1. ABDUL BASIT - Department of Geography & Regional Planning, University of Balochistan, Quetta Pakistan.
2. ROMANA AMBREEN - Department of Geography & Regional Planning, University of Balochistan, Quetta Pakistan.
3. Dr. RABIA ZAFAR - Environmental Science Department Sardar Bahadur Khan womens university Quetta Pakistan.
4. TEHMOOR REHMAN - Department of Geography & Regional Planning, University of Balochistan, Quetta Pakistan.
5. SABIHA MENGAL - Department of Geography & Regional Planning, University of Balochistan, Quetta Pakistan.
6. SHAIKH SADDAM - Department of Plant pathology, Lasbela university of Agriculture water and marine sciences Uthal,
Baluchistan, Pakistan. National Nematological Research Center, University of Karachi.
7. MARVIN AYEH - Kwame Nkrumah University of Science and Technology, Ghana.
This article describes an improved Change Detection approach based on the Normalized Difference Vegetation Index for satellite image analysis (NDVI). With the help of a few band combinations of remotely sensed data, NDVI uses the Multi-Spectral Remote Sensing data technique to determine the vegetation index, land cover classification, vegetation, water bodies, open areas, scrub areas, hilly areas, agricultural areas, thick forests, and thin forests. Such remote sensing technique is applied in the Kachhi district of Balochistan (Pakistan). The floodwater dispersal project was started in 2008 by the Irrigation and Power Department of the Government of Balochistan. After the completion of the Project in 2016 and later increase in vegetation cover is detected. The flood dispersal structures at six points on river Nari were installed to irrigate the vast agricultural land on both sides of River Nari. The results show the robust change in vegetation cover after the proper distribution of water available for cultivation. Vegetation cover increased from 61082.48 hectares to 138490.38 hectares respectively.
Change Detection, Kachi, Vegetation, NDVI, Remote Sensing.