land cover
Mohammad Mansourmoghaddam Iman Rousta Mohammadsadegh Zamani Mohammad Hossein Mokhtari Mohammad Karimi Firozjaei Seyed Kazem AlavipanahBackground and Objective The expansion of urbanization has increased the scale and intensity of thermal islands in cities. Investigating how cities are affected by these thermal islands plays an important role in the future planning of cities. For this purpose, this stu MoreBackground and Objective The expansion of urbanization has increased the scale and intensity of thermal islands in cities. Investigating how cities are affected by these thermal islands plays an important role in the future planning of cities. For this purpose, this study examines and predicts the effect of land cover (LC) changes in the three classes of LC including urban areas, barren lands, and vegetation on land surface temperature (LST) in the city of Yazd during the last 30 years using Landsat 5 and 8 images. This study also examines the effect of the ratio of proximity to the barren land and vegetation classes during this period to examine how the recorded LST is affected by the mentioned ratio.Materials and Methods The LC maps of Yazd city were extracted using a supervised Artificial Neural Network classifier for 1990, 2000, 2010, and 2020. Terrestrial data, google earth, and ground truth maps were used to derive training data. The LST of Yazd was obtained from the thermal band of Landsat 5 and Landsat 8. After that, the LST was classified into six available classes, including 16-20, 21-25, 26-30, 31-35, 36-40, and 41-46°C which has shown that the four last classes play an important role in LST changes in Yazd city during last 30 years. To evaluate the effects of the proximity of barren land and vegetation LC classes on the LST recorded by the sensor, firstly the proximity ratio was calculated in 5×5 kernels for all image pixels. Then the mean of LST was derived based on this ratio of barren and vegetation lands.Results and Discussion The results of this study showed that in Yazd city, from 1990 to 2020, the area of the urban area has grown 91.5 % (33.6 km2) over the last 30 years. Barren and vegetation land, have negative growth in the area over the same period. From 1990 to 2020, barren lands in Yazd experienced a growth -79.4% (21.3 km2), which the sharp growth of urban areas justifies this negative growth in barren lands. Vegetation classes in Yazd from 1990 to 2020, have experienced a growth -68.5% (12.2 km2). The average ground temperature of this city has been constantly increasing during these 30 years. By 2020, the city of Yazd, reaching an average of 38.1°C compared to 29.2°C in 1990, has experienced a 30.4% increase in its average LST. The temperature classes of this city have also moved towards warmer temperature classes in these 30 years. As the main part of the LST area of Yazd, in 1990, in the first place, the class of 26-30 °C with 47 km2 and at the second place the class of 31-35 °C with 26.4 km2 are classified. In 2000, in a reverse trend, the main LST class was 31-35°C with 52.8 km2 as the first place and the 26-30°C class with 20 km2 as the second place. With an increased class, the LST class of 36-40 °C for both 2010 and 2020 with 40.2 and 63 km2 respectively has been recorded as the largest LST class. The LST class of 31-35 °C has been recorded as the second LST class of both years with 33.2 and 9.7 km2, respectively. The difference between these two years is in the growth -70.7% (23.5 km2) of the class area of 31-35°C and the increase of 10.3% (0.8 km2) of the hottest class of the statistical period, 41-46°C, in 2020, compared to 2010. The results of this study also showed that the highest average temperature in all year was recorded for barren lands at 37.3°C. Also, a positive correlation (mean correlation 0.95) was shown between the proximity to barren land cover and the mean LST. However, the sharp upward trend of urban areas in the whole statistical period (91.5% with 33.6 km2) as the second class with the highest average LST after the barren lands with an average of 34.1 °C versus a downward trend of 79.4% (21.3 km2) of barren lands has increased the average LST over a statistical period of 30 years. It is because the decrease of 68.5% (12.2 km2) of vegetation areas as an LC class with the lowest average LST (32.2°C) in the same period, neutralized the effect of decreasing barren lands and intensified the trend of increasing the LST. Meanwhile, a negative correlation (mean correlation -0.97) was established between the ratio of proximity to vegetation and the average LST. The results of forecasting land cover changes in 2030 in the city of Yazd indicate that in a process similar to previous periods, the class of urban areas will increase. This growth will not be significant compared to 2020, with 1.6% (1.1 km2). However, a significant decrease in green areas (vegetation) by -19.6% (1.1 km2) in the same period, along with a slight decrease in barren lands -1.8% (0.1 km2) will cause the earth’s surface to become warmer, and the area of LST classes will be increased by the year. Accordingly, the main area of the LST class in 2030 for the city of Yazd, as in 2020, is forecasted 36-40°C with 58.2 km2 (-7.6% growth compared to 2020). But the dramatic growth of the hottest class of LST over the statistical period (41-46°C) with 166.3% (14.3 km2) growth as the second major class of LST in this year (2030), as well as the negative and dramatic growth of the relatively cooler class 31-35°C with -97.9 % (9.5 km2) in this year indicates the warmer ground surface temperature in 2030.Conclusion The results of this study indicate that in 30 years in Yazd city, the decrease in vegetation in the first place, along with the increase in urban areas in the second place, has caused an increase in LST. Thus, the vegetation class reduces the LST due to its cooling effect considering its water content. In this study, it was shown that by taking all factors into account, the reduction of barren lands will lead to a decrease in LST, and also increasing urban areas with a lower impact factor than barren lands will increase the LST. However, the decrease in the area of green lands (vegetation) in recent years, along with the sharp increase in the area of urban areas has caused an increase in LST. Increasing the proximity to vegetation by creating green areas by increasing the ratio of vegetation in the vicinity of different LC and also reducing the area of barren lands, can be a good solution to deal with the impact of urbanization in recent years on ground surface temperature. Manuscript profile -
Open Access Article
20 - The effect of land use change/land cover on land surface temperature in the coastal area of Bushehr
Fazel Amiri Tayebeh TabatabaieBackground and Objective Urbanization accelerates the ecological stress by warming the local or global cities for a large extent. Many urban areas are suffering from huge land conversion and resultant new heat zones. Remote sensing techniques are significantly effective MoreBackground and Objective Urbanization accelerates the ecological stress by warming the local or global cities for a large extent. Many urban areas are suffering from huge land conversion and resultant new heat zones. Remote sensing techniques are significantly effective in detecting the land use/land cover (LULC) change and its consequences. Several satellite sensors are capable to identify these change zones by using their visible and near-infrared (VNIR) and shortwave infrared (SWIR) bands. Apart from the conventional LULC classification algorithms, some spectral indices are used in detecting specific land features. Normalized difference vegetation index (NDVI) can be considered the most applied spectral index in this scenario. NDVI is a dominant factor in LST derivation processes and is used invariably in any LST-related study. NDVI is directly used in the determination of land surface emissivity and thus is a significant factor for LST estimation. It also determines the LULC categories by its optimum threshold limits in the different physical environments. Being a vegetation index, NDVI depends largely on seasonal variation. Hence, LST is also regulated by the change of seasons. Thus, seasonal evaluation of LST and NDVI is an important task in LST mapping and monitoring, especially in an urban landscape. In this research, LST and NDVI in August in the coastal lands of Bushehr are investigated using Landsat satellite images for the years 1990, 2005 and 2020. The LULC map was obtained with suitable threshold values of NDVI. The objectives of this study are; 1) to analyze the temporal changes of the LST spatial distribution pattern in the study area, 2) to determine the spatial-temporal changes of the LST-NDVI relationship for the whole studied land, and 3) to investigate the spatial-temporal changes of the LST relationship - NDVI in different types of land use/cover.Materials and Methods The land study area of Bushehr city, which is on the northern coast of the Persian Gulf, with dimensions of 20 × 8 km2 an area of 1011.5 km2 and with an average minimum temperature of 18.1 oC and an average maximum temperature of 33 oC, relative humidity between 58-75% and the average annual rainfall is 272 mm. The data used in this research include; Landsat 8 (OLI) and Thermal Infrared Sounder (TIRS) data in 2020; 2005 ETM+ data, and 1990 TM data downloaded from the United States Geological Survey (USGS) (https://earth explorer.usgs.gov). The Landsat 8 TIRS instrument has two TIR bands (bands 10 and 11), in which band 11 has calibration uncertainty. Therefore, only TIR band 10 (100 m resolution) is recommended for the present study. The 10 TIR band was converted to a pixel size of 30 × 30 meters by the USGS cubic convolution method. Landsat 5 TM data has only one TIR thermal infrared band (band 6) with 120 m resolution, which was also converted by USGS to 30 × 30 m pixel size by cubic convolution method. For Landsat TM and ETM+ data, the spatial resolution of 30 m visible to near-infrared (VNIR) bands was used. The maximum likelihood classification method was applied to validate NDVI threshold-based LULC classification. In this study, the mono-window algorithm was applied to retrieve LST from multi-temporal Landsat satellite sensors. NDVI can extract different types of LULC by using the optimum threshold values. These threshold values can differ with respect to the differences in the physical environment. The NDVI threshold limits were applied to the images to extract the different LULC types.Results and Discussion The overall accuracy values of the LULC classification were 73.6%, 83.9%, and 84.6% in 1990, 2005, and 2020, respectively. The kappa coefficients for the LULC classification were 0.77, 0.80, and 0.84 in 1990, 2005, and 2020, respectively. In the present study, the average overall accuracy and average kappa coefficient were 80.7% and 0.80, respectively. Thus, the NDVI threshold method-based LULC classification was significantly validated. The results of this research showed a gradual rising (1.4 °C during 1990–2005 and 2 °C during 2005–2020) of LST during the whole period of study. The mean LST value for three study years was the lowest (30.86 °C) on green vegetation and the highest (49.07 °C) on bare land and built-up areas. The spatial distribution of NDVI and LST reflects an inverse relationship. The best (-0.97) and the least (-0.80) correlation, respectively, whereas a moderate (-0.89) correlation was noticed. This LST-NDVI correlation was strong negative (-0.80) on the vegetation surface. The LST is greatly controlled by land-use characteristics.Conclusion The present study analyzes the spatial, and temporal relationship of LST and NDVI in Bushehr coastal lands using 3 Landsat data sets for 1990, 2005, and 2020. The mono-window algorithm was applied in deriving LST. In general, the results showed that LST is inversely related to NDVI, irrespective of any year. The presence of vegetation is the main responsible factor for high negativity. The LST-NDVI relationship varies for specific LULC types. The green area presents a strong negative (-0.80) regression. The mean LST of the study area was increased by 3.4 °C during 1990-2020. The conversion of other lands into the built-up area and bare land influences a lot on the mean LST of the city. Both the changed and unchanged built-up area and bare land suffer from the increasing trend of LST. This study can be used as a reference for land use and environmental planning on coastal land. Manuscript profile -
Open Access Article
21 - Assessment relations of land use in heat islands using time series ASTER sensor data (Case study: Bandar Abbas city)
Ali aKbar Matkan Ahmad Nohegar Babak Mirbagheri Nahid TorkchinInvestigation of the situation of heat radiation scattering and its relationship by land use types is important in identification of the urban microclimate. Temperature is one of the features that are influenced by environmental conditions and it is considered as one of MoreInvestigation of the situation of heat radiation scattering and its relationship by land use types is important in identification of the urban microclimate. Temperature is one of the features that are influenced by environmental conditions and it is considered as one of quality indices of environmental. According to this study the quality of the environment and the amount of pressure on which come to attention. On the other hand, land use planning as the main core of the urban planning based understanding of the environment is searching to find a way to improvement of environmental, social and ecological system of cities to the aims of sustainable development, especially countries. In this study, the effects of land use/cover and risk of land surface temperature (LST) in the coastal city of Bandar Abbas assessed by using satellite imaging data Terra ASTER for the years 2007 and 2011. After the processing required and using the heat equation, the surface temperature was prepared. Land use layers and harvesting of selected parts and also inferential statistical tests (Kruskal-Wallis test and Spearman correlation coefficient) the relation between land use/cover and surface temperature was calculated. The results showed industrial areas, barren land of high temperature and high coastal areas due to the presence of water due to evaporation and transpiration from vegetation green leaf area of trees and shade temperatures were lower than those of other users. Manuscript profile -
Open Access Article
22 - Evaluation of the geographical factors effect on land surface temperature using satellite imagery in Taftan volcanic cone
Shahram Bahrami Elahe Akbari Atefeh DoranLand surface temperature estimation in the vast area using remote sensing can be eliminated depletion of its monitoring in limited numbers of weather stations. The surface energy balance algorithm for land (SEBAL) used for estimating the temperature in most parts of the MoreLand surface temperature estimation in the vast area using remote sensing can be eliminated depletion of its monitoring in limited numbers of weather stations. The surface energy balance algorithm for land (SEBAL) used for estimating the temperature in most parts of the world. The aim of this research is gaining the land surface temperature and studying its relation to geographical factors like height, geographic direction, lithology and morphometric of some landforms in Taftan volcanic cone. Therefore, by using SEBAL method on ETM+ imagery in 2001 year, heat map of this area is produced. As for performing this method, the corrected thermal radiance, surface emissivity in thermal band, spectral radiance, reflectivity in each bands and surface albedo was calculated. Ridges and thalweg map is produced by studying the regional contours using topographic maps and Google Earth. On the other hand, river maps, digital elevation model, geographic direction and geology are digitized and created. Then by overlapping the mentioned maps with land surface temperature (LST) map and using zonal statistical analysis, the LST is taken in every elevation class, geographic directions, formation and special land forms. Overall, results showed that at higher levels, LST decrease and geographic directions have an important role in temperature rate of cone. The minimum average of temperature and the maximum average of temperature are seen in west direction and east direction, respectively. Furthermore, formations and land forms that have minimum and maximum temperature are located in these directions. So, by regarding temperature conditions in geographic directions and different formations, could plan for implanting compatible agricultural crops and appropriate environmental conditions. Manuscript profile -
Open Access Article
23 - Identification of Geothermal Regions by Examining Vegetation Changes Under Stress By Using of ETM + Sensor and ASTER Sensor (Case Study, Khoy Township)
Tajadin karami kamal rassouli Vahid isazade esmail isazadeThermal remote sensing, as a branch of remote sensing science plays an important role in environmental studies. Thermal sensing is one of the new and low cost methods against ground surveys in remote areas, which provides valuable information from the study area to rese MoreThermal remote sensing, as a branch of remote sensing science plays an important role in environmental studies. Thermal sensing is one of the new and low cost methods against ground surveys in remote areas, which provides valuable information from the study area to researchers in the shortest time. It is possible to prepare a surface temperature map to identify areas prone to geothermal and plant stress by using an infrared thermal band. Which provides the basis for further exploratory studies. In this research, we used the ETM + and ASTER sensors to map the vegetation anomalies using the NDVI index of Khoy city. And plant seasonal variations were examined. Two datasets, one in early summer 2002 and the other in late summer and fall 2002, were derived from Landsat 7 data. By calculating the LST for the ETM + sensor, in this study, changes beyond the normal seasonal changes were considered as thermal anomalies. Also, by calculating the surface temperature by ASTER data, the surface manifestations of these anomalies under dense vegetation were revealed. MODIS sensor images were used to validate LST calculated by ASTER sensor and NDVI and ALI were calculated using it. The results of the present study showed that the identification of geothermal regions has a good spatial correlation with plant stress in Khoy city. ETM + and ASTER sensors, due to their high resolution in the infrared thermal band, 60 meters and 90 meters, respectively, are suitable sensors for calculating the surface temperature and detecting thermal anomalies. Therefore, the image difference method in this study was not a suitable method and did not show good results. Manuscript profile -
Open Access Article
24 - Evaluation Remote sensing of land use effects on land surface temperature gradient using Landsat images: Case study: Kharestan Watershed
Abbasali vali abolfazl ranjbar marzieh mokarram farideh taripanahSeveral factors affect the temperature gradient of the Land surface, one of the factors affecting human activities is land use changes that can lead to global temperature changes. Land surface temperature changes affect the natural climate of the region, so understandin MoreSeveral factors affect the temperature gradient of the Land surface, one of the factors affecting human activities is land use changes that can lead to global temperature changes. Land surface temperature changes affect the natural climate of the region, so understanding its changes and balancing it is essential to understand the indirect effects of human intervention on ecosystems and their management. The aim of this study is to investigate land use, land surface temperature characteristics in each land use as well as correlation between land surface temperature variations and normalized difference index (NDVI). In this study, land use, land temperature and NDVI analysis was used from Landsat 5TM in 1990, 2010, ETM7 2000, and 8OLI for 2017. Land use was studied using supervised classification method. The results showed that the amount of land surface temperature in each land use was different and the maximom amount was found in the bare soil and in the built areas and the lowest in the garden. The difference in land surface temperature between built areas with vegetation in the years 1990, 2000, 2010, and 2017 was 3.58, 2.27, 3.20 and 2.12 ° C, respectively. Also, the difference in temperature between bare soil with vegetation cover in these four periods was 3/3, 0.8, 0.81 and 2.38 ° C respectively. In this study, the relationship between NDVI and surface temperature showed a negative correlation, so that areas with low NDVI had higher temperatures than those with high NDVI. The relationship between vegetation changes and surface temperature changes showed a significant correlation between these two parameters (R = 0.63). Therefore, it can be stated that land uses with more vegetation have lower temperatures than land uses with less cover. Manuscript profile -
Open Access Article
25 - Effect of urban construction on the temperature of the earth's surface (case study: Sahand New City)
Firouz jafaria shiva sattarzadehFollowing the increase in population and the growth of urbanization in recent decades, natural landscapes are being transformed into human landscapes and urban open spaces are being transformed into built-up areas. The purpose of this research is the changes made in urb MoreFollowing the increase in population and the growth of urbanization in recent decades, natural landscapes are being transformed into human landscapes and urban open spaces are being transformed into built-up areas. The purpose of this research is the changes made in urban constructions and the excessive increase of buildings and their relationship with the surface temperature of the earth using Landsat satellite from 2005 to 2020 for the new city of Sahand. The current research is applied in terms of purpose and descriptive-analytical in terms of method, and Global Human Settlement, Built-Up (GHSL) layers related to Landsat images of OLI/TIRS sensor in Google Earth Engine system have been used. The best results for the index of built-up complications were obtained with an accuracy rate of 79.97%, which was considered as the best method for extracting construction phenomena. While in 2010, it shows 45.32%, and the lowest rate of construction development is related to 2005, which showed 16.98%. The highest average air temperature for the LST image from 2010 to 2020 shows more than 16 degrees. In this year, the highest air temperature on the surface of the earth has coincided with the peripheral areas, built buildings and the northwestern parts of the new city of Sahand. Manuscript profile -
Open Access Article
26 - Providing LST map and the estimation of soil temperature by using surface temperature (Case study: the city of Tabriz)
لیلا خدائی قشلاق سید اسدالله حجازی سعید صاحب خیرIn recent years, remote sensing technology has been used in almost all areas, and has been considered as a method of creating and updating data in many countries around the world. However, studies to extract surface temperature, especially in Iran, have been limited by MoreIn recent years, remote sensing technology has been used in almost all areas, and has been considered as a method of creating and updating data in many countries around the world. However, studies to extract surface temperature, especially in Iran, have been limited by infrared band and satellite imagery, and so far the first steps have been taken in this regard. Also, soil temperature is an important parameter in hydrological studies, agriculture meteorology and climatology, which is necessary to measure and predict. This parameter is measured only at synoptic stations, so the lack of it in areas without a station is an important challenge in many agricultural sciences. In this study, Sibal algorithm was used to achieve ground temperature, using Landsat 8 thermal imagery and Emissivity Refrence Chanel method to calculate ground surface temperature. Using surface temperature, soil depth was estimated at six depths of 5, 10, 20, 30, 50, 100 and 120 cm using satellite imagery and remote measurement techniques. The study area is Tabriz city. The results showed that the soil temperature at 5 cm depth in the morning was less than the night temperature, and the daily temperature change at a depth of about 40 cm is insignificant Manuscript profile -
Open Access Article
27 - Evaluation of the relationship between land use, land vegetation, urban development with urban temperature classes using TM Landsat images and NDVI Index (Case study of Kermanshah (
mohammadebrahim afifiThe haphazard urban growth and the increase in population have caused problems for urban communities. Including the phenomenon of thermal islands, which is the result of an unusual increase in temperature of the city compared to its suburbs. In this paper, the condition MoreThe haphazard urban growth and the increase in population have caused problems for urban communities. Including the phenomenon of thermal islands, which is the result of an unusual increase in temperature of the city compared to its suburbs. In this paper, the condition of Kermanshah thermal island in terms of spatio-temporal changes was investigated. The purpose of choosing Kermanshah is its important location and the lack of study in the field of thermal island. The data used in this research include using Landsat 5 multitemporal images b4, b5 and Thermal InfraRed with resolution 30, 120 meters and Landsat 8 b10, b11 with resolution 30 and 100 meters (TM 1992, 1998, 2007, 2011 and OLI/TIRS 2016), NDVI Index, Planck law for the TM images and two-window algorithm for OLI/TIRS images. Then the surface temperature was normalized, its relationship with vegetation loss and land use changes was investigated. The city was classified into five temperature classes from very cool to very hot, the area of each class was calculated and their variations were analyzed. The results showed a direct relationship between the thermal islands of Kermanshah with the city’s construction and land use. In the period of the study (1992-2016), the area of the city has almost doubled with the conversion of 3,800 hectares of agricultural and barren lands into urban areas. It was found that barren land use is the main center of the thermal islands. Manuscript profile -
Open Access Article
28 - Analysing the Quality Karaj City Green Spaces using Remote Sensing Ecological Index (RSEI)
Nazanin Naseri Milad Hosseinzadeh Niri Raoof MostafazadehThe increase of human activities has caused disturbances in human ecosystems and environment in different scales. Remote sensing techniques have been found to be effective for quantifying and detecting ecological changes and can be considered as an alternative for monit MoreThe increase of human activities has caused disturbances in human ecosystems and environment in different scales. Remote sensing techniques have been found to be effective for quantifying and detecting ecological changes and can be considered as an alternative for monitoring spatial changes in the ecological conditions of the environment. Today, the use of remote sensing data for studies related to the quality of the urban environment has also gained a great attention. In this research, the ecological quality of Karaj city's environment was evaluated and analyzed using Landsat series images in 2010 and 2020 by analyzing the main components of greenness, humidity, dryness and heat to determine four remote sensing ecological indicators. Remote sensing ecological indicators used in environmental quality extraction include LST, NDVI, NDBI and WET. The results showed that the quality of the environment of Karaj city has generally decreased from 2010 to 2022 and the average RSEI has decreased from 0.59 to 0.25, which shows the destruction of the environment of this city due to the expansion of its residential parts. Environmental changes in the study area are closely related to human activities in the form of spatial expansion of residential areas and development, which is caused by the immigration of the study area and its proximity to Tehran. The index used in the present research can adequately reflect the spatial changes of environmental quality from different dimensions and is an effective method for comprehensive evaluation of environmental quality and ecological conditions in urban environments Manuscript profile -
Open Access Article
29 - Earth surface temperature monitoring in relation to land use changes Case study: Maragheh Sufi chay basin
mousa Abedini Abozar sadeghi Nazfar Aghazadeh AmirHesam PasbanThe main purpose of this study was to monitor the surface temperature in relation to land use changes with surface temperature using OLI and TM images in the present study. It was used for 2020, and the Landsat 5TM satellite imagery was used to extract land use and its MoreThe main purpose of this study was to monitor the surface temperature in relation to land use changes with surface temperature using OLI and TM images in the present study. It was used for 2020, and the Landsat 5TM satellite imagery was used to extract land use and its thermal band (band 6) was used to extract ground surface temperature for 1992. The monitored method was used to classify land use for 1992 and 2020 and land use changes and the maximum similarity method was used. The obtained results indicate the accuracy of the classification by the basic pixel method. According to the research findings, the total accuracy of the classification maps using the maximum similarity method was 99.84 for 1992 and 99.78 for 2020. According to the land use map of Sufi Chay watershed from 1992, which has been extracted by the maximum similarity method, most of the land uses are primarily related to the type 1 mountainous part, which has an area of approximately 320.42 square kilometers. Then, rainfed land use with an area of 191.09 square kilometers and dense agricultural land use with an area of 74.29 square kilometers have the most areas. The area of land uses in 2020 also shows that the most land uses are mountainous type 1 rainfed and residential. Keywords: Surface temperature, land use change, OLI, QGIS, Sufi chay. Manuscript profile -
Open Access Article
30 - Monitoring of Land Surface Temperature and Analysis of Recovered Temperature in Land Use Surface in Parsabad, Moghan Using ETM and OLI Sensor Images
Batool Zeinali Shahnaz Panahi Shirin MahdavianThe temperature of the land surface is one of the most key parameters that can provide valuable information about the physical characteristics of the earth's surface and the surrounding air. This research was conducted with the aim of investigating and evaluating the la MoreThe temperature of the land surface is one of the most key parameters that can provide valuable information about the physical characteristics of the earth's surface and the surrounding air. This research was conducted with the aim of investigating and evaluating the land surface temperature and analyzing it in relation to land use by the separate window algorithm in Parsabad city with two Landsat 5 and 8 satellite images for August 24, 1990 and 2020. The results showed that in the years 1990 and 2020, generally the western and northwestern parts of the city have forest covers and relatively dense vegetation, while the southwestern parts are generally mountainous and barren. The vegetation index of 1990 and 2020 in the eastern parts of the studied area has an NDVI index higher than 0.3, which indicates medium to high density vegetation. The maximum vegetation index in the range reached 0.55 in August, which is generally related to garden and agricultural lands or dense forest areas in the north and northeast of the range. On the other hand, large parts of Parsabad city, especially in the south and southwest of this city, lack vegetation and are considered barren lands. Also, the results of the land surface temperature evaluation showed that the retrieved spatial average temperature of the earth surface on August 24, 1990, which was obtained at 11:30 local time using the separate window algorithm, was 31.8 degrees Celsius in Parsabad city. While this temperature on this day and at this time in 2020 was equal to 33 degrees Celsius. Manuscript profile -
Open Access Article
31 - نقش سنجش از دور در تعیین محدوده آسایش حرارتی در مناطق شهرداری شیراز
محمود احمدی مهدی نارنگی فرد محبوبه کریمی -
Open Access Article
32 - Evaluation of land use changes and its effect on surface albedo and surface temperature Case study: Cities from Sari to Chalous
Abbas Ebrahimi Taher Safarrad Gholamreza janbazghobadiLand use change in cities leads to changes in surface temperature and surface albedo. Surface albedo plays an important role in land surface energy budget and climate. This article examines the land use changes and its effect on the surface albedo and surface temperatur MoreLand use change in cities leads to changes in surface temperature and surface albedo. Surface albedo plays an important role in land surface energy budget and climate. This article examines the land use changes and its effect on the surface albedo and surface temperature. For this purpose, 3 satellite images of Landsat 5 and 8 were used for August, 1998, 2010 and 2017 in the area of Sari to Chalus cities. The Sabal algorithm was used to extract the surface temperature and surface albedo. Urban thermal characteristics were analyzed by examining the relationships between land surface temperature (LST) and two indices, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-Up Index (NDBI). The results of this research confirm the inverse and significant relationship between LST and NDVI and the direct and significant relationship between LST and each of the variables Albedo and NDBI. On the other hand, during the years 1978 to 2017, built-Up area that form impervious surfaces have been replaced by natural and permeable surfaces, in other words, a decrease in NDVI and an increase in NDBI and Albedo have been observed in the studied area. The surface of the earth has been manifested in cities. Also, the correlation between NDVI and LST is rather weak, but there is a strong positive correlation between albedo, NDBI and LST. The increase in construction in cities has led to an increase in albedo and the subsequent increase in surface temperature due to the increase in impervious surfaces. Manuscript profile -
Open Access Article
33 - Assessing the relationship between urban land use and thermal islands, Case study: Yazd desert city
کمال امیدوار کمال امیدوار سعیده موید فر سعیده موید فر مهران فاطمی مهران فاطمی مهدی نارنگی فرد مهدی نارنگی فردUrban thermal islands are one of the most common urban climatic phenomena in which some urban areas, especially urban centers, are several degrees warmer than the surrounding areas. The study of this phenomenon and its mechanism of study is very important for urban plan MoreUrban thermal islands are one of the most common urban climatic phenomena in which some urban areas, especially urban centers, are several degrees warmer than the surrounding areas. The study of this phenomenon and its mechanism of study is very important for urban planning. This research has been applied in terms of analytical method and in terms of purpose and has been done with the aim of investigating the effect of applications on the temperature of Yazd desert city. To illustrate this relationship, images from the 2005 and 2015 Terra satellites measuring the Aster were used. The results of the studies show that the physical expansion of the city of Yazd in different historical periods, has led to the advancement of this city in the marginal salt and sand surfaces, so that construction and asphalt areas, increase and areas Salt and sand and barren lands on the outskirts of the city have declined. As a result, most of the thermal islands of Yazd city have been formed in marginal areas and barren lands. In this regard, there is a negative correlation between the two variables of vegetation and land surface temperature during the 10-year period, which indicates that the size of the heat islands has increased as the green space decreases Manuscript profile -
Open Access Article
34 - Spatiotemporal Changes in Snow-Cover related to the Land Surface Temperature over Central Alborz
امیرحسین حلبیان امیرحسین حلبیان سینا صلحی سینا صلحیThe area, covered by snow or snow-cover variations, is one of the important factor in climatologic and hydrologic studies, that could be also useful and applicable in water management and environmental studies, specifically when it is combined with topographic character MoreThe area, covered by snow or snow-cover variations, is one of the important factor in climatologic and hydrologic studies, that could be also useful and applicable in water management and environmental studies, specifically when it is combined with topographic characteristics. In this research Land Surface Temperature (LST) and snow-cover interactions were considered. These environmental indicators interactions, combined with focal topographic characteristics such as slope, play a major role in snow-cover persistency. As a result, the influences of these factors had taken into account in central Alborz mountainous belt in Iran northern boundary. To achieve this goal, snow-cover (SC) and land surface temperature (LST) obtained from Aqua and Terra satellite images that are carrying Modis sensor, used in a the temporal range of 2003 up to 2018. Snow cover data with spatial resolusion of 500m analyzied using python programming language. The analysis performed related to the aspect as a major topographic characteristic in the scope of terrain modeling with using moving window and cell by cell raster analysis thechniques. The result, shows a strong relationship between terrain aspect and snow coverage in the central sector of Alborz Mountains. Land surface temperature and snow-cover had an inverse trend, specifically during winter and fall seasons. June LST (Khordad) was high according to the higher zenith angle of the sun in this period of year. There is a clear gap between the LST values of northern and southern aspects of central Alborz that could be result of mountain orientations to the sun rays, higher humidity levels and denser vegetation cover in the northern part. Southward areas, show higher temperature in almost all months. Directional analysis of LST, demonstrated, that maximum levels of LST are observed in the south-faced and specifically southeastward area and the minimum levels observed in northeastward and specifically northward area during all months. Southward area of the alborz mountainous wall, located at the latitude band of 36N, experienced a higher sun ray incident angle and thus having higher LSTs in southern and southeastern parts. Finally in almost all temporal periods (including month, season and year) higher LSTs in southern aspects (South, Southeast and southwest) in compared to northern one (North, Northeast and northwest) has been observed. Manuscript profile -
Open Access Article
35 - A Study of The Relationship Between The Land Surface Temperature and Normalized Indicator of Vegetation in Urban Environment (Case Study: Esfahan Mega City)
Om Salameh Babaee FiniThe purpose of this research is to study the method of distribution of thermal models of land surface and the normalized indicator of vegetation and the relationship between these two variables in the cold and hot seasons in Isfahan city as one of the most important pop MoreThe purpose of this research is to study the method of distribution of thermal models of land surface and the normalized indicator of vegetation and the relationship between these two variables in the cold and hot seasons in Isfahan city as one of the most important population centers in Iran. In line with this objective, employing the four images of the Landsat TM sensor, the land surface temperature and the normalized Index of vegetation in a 19-year time span was made in the dates of January 7, 1991, June 16, 1991, December 29, 2010 and July 4, 2010. The results of the research showed that: On 7 January, 1991, the minimum temperature of-1/1 centigrade, the maximum temperature of 16 centigrade with an average of 5/1 and standard deviation of 1/4 were calculated. On 16 June, 1991, the minimum temperature of 16, the maximum temperature of 33 centigrade with an average of 28 centigrade and standard deviation of 3, On 4 June, 2010, the minimum temperature of 18, the maximum temperature of 37 , with an average of 29 centigrade and standard deviation of 3/2, On 29 December, 2010, the minimum temperature of -3/6, the maximum temperature of 19, with an average of 7/7 centigrade and standard deviation of 3/2 were calculated. Also, the index minimum On 7 January, 1991 of -0/96 and its maximum of 0/78 with an standard deviation of 0/1 and On 16 June, 1991, the minimum index of -0/36, the maximum of 0/66 and the standard deviation of 0/14, On 4 June, 2010, the minimum index of -0/23, the maximum of 0/68 and the standard deviation 0/11 and on 29 December, 2010, the minimum index of -0/4, the maximum of 0/56 and the standard deviation of 0/066 were calculated. The dispersion of the hot temperature range in the regions of 5, 6 and 13 and in the cold period of the year and the hot temperature range in the regions of 6 and 5 and cold in the peripheral regions of Zayandeh Rood (River) in the hot period of the year is observable. Manuscript profile -
Open Access Article
36 - Detection of Heat Islands over Arak City Based on Spatial Autocorrelation Analysis
Mohammad Ghasem TorkashvandThe assessment of urban heat islands is considered as a key variable in the studies of environmental sciences because modeling the interactions of the land surface flux can best respond to many urban problems of modern societies. This study aimed to detect heat islands MoreThe assessment of urban heat islands is considered as a key variable in the studies of environmental sciences because modeling the interactions of the land surface flux can best respond to many urban problems of modern societies. This study aimed to detect heat islands over Arak city and their clustering was done. For this purpose, the satellite images of Landsat 8 (OLI and TIRS) related to August for three consecutive years 2013, 2014 and 2015 were taken from the United States Geological Survey (USGS) Site. For the extraction of Urban Heat Islands (UHI) values of Land Surface Temperatures (LST), Moran's autocorrelation functions and hot spot analyses by MATLAB and Arc GIS capabilities were used. After land surface temperature (LST) calculation, hot and cold clusters of heat islands over Arak were extracted using the hot spot analysis index. To evaluate the factors affecting on the formation and clustering of heat islands in Arak NDVI and NDBI indices were used. The results showed that there is a high correlation between the two parameters, vegetation and urban built areas with land surface temperature so that the vegetation index has moderated and urban built areas has exacerbated the heat islands over Arak city. Comparative assessment of urban heat islands led to the detection of two types of heat islands over Arak: Focal heat islands and the linear heat islands. Moran's spatial autocorrelation analysis revealed that the land surface temperature has spatial structure in Arak; in other words, land surface temperature is distributed in clusters in Arak. Finally, analysis of hot spots is a clear confirmation on focus and clustering of heat islands over Arak by increasing the time period. Manuscript profile -
Open Access Article
37 - Evaluating the relationship between land use planning and the formation of urban heat islands (Case Study: Meshginshahr City)
Houshang sarvar pooran karbasi Mousa VaeziIntroduction: Population growth and urban development have made use of much of the urban land, especially agricultural lands and gardens, for residential, industrial, and transportation uses. This use changes lead to increased pollution and degradation of the environmen MoreIntroduction: Population growth and urban development have made use of much of the urban land, especially agricultural lands and gardens, for residential, industrial, and transportation uses. This use changes lead to increased pollution and degradation of the environment and above all the earth's surface temperature has increased.Research Aim: This study investigates the relationship between land use and thermal islands in Meshginshahr over the 1984, 1999 and 2020 time periods.Methodology: The research method is applied and research in nature. To achieve the goal of the research, after radiometric and atmospheric processing of the images, land surface temperature (LST) and vegetation index (NDVI) were calculated. Then, using the error matrix method, the accuracy and precision of kappa for production maps were evaluated.Studied Areas: The geographical area of this research is MeshginShahr city.Results: The findings indicate that Maps of the heat island show that in 1984 the minimum temperature is 22 and the maximum temperature is 43 ° C. While this situation has been increasing in 2020, the minimum temperature is 29 and the maximum temperature is 63 ° C.Conclusion: The results of the relationship between land surface temperature and land use changes show that the highest land surface temperature is related to urban construction lands and this is a result of reduced vegetation cover and increased impermeable levels. Also, the study of the spatial distribution changes of the surface temperature of the island and the thermal island showed that with the disappearance of vegetation inside and around the city the cool temperature class replaced the warm temperature class. Manuscript profile -
Open Access Article
38 - Analysis Temperature patterns associated with urban land use using remote sensing data (Case Study: Kermanshah city)
mehdi narengifard Ahmad mazidi esmaeil abdoliLand use and land cover diversity and difference on one hand and changes in destruction of green space of the urban landscape as a result of increasing population and expanding dense urban areas on the other hand would result in change in energy balance, heat accumulati MoreLand use and land cover diversity and difference on one hand and changes in destruction of green space of the urban landscape as a result of increasing population and expanding dense urban areas on the other hand would result in change in energy balance, heat accumulation and temperature patterns in urban areas. Thus, the analysis of user relationships and the influence of land cover on slopes temperature can influence each other and play an important role in urban management. In this study, the thermal patterns in Kermanshah, a city in west of Iran as the main center of population which is faced with a growing population and high rates of immigration was studied. The purpose of this study is to extract heat patterns and land use in urban areas using remote sensing data. Therefore, classification of land cover classification based on the maximum likelihood algorithm is applied and the land surface temperature from TM sensor Landsat satellite images using to date: 31 August 2011 was measured. The results represented five temperature ranges and three residential users, vegetation and barren derived from the city in which barren land use, residential and vegetation temperature range of 30-36 ° C and 16-22 and 25-26 have occupied the largest area data Manuscript profile
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