Accuracy Assessment of Land Use/Land Cover Indices for Al-Rusafa in Baghdad Governorate by Remote Sensing Technology and GIS

Abstract

Abstract The management and planning of natural and artificial resources depend on accurately monitoring land cover changes. Land cover change mapping and monitoring used to require expensive field surveys. Remote sensing is cheaper and more practical for mapping land use and cover changes. The Tigris River divides the Iraqi capital, Baghdad, into two parts: Karkh and Rusafa. Al-Rusafa was selected as a study area for current research, which has had rapid population and urban growth in recent decades. The current research applies the support vector machine technique to supervised LU/LC maps’ classification into barren regions, water bodies, vegetation cover and built-up regions. Spectral indicators were calculated: Enhanced Vegetation Index, Modified Normalized Difference Water Index, Normalized Built-Up Area Index, Dry Bareness Index in addition to calculating the accuracy assessment and Kappa coefficient. Using the Landsat 9 satellite image, ArcGIS 10.8 and Envi5.3 software were used to analyze and evaluate the results and field points observed by GPS devices. The results showed that the SVM classification algorithm accurately revealed the categories of LU/LC, where the classification accuracy reached 95%, and that the arid lands covered most of the study area 848.864 km2 and water bodies 76.747 km2, the vegetation and the built-up regions 466.459 km2 and 439.077 km2, respectively. The spectral indices showed slightly different areas of barren lands (DBSI 752.589 km2, 93% accuracy), vegetation (EVI 423.651 km2, 96% accuracy), and water bodies (MNDWI 73.187 km2, 98% accuracy) and built-up areas (NBAI 501,731 km2, 90%accuracy). The Support Vector Machine method outperforms other classification methods, and the spectral indicators employed in this work are useful and dependable for extracting each LU/LC category. In conclusion, Landsat 9 satellite data can reliably and swiftly detect ground cover.