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Target detection is the process that helps in determining the changes associated with land use and land cover features with reference to geo-registered multi temporal remote sensing data. This research aimed to utilize change detectionfor investigating the current vegetation cover at(1975-2015) period. The main objectives of this research are collect a number of satellite images in sequence time for the same studied area,these image captured by Landsat (MSS 1975, TM 1985, TM 1995, ETM+ 2005 and Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such as atmosphere correction and rectification has been done. Gap filling was applied on the defected image (Landsat 2005)to remove slice lines. For monitoring the vegetal changes two classification methods have been used such as support vector machine and K-mean clustering. To detect the target (vegetation) two target detection methods have been applied such as matching filter and Constrained Energy Minimization (CEM). Many histogram and statistical properties were illustrated as well as the pixel count and the target area has been computed.

Monitoring the Changes of Vegetal Cover of Karblaa Province (Iraq) using Target Detection and Classification Techniques