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Open Access Article
1 - Land use management change in Marvdasht plain - Fars Province
Khatereh Nobaharan Shahla Mahmodi seyad ali abtahiIn Iran, there are many investigations about landuse change which usually mention negative side. In this research landuse/land cover change trend investigate with use of landsat image and Markov chain in IDRISI Andes V15 software at the period of 1990, 2004 and 2018, an MoreIn Iran, there are many investigations about landuse change which usually mention negative side. In this research landuse/land cover change trend investigate with use of landsat image and Markov chain in IDRISI Andes V15 software at the period of 1990, 2004 and 2018, and predicted changes for 2032 in Marvdasht region. There are about 196000 ha, equal to 91%, that used for cultivation, while range land, bare land and urban area are about 20000 ha, respectively 4.9, 2.7 and 1.6 percent of region area. In 28 years, from 1990 to 2018, agricultural and range lands decrease about 9%, while bare lands and urban area increased. At this period bare lands increased from 2.7% to 11.29% of the total region area. In general, the results of this study indicate that in the long-term, agricultural lands are declining and bare land is increasing, Hence immediate management plans are necessary to prevent the destruction of agricultural land. Manuscript profile -
Open Access Article
2 - Investigating Capability and Evaluation of Spatial Temporal Variations in Yasuj in Urban Development
Arezoo salamatnia seyed Ali jozi Saeed Malmasi roya nezakati mojgan zaeimdarSustainable development is a kind of development that responds to the needs of the present generation, without threatening the future generation's capabilities in meeting their needs. So one of the most important steps to achieve sustainable development is to carry out MoreSustainable development is a kind of development that responds to the needs of the present generation, without threatening the future generation's capabilities in meeting their needs. So one of the most important steps to achieve sustainable development is to carry out various environmental studies before implementing any development plan. Background and Purpose: In this study, with the aim of investigating capability and evaluation of spatial temporal variations in Yasuj, efforts have been made to implement weighted Linear Combination Technique in order to predict the capability of the region for urban development. Also satellite images were used to investigate the spatial temporal variation in Yasuj city. Analysis method: In order to investigate the amount of power and evaluation of temporal and spatial variation in urban development, the criteria and sub-criteria were determined based on experts' opinions and previous researches. Then the AHP technique assisted by 30 faculty members and experts was employed to paired comparison dimensions and criteria. After the paired comparison, the information layers were standardized in the Idrisi environment and in the GIS environment. Then the layers were combined to determine the land suitability for Urban development. Afterwards, in order to study the time-shift changes of land use in Yasuj city in the three periods of 1986, 2001, and 2016, Landsat satellite images, TM, ETM + and OLI sensors, which were prepared in the Envi 5.1 software environment, were used. Findings: Based on the land use change trends in the Yasuj area, residential or urban areas have undergone extensive changes that affected environment uses including forests, grassland, agriculture and aquatic structures. The forest, located inside and around the city of Yasuj, provides a lot of ecosystem services for the area, which by city development, these services have been reduced both quantitatively and qualitatively, which should be considered. Discussion and Conclusion: The results of this study can be used as a model for selecting suitable locations for urban development with respect to environmental considerations and results of this work shown that studies based on spatial data, especially on human settlements (due to their inherent nature) can be the basis for accurate planning. Manuscript profile -
Open Access Article
3 - Using satellite imagery and spectral data to estimate the amount of soil organic carbon in central Zagros forests in Khoozestan
saeede esmizade ahmad landi hamidreza matinfarBackground & Objective: Soil organic carbon (SOC) is one of the most important components of soil physical and chemical properties that prevented soil decay and destruction. The objective of the present study is the evaluation of SOC changes using the remote sensing MoreBackground & Objective: Soil organic carbon (SOC) is one of the most important components of soil physical and chemical properties that prevented soil decay and destruction. The objective of the present study is the evaluation of SOC changes using the remote sensing technique compared with field methods at central Zagros forests in Khoozestan province in Iran over the past 2 decades. Material and Methodology: The soil samples were collected randomly from the soil surface (0-10 cm depth) to estimate the SOC concentrations in the laboratory. Analysis of digital data by using Operational Land Imager (OLI) of satellite Landsat 8 and Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7 images in 2016 (the sampling year) was done to estimate surface organic carbon levels of soil. The main objective was to establish soil organic carbon relation with landsat different bands ratios and also herbal and moisture indexes such as NDVI, SAVI, BSCI, NDMI and NSMI corresponding to the SOC values obtained from soil samples of the forest areas in the central Zagros mountain, and for that purpose these data were evaluated using different linear regression methods. Findings: The best fit model of stepwise regression method showed R2 value of 0.435 for landsat 8 and R2 value of 0.501 for landsat 7 and finally based on these results, evaluation of SOC changes occurred in previous years. Discussion and conclusion: Results show the significant relationship between soil organic carbon and the reflectance in the Visible, Near-Infrared and Short-wave Infrared part of the spectrum. Manuscript profile -
Open Access Article
4 - Determination of land surface temperature using Landsat images (Case study: Bushehr coastal lands)
Fazel Amiri Tayebeh TabatabaieBackground and Objective Land surface temperature (LST) has become an important issue in the world today, as it affects the climate and environment at the local, regional and global levels, and these changes in land surface temperature are mainly caused by it arises fro MoreBackground and Objective Land surface temperature (LST) has become an important issue in the world today, as it affects the climate and environment at the local, regional and global levels, and these changes in land surface temperature are mainly caused by it arises from urbanization, and human activities and extreme Landuse and Land-cover (LULC) changes. Due to the limitations of meteorological stations, remote sensing can be used as the basis of many meteorological data. One of the most important practical aspects of remote sensing in climate studies is the estimation of surface temperature. In this research, the temperature of the earth's surface between 1990 and 2018 was extracted from the images of TM and OLI sensors of the coastal lands of Bushehr, using the Stefan-Boltzmann method.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 18.1oC and an average maximum temperature of 33 oC, relative humidity between 58-75% and the average annual rainfall is 272 mm, it’s located in the geographical location of 50°50' to 10°51 E longitude and 28°40' to 29°00' N latitude. The data used in this research include; Landsat 8 (OLI) data in 2018 and TM data in 1990, which were downloaded from the United States Geological Survey (USGS) data center (https://earth explorer.usgs.gov). In order to calculate the parameters related to temperature extraction, the meteorological data of the synoptic stations located in the studied area were used. After taking the images, due to the larger range of the images, the images were cut (Resized) and then the geometric correction of the images was done using topographic maps on a scale of 1/25000 and all the images were adjusted to the UTM coordinate system of the 39 N were adapted. In geometric correction, the RMS error of all images was less than 0.5 pixels. In order to compare the results of Stefan-Boltzmann method for extracting LST with ground data, thermal map data obtained was compared with soil temperature data (obtained from meteorological stations in the selected area). In order to evaluate the Stefan-Boltzmann method from ground data, the Mean Absolute Error (MAE) index statistical method was used.Results and Discussion The average minimum and maximum Land surface temperature (LST) extracted from the 1990 TM image was 26.5 and 45 °C, respectively, and for the 2018 OLI image, it was 30.1 and 48.6 °C, respectively. The results showed that the Mean Absolute Error (MAE) index values for TM and OLI sensors are to 7.1 and 5.6, respectively. The results of the research showed that the Stefan-Boltzmann method provided a reliable result in estimating the Land surface temperature.Conclusion This research aims to extract LST by Stefan-Boltzmann method. The results of this method were estimated using the Mean Absolute Error (MAE) statistical index for the study period (1990-2018). Applying the MAE on the produced thermal maps, it was found that the Stefan-Boltzmann method is suitable for future research in the fields of thermal remote sensing by observing the results of using the MAE index on thermal maps. Therefore, we conclude that the Stefan-Boltzmann method is suitable for estimating the surface temperature of the land in coastal areas. Finally, it is suggested that for quantitatively describing LST patterns a GIS/RS-based method, and methods such as spatial autocorrelation and semivariance are used. Manuscript profile -
Open Access Article
5 - Determination of urban surface temperature using landSat images (Case study: Karaj)
Behrouz Ebrahimi Heravi Kazem Rangzan Hamidreza Riahi Bakhtiari Ayoub TaghizadehLand surface temperature is a key indicator of energy balance. Besides, it serves as input data for models of climate change, agriculture, meteorology, urban heat islands, choosing the best time to agricultural activities, study of volcanic and geothermal activity, and MoreLand surface temperature is a key indicator of energy balance. Besides, it serves as input data for models of climate change, agriculture, meteorology, urban heat islands, choosing the best time to agricultural activities, study of volcanic and geothermal activity, and fire detection. In this study land surface temperature has been extracted by available methods using 4 images of TM and ETM+ sensors of Landsat in span years of 1985 to 2003. The methods of land lurface temperature extraction included landsat project science office, mono window, SEBAL, Stefan-Boltzmann and single channel. Because of the multiplicity of methods and the number of images used in this study using a statistical method is required. It is required to determine the most efficient extraction method of land surface temperature, which is close to the existing field data. The statistical indicator used in this study was a mean absolute error (MAE). The results indicated that Stefan-Boltzmann method was the best method for both TM and ETM+ sensors. The MAE values for TM and ETM+ were 4.3 and 6.8 respectively, which showed a minimum value among other results. Manuscript profile -
Open Access Article
6 - Forest cover density mapping in sparse and semi dense forests using forest canopy density model (Case study: Marivan forests)
Aboutaleb Shahvali Kouhshour Mahtab Pir Bavaghar Parviz FatehiThe main aim of this study was the evaluation of the Forest Canopy Density model (FCDm) for prediction of forest canopy density, using Landsat-7 ETM+. The study area was the eastern part of Marivan city that situated in Kurdistan province. A Landsat image was geo-refere MoreThe main aim of this study was the evaluation of the Forest Canopy Density model (FCDm) for prediction of forest canopy density, using Landsat-7 ETM+. The study area was the eastern part of Marivan city that situated in Kurdistan province. A Landsat image was geo-referenced with sub pixel accuracy. First, all bands (1-5 of ETM+ imagery) except band 6 was normalized and then four main indices of FCD Model, including Advanced Vegetation Index, Bare soil Index, Shadow Index and thermal Index was calculated, and the forest canopy density map was derived finally. Forest's canopy densities according to 6, 4 and three classes were classified. To assess the accuracy of classified maps, a ground truth map using aerial photos with the scale 1:20000 was produced. The overall accuracy and kappa coefficient for classification 6 and four classes were obtained equal to 52%, 0.29 and 53%, 0.30, respectively. Spectral similarity between open density classes and irradiance of background soil in these classes reduced the accuracy as the result. Actually, in the dense forest, the result will be more accurate. According to the results, this method could be relatively desired for Zagro's forests. Manuscript profile -
Open Access Article
7 - Quality assessment and detection of forest area changes using satellite images (Case study: Rustam, Fars)
Mahmoud Ahmadi Mehdi NarangifardThis paper has been conducted to estimate the detection capability of LandSat satellite data for the detection and qualitative assessment of forest area and vegetation changes, land uses and vegetation percent in Rustam city. In this regard, using Landsat satellite imag MoreThis paper has been conducted to estimate the detection capability of LandSat satellite data for the detection and qualitative assessment of forest area and vegetation changes, land uses and vegetation percent in Rustam city. In this regard, using Landsat satellite images (1987 and 2010), forest land use map, Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) were obtained by Maximum Likelihood and Supervised Classification algorithms. The results showed that the area of extracted layers of forests with high, moderate and low density as well as barren regions has been estimated as 48.78, 348.67 and 281.42 and 81.68 km2, respectively. Assessing the classification results indicated that the overall accuracy, producer accuracy and user accuracy were given as 94.3, 91 and 95%, respectively and also, Commission error and Ommission error have been computed as 0.09 and 0.05. The highest and lowest producer accuracy estimated as 99 and 80% was related to low-density and high density forests and the highest and lowest percent of user accuracy given as 100 and 87% was attributed to the barren and moderate density forest. Also, comparing maps of vegetation percent and Ratio Vegetation index during 1987 and 2010 has shown no significant changes. Manuscript profile -
Open Access Article
8 - Modifications in Green Spaces of Kerman, Using Landsat Images Time Series (2000 - 2018)
Hamid Soltaninejad Soroush Khalili Zahra Shahi Mohammad Taghi RazavianThe explosion of the population and the development of cities in the last century have caused many problems, including the destruction of agricultural lands and green spaces, which is the subject of our discussion in this study. The city of Kerman has seen rapid growth MoreThe explosion of the population and the development of cities in the last century have caused many problems, including the destruction of agricultural lands and green spaces, which is the subject of our discussion in this study. The city of Kerman has seen rapid growth in recent years in the city's physical development, with its direct reflection of the loss of green spaces in and around the city. With the help of Landsat images and comparison of land use maps, it is clear that this trend has been rising rapidly between 2000 and 2018. In this research, data gathering was done through field observations and use of Landsat satellite imagery. ENVI, ArcGIS and Google Earth softwares have been used for statistical and visual analyzes. On satellite images in the ENVI software, radiometric correction was performed using Radiometric Calibration, and then by FLAASH Atmospheric Correction, an atmospheric correction was performed to minimize the error. The results show that over the years, almost 11% have been reduced from the share of agricultural lands and wastelands and by contrast, the share of land that has been built has increased the same amount. Therefore, it is possible to make suggestions including the use of infill development for the conservation of agricultural lands, the completion of the green belt of Kerman city by the municipality, construction on the arid lands in the 2nd district of Kerman, preventing land speculation, and fully comply with the rules of comprehensive and detailed plans, especially on urban green spaces. Manuscript profile -
Open Access Article
9 - سنجش میزان برخورداری از فضای سبز در مناطق شهری استان فارس
مهدی نارنگیفرد محمود احمدی اسماعیل عبدلی -
Open Access Article
10 - نقش سنجش از دور در تعیین محدوده آسایش حرارتی در مناطق شهرداری شیراز
محمود احمدی مهدی نارنگی فرد محبوبه کریمی -
Open Access Article
11 - آشکارسازی تغییرات کاربری اراضی با استفاده از دادههای سنجش از دور (مطالعه موردی: دشت بجنورد)
جواد فارسی مریم یوسفی -
Open Access Article
12 - ارزیابی روش رگرسیون لجستیک در بررسی پتانسیل وقوع زمین لغزش مطالعه موردی: حوضه آبریز رودخانه حاجیلر چای
لیلا خدائی قشلاق شهرام روستائی سید اسدالله حجازیارزیابی پتانسیل وقوع زمین لغزش در منطقه ای که به دلیل وضعیت جغرافیایی و ساخت و ساز های انسانی مستعد لغزش می باشد ضروری می نماید. در این مطالعه، جهت بررسی پتانسیل وقوع زمین لغزش، روش رگرسیون لجستیک مورد ارزیابی قرارگرفت . جهت این مطالعه از تصویر OLI_TIRS ، 2014 ماهواره ل Moreارزیابی پتانسیل وقوع زمین لغزش در منطقه ای که به دلیل وضعیت جغرافیایی و ساخت و ساز های انسانی مستعد لغزش می باشد ضروری می نماید. در این مطالعه، جهت بررسی پتانسیل وقوع زمین لغزش، روش رگرسیون لجستیک مورد ارزیابی قرارگرفت . جهت این مطالعه از تصویر OLI_TIRS ، 2014 ماهواره لندست استفاده شد. فاکتورهای موثر وقوع زمین لغزش ( شیب، جهت دامنه، لیتولوژی، کاربری زمین، فاصله از گسل، فاصله از رودخانه، فاصله از جاده، طبقات ارتفاعی ) در محیط GIS آماده و سپس با لایه پراکنش زمین لغزش ها قطع داده شده و نقشه پهنه بندی خطر زمین لغزش در روش فوق تولید شد. نتایج نشان داد که روش رگرسیون لجستیک عملکرد بهتری را در بررسی پتانسیل وقوع زمین لغزش ها در منطقه مورد مطالعه دارد همچنین تفسیرضرایب نشان دادکه ، طبقات ارتفاعی ، شیب و فاصله از گسل نقش مهمی در وقوع زمین لغزش دارند. و با استفاده از نقشه پیش بینی احتمال وقوع زمین لغزش، منطقه به پنج گروه حساسیت تقسیم شد: بسیار پایین، پایین، متوسط، بالا، بسیار بالا. Manuscript profile
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