Detection of Vegetation Cover Changes from 1988-2022 in the University of Baghdad Campus by Remote Sensing and GIS Techniques (Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI)

Abstract

This study aims to investigate changes in vegetation cover of the University of Baghdad campus by Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) as a tool to determine the changes in vegetation cover on the University landscape were used for the period 1988 and 2022 for two seasons (Winter and Summer). Land cover was divided into four categories: Barren & buildings, Low, Medium, and Dense vegetation. The results showed an increase in NDVI values in winter (-0.2-0.5), and (-0.1-0.9) in 1988, and 2022 respectively, and recorded in summer (-0.3-0.5) and (-0.04-0.4) in 1988, and 2022 respectively. The highest value was recorded in winter of 2022. Barren & buildings recorded the highest value 1470630 Km2 with 43% in summer of 1988 while in 2022 recorded 1411156 Km2 with 40%, for both seasons. The Low vegetation recorded the highest value 130031 Km2 with 377% in winter 1988 and the lowest was recorded at 941671 Km2 with 28% in summer 2022. Medium vegetation was recorded the highest 787580 Km2 with 22% in winter 2022 and lowest 667730 Km2 with 19 %. Dense vegetation was the highest 413614 Km2 with 12 % in summer 2022 while the lowest was recorded 211763 Km2 with 6 % in winter 1988. SAVI values were recorded in winter (-0.3-0.7), (-0.1-0.4) in 1988 and 2022 respectively and in summer (-0.4 - 0.7)(-0.06 - 0.6) in 1988 and 2022 respectively. The results showed slight differences from NDVI values of vegetation cover (Dense). The integration of remote sensing and geographic information systems is an effective and sustainable tool for studying land cover changes in order to obtain reliable and accurate rapid and economical results.