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Investigation of land use change detection using satellite imagery (case study in Behbahan Province hills in Iran)

Research Paper | January 1, 2014

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Kianosh Rostami, Shahram Yousefi Khanghah, Amin heydarpur

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J. Bio. Env. Sci.4( 1), 149-156, January 2014


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Change detection using remote sensing data has been intentioned much expansive with researchers in recent years. This study aimed to investigate changes in the area of Zagros forests using satellite imagery using TM and ETM+ Landsat data to achieve the forest changes from 1986 to 2010. We used post classification method to determination of change detection. The radiometric, geometric and atmospheric errors of satellite images is corrected, training samples selected from Land used then images classified using maximum likelihood algorithm of supervised classification. The results showed that the overall accuracy and kappa coefficient of TM classification is respectively 90.86% and 85%, and ETM+ 95.31% and 93%. After classification maps of TM and ETM+ overlaid to detect changed and measure changed and changing position. The results showed that amount of forest land decreased from 40.61% to 14.95% of the total area, while agriculture, pasture and surface water respectively from 2.11% to 5.44%, 56.75% to 75.13% and 0.53% to 2.44%, increased in this period, and land forest to pasture and then pasture to agriculture have been the more changes. The results showed that the TM and ETM+ satellite imagery able to produce Land use map in Mountain regions.


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Investigation of land use change detection using satellite imagery (case study in Behbahan Province hills in Iran)

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