Meisam Aramesh; abbas ali vali; Abolfazl Ranjbar
Volume 29, Issue 2 , July 2022, , Pages 146-160
Abstract
Desertification is a serious ecological, environmental, and socio-economic threat to the world, and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. Therefore, in the present paper, changes in cover and desertification of Kashan, Aran and Bidgol ...
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Desertification is a serious ecological, environmental, and socio-economic threat to the world, and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. Therefore, in the present paper, changes in cover and desertification of Kashan, Aran and Bidgol regions in the north of Isfahan were developed using Landsat ETM and OLI data. According to this research, NDVI (Normalized Difference Vegetation Index), TGSI (Topsoil Grain Size Index), and land surface albedo were selected as indicators for representing land surface conditions from vegetation biomass, landscape pattern, and reflection. A Decision Tree (DT) approach was used to assess the land cover change and desertification of the study area from 1995-2020. Temporal changes indicated an increase in NDVI, TGSI, and albedo trends during this period. The spatial distribution of NDVI showed that values greater than 0.5 were observed only in a small part of the west and southwest, while high values of TGSI and albedo occupied a large area of the study area. There was also a correlation between the above three indicators at 95% (R = 0.99). The results also showed that desertification is increasing in the study area, so that the intensity of desertification from 1995 to 2020 in classes without desertification was low, medium, and severe. The high desertification class decreased by 1420.75 square kilometers (13.54%), while severe desertification increased by approximately 1388.8 square kilometers (13.23%). The highest NDVI values were found in the non-desert area and the low desertification class, while the highest TGSI and albedo values were found in the high and severe desertification classes.
Zahra Abolalizadeh; Ataollah Ebrahimi
Volume 22, Issue 1 , June 2015, , Pages 21-30
Abstract
Sabzkouh protected area is located in central Zagros. This area, with a variety of natural ecosystems and landscapes, is very rich from the point of diversity of climate, topography, habitats and wildlife. Its ecosystems, like other semi-arid ecosystems of Iran, have undergone changes in their structure ...
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Sabzkouh protected area is located in central Zagros. This area, with a variety of natural ecosystems and landscapes, is very rich from the point of diversity of climate, topography, habitats and wildlife. Its ecosystems, like other semi-arid ecosystems of Iran, have undergone changes in their structure in recent years. Nowadays, Markov chain models are widely used in ecological studies to predict these changes quantitatively. For this purpose, satellite images and geographic information system were used to predict the future condition of the region using CA-Markov model. Finally, the land cover map of the region for the next fifteen years (2003-2018) was predicted by CA-Markov model. According to the prediction map, an increase in the area of agricultural lands, shrub/brush rangelands and forests of the region was observed, while the area of forbs rangelands and bare lands decreased. The results of these predictions provide a valuable tool to the managers and policy makers of natural resources and environment
Abalfazl Akbarpour; Mohammad bagher Sharifi; Hadi Memarian Khalilabad
Volume 13, Issue 1 , February 2006, , Pages 27-38
Abstract
Land cover information can be used in hydrologic modeling to estimate the value of surface roughness or friction. The objective of this work is comparison of two different methods to provide land cover maps using Landsat images to estimate surface roughness in the manning equation and curve number (CN) ...
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Land cover information can be used in hydrologic modeling to estimate the value of surface roughness or friction. The objective of this work is comparison of two different methods to provide land cover maps using Landsat images to estimate surface roughness in the manning equation and curve number (CN) in SCS method in the Kameh watershed located in the North of Torbat Heydarieh. At the first, Radiometric and Geometric correction performed on ETM+ data. Then with field surveying, The land cover classes were defined and training areas were selected. All of the bands with the exception of band 6 were used in classification. Because of low accuracy of village and road classes, These classes were removed from classification process and for entering these classes in the final map, information from the other layers of GIS system were applied. Results of this work show that in the fuzzy method using 3 layers in classification, The overall accuracy is 75.12% and kappa Index is 0.63. While those of fuzzy method using 2 layers in classification and maximum likelihood method are (73.3%, 0.6) and (72.39%, 0.59) respectively. Therefore the fuzzy method using 3 layers in classification is recommended
Mahmood Goudarzi; Mahdi Farahpour; Alireza Mosav
Volume 13, Issue 3 , February 2006, , Pages 265-277
Abstract
In Iran, like many other developing countries, high population growth rate causes unfairly uses of natural resources and consequently land cover change. Therefore, detection of land cover (rangelands, irrigated and rainfed agricultural lands, urban areas…) changes can influence local planning ...
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In Iran, like many other developing countries, high population growth rate causes unfairly uses of natural resources and consequently land cover change. Therefore, detection of land cover (rangelands, irrigated and rainfed agricultural lands, urban areas…) changes can influence local planning and natural resource management. Present study efforts to find a rapid and exact method of recognition different land covers using Landsat satellite data. Methods used in this research were image enhancement, false color composite (FCC), principal components analysis (PCA) and Image classification, i.e. normalized different vegetation index (NDVI) and supervised classification. A GIS environment, ILWIS software, was used. Results showed that irrigated agriculture, rainfed agriculture, rock out crop, rangeland classes (fair, moderate, poor condition) could be separated with overall accuracy of 89%.