Paper Details

Investigation of forest extends change detection using satellite imagery in Zagros forests (case study in Behbahan Province Hills in Iran)

Kianosh Rostami, Ali asghar Torahi, Shahram Yousefi Khanghah

DOI: https://dx.doi.org/10.12692/ijb/4.2.47-54

Int. J. Biosci. 4(2), 47-54. January, 2014. (PDF)

Abstract:

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 forests and non-forests area 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%. The classification maps of TM and ETM+ overlaid to detect changed and non-changed areas and changing rate. The results showed that 16231.23 hectares of forest areas reduced in this period. The changing rate is 676.3 hectares and 1.06 percent per year. The results showed that the TM and ETM+ satellite imagery able to produce forest map in Zagros forests.