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Open Access Article
1 - Investigation of Talar Watershed Health the using Watershed Health Assessment Framework
kaka shahedi behrooz mohseni babak moumeniIntegrated management of water, land and biological resources in a watershed leads to an assured water supply from water resources of that watershed. One of the key components of resource management strategies is to increase the protection of waters (healthy watersheds) MoreIntegrated management of water, land and biological resources in a watershed leads to an assured water supply from water resources of that watershed. One of the key components of resource management strategies is to increase the protection of waters (healthy watersheds). Also, one of the most important and basic issues in sustainable management of the watershed is awareness of watershed health. In this study, by dividing the Talar watershed into 37 sub-watersheds in GIS environment, the watershed health index was evaluated. For this purpose, in each of the sub-watersheds, the main and effective criteria in the health of the watershed were selected. Considering the connections and interactions of the constituent parts of each sub-watershed, the health index was evaluated based on five indicators: geomorphology, water quality, hydrology, biological status and hydrological continuity. The sub-watersheds were prioritized according to each of the indicators and at the end, the final health map was obtained from the combination of all indicators. The results showed that sub-watershed No. 34 with a score of 71.66 compared to the others had the maximum health score and sub-watershed No. 26 with a score of 40.79 had the minimum health score. The health status of the sub-watersheds also showed that 24 sub-watersheds are in the 40-60 class and in the average level and the rest (13 sub-watersheds) are in the 80-60 class and have high health. The results of watershed health assessment parameters for each health component can be used to advance the main watershed management planning process at the watershed scale based on specific management objectives. Also, by combining any of the other sub-parameters in the Talar watershed, the priority of the areas in terms of watershed health can be determined. Manuscript profile -
Open Access Article
2 - Vegetation Vulnerability Probability Index: A Method for Determining Desertification Risk
Esmail Heydari Alamdarloo Pouyan Dehghan Rahimabadi Hassan Khosravi Javad Rafie Sharifabad Hassan BarabadiDetermining desertification risk can be a good way to prioritize an area for management and control of the desertification process. One determinant of desertification risk is the use of the Probability of Vegetation Vulnerability Index (PVVI). For this purpose, in this MoreDetermining desertification risk can be a good way to prioritize an area for management and control of the desertification process. One determinant of desertification risk is the use of the Probability of Vegetation Vulnerability Index (PVVI). For this purpose, in this study, LST and EVI of MOD11A2 and MOD13A2 products, respectively, from MODIS sensors were used to calculate TCI and VCI to estimate VHI in Yazd province from 2001 to 2019. VHI, which indicates the severity of drought, was classified into five classes. Then, the probability of occurrence for each class was calculated and multiplied by the weight of each class, which was between zero and 4 based on the severity of the drought. Finally, by adding the values obtained for each class, PVVI was calculated. The results showed that in the western, eastern, and southern parts of Yazd province, the risk of vegetation degradation and consequent desertification is generally higher than in other areas. The highest probability of Non-drought class occurs in Abarkooh (VHI = 68.34) and the lowest is in Ardakan (VHI = 53.59). Abarkooh with 14.03% and Ardakan with 46.02% have the lowest and the highest areas in the high class of PVVI. Also desert areas and uncovered lands, such as Abarkuh, were at low risk of desertification, which could be due to the ecological inability of this area to regenerate the vegetation cover. In general, the evaluation of the results obtained in this study showed that PVVI can distinguish real deserts from the areas that are at risk of desertification. Manuscript profile -
Open Access Article
3 - Comparison of soil organic carbon estimation using remote sensing and Near Infrared spectrum in forest and agricultural land uses in Gyan area, Hamadan province
Soheilasadat Hashemi Parinaz AbdoliIn this study, the relationship between spectral reflections using Landsat 8 satellite sensors and near infrared spectrum with 48 soil samples were investigated in agricultural and forestry uses in Gyan Nahavand, Hamadan province . Soil samples were collected from 0-30 MoreIn this study, the relationship between spectral reflections using Landsat 8 satellite sensors and near infrared spectrum with 48 soil samples were investigated in agricultural and forestry uses in Gyan Nahavand, Hamadan province . Soil samples were collected from 0-30 cm depth, randomly. The analysis of the correlation between main bands, artificial bands and soil surface organic carbon, as well as vegetation indices, composition of indicators and soil surface organic carbon were performed. Spectral analysis of soils using field spectrometer with wavelength range of 350-2500 nm was conducted. After recording the spectra, a variety of pre-processing methods were evaluated. The results showed that in the remote sensing method, only the 11 band shows a significant correlation at the level of 5% with organic carbon in agricultural. Also, band composition (band7/ band8) had a significant correlation at the level of 1% with organic carbon content. Three vegetation indices, NDVI, DVI and RAI with organic carbon showed a significant correlation at the level of 5%. The correlation between the calculated organic carbon in the laboratory and the image in agricultural land use was achieved R2 = 0.36. While the correlation of calculated organic carbon in the laboratory and the image was calculated (R2=0.32) at all points. In the spectroscopy method, the highest correlations were observed at wavelengths of 1404, 1907, and 2216, respectively. Among the fitted models given by the multiple regression, stepwise model is proposed for the estimation of organic carbon, a suitable model. Consequently if the number of samples is very low, the laboratory method may be appropriate, but if the number of samples is too high, the spectroscopy method is appropriate to save time, and in order to save costs. Due to the high cost of spectroscopy in Iran, the method of remote sensing is propose as appropriate method. Manuscript profile -
Open Access Article
4 - Comparison of the effectiveness of machine learning methods in modeling fire-prone areas (Ilam Province, Darehshahr City)
maryam mohammadian Maryam Morovati Reza OmidipourFire is one of the most important natural hazards that has a great impact on the structure and dynamics of natural ecosystems. Due to Iran's location in the arid and semi-arid belt of the world, a large number of human-made and natural fires occur in different regions o MoreFire is one of the most important natural hazards that has a great impact on the structure and dynamics of natural ecosystems. Due to Iran's location in the arid and semi-arid belt of the world, a large number of human-made and natural fires occur in different regions of the country every year. Therefore, determining sensitive areas to fire occurrence plays an important role in fire management in natural resources. To do so, the current study aims to identify fire-prone areas in Dere Shahr city in Ilam province using two machine learning of random forest (RF) and support vector machine (SVM) and 2024 fire occurrence points. Environmental factors were prepared in categories including topographical factors (altitude, slope direction, slope anlgle), climatic factors (rainfall, relative humidity, wind, temperature), biological factors (vegetation and soil moisture) and man-made factors (distance from residential areas, distance from road, distance from agricultural land, distance from river). The model’s accuracy was evaluated using the area under the curve (AUC) in the ROC curve and cross-validation statistics. Examining the AUC index showed that both models had good accuracy, although the RF model (AUC = 0.97) had higher accuracy than the support vector machine model (AUC = 0.86). According to the results of RF model, about 60% are in the low-risk class and about 20% are in the high fire risk class. Investigating the contribution of the factors affecting the occurrence of fire showed that man-made factors (distance from residential areas) and climatic factors (temperature) played a more important role in areas with a history of fire. Therefore, increasing public culture and reducing dangerous behaviors in nature can reduce the occurrence of fire in this area and contribute greatly to the protection of the environment and preservation of natural resources. Manuscript profile -
Open Access Article
5 - Effects of Land Use and Land Morphology on Land Surface Temperature: A Case Study for Bojnourd City, North Khorasan
zahra parvar marjan mohammadzadeh sepideh saeidiUrbanization can affect land surface temperature (LST) on a global scale by changing the natural land forms. Reducing the consequences of climate changes, requires to develop a coherent land use/cover management plan that restricts unplanned urban expansion and increase MoreUrbanization can affect land surface temperature (LST) on a global scale by changing the natural land forms. Reducing the consequences of climate changes, requires to develop a coherent land use/cover management plan that restricts unplanned urban expansion and increases green cover. The purpose of this study is to investigate how features and spatial patterns of urban areas and its surroundings affect the LST of Bojnord city. For this, a split-window algorithm (SWA) used for land surface temperature (LST) retrieval from Landsat 8 TIRS of 2021. Based on the results, the main centers of high heat emission in urban areas such as public facilities, car parks and industrial areas have higher LST (more than 38 °C) compared to urban green spaces (less than 36 °C)c, which are cooler parts of the city. Comparing the results with MODIS nighttime LST reveals the different behavior of LST in day and night in urban and non-urban areas. In this study, the difference between day and night LST was revealed using MODIS nighttime LST. The spatial autocorrelation result show the contrast of LST behavior in urban and peri-urban fabric in semi-arid regions. The presence of hot spots in permeable surface areas such as agricultural land and cold spots in impermeable areas indicate the opposite effect of urban heat island in such areas. Understanding the complex interactions of urban land uses and LST by considering regional climate patterns can help managers and urban planners to improve the quality of life in urban areas. Manuscript profile -
Open Access Article
6 - Spatio-temporal Variations of Snow-covered Days in the Northwest of Iran using Remote Sensing Data
Abbas Kashani Bromand Salahi Amirhossein Halabian Batool ZeinaliIn this research, the spatiotemporal variations of snow-covered days (SCDs) in this region were analyzed using the data of the sixth version of MODIS Terra and MODIS Aqua sensors on a daily basis in the period of 2003-2020. In order to reduce the cloud cover effect, thr MoreIn this research, the spatiotemporal variations of snow-covered days (SCDs) in this region were analyzed using the data of the sixth version of MODIS Terra and MODIS Aqua sensors on a daily basis in the period of 2003-2020. In order to reduce the cloud cover effect, three algorithms were applied to the data. For the digital elevation model, the Digital Surface Model (DSM) of the Japan Space Exploration Agency was used. The relation between two snow-cover phenological components (SCAs and SCDs) and the relation between the SCDs and the altitude were investigated. The findings show an increase in SCDs in the months of November, December, and January. Maximum SCDs are observed in January in Sabalan Mountain and then Sahand. The reduction of SCDs in the spring and summer months is also affected by the two factors of latitude and altitude. The absolute maximum of SCDs in this region is observed at 160 days/ year in the mountain of Sabalan. Examining the changes in SCDs in March and April shows a decrease in SCDs in high-altitude classes. At the same time, it shows the increasing pattern of SCDs in November and December at many altitude levels. Analysis of the relation between SCA and SCDs in different months illustrated that SCAs has decreased in regions with more SCDs (heights) due to the reduction of topographic areas. The relation of SCDs and altitude also showed that the minimum of SCDs occurred in all altitude levels (even altitudes above 3500 m with 4 days) in August and the maximum occurred in December with 22 days at the altitude of 3500 m. SCDs decrease with increasing altitude in mountainous areas of 3500 to 4000 m, due to the increase of land slope and instability of SC in steep areas. Manuscript profile
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