mahmood Goudarzi; Mahdi Farahpour
Volume 14, Issue 3 , January 2007, , Pages 432-446
Abstract
According to reports, the problem range managers face is impossibility of distinguish between dry land farming and the rangeland, as the reflectance between dry land farming and rangeland are the same. One solution is usage of temporal images, i.e. times that reflectance between these two features is ...
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According to reports, the problem range managers face is impossibility of distinguish between dry land farming and the rangeland, as the reflectance between dry land farming and rangeland are the same. One solution is usage of temporal images, i.e. times that reflectance between these two features is high. For the experiment rainfed cereal farms and rangelands in Taham region of Zanjan province, characterized as a semi arid area, was selected. Crop calendar (seeding, sowing, harvesting) of rainfed crop was drawn. Outstanding dates, over which differences between natural vegetation and crops was high, were distinguished. Corresponding Landsat ETM images, 8 August 2002, and IRS images (multi-spectral and panchromatic), 16 October 2002, were used. Images were georeferenced using available topographic map to a Universal Transverse Mercator projection using control points. For preparation of base map (ground true) IRS panchromatic images were interpreted and land use map was made through digit screen checking boundaries of the map lead to preparation of the final map. Via Image Classification Techniques, supervised (maximum likelihood and Box classification), unsupervised and principal components analysis were used to create a map. The maps were overlaid on base map (ground true) and accuracy of classified map was assessed. The result showed that it is not possible to distinguish between dry land farms and rangeland with the assistance of image classification technique, in panchromatic images however dry lands could be easily distinguished through the pattern, shape and texture found on images.
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%.