Mapping vegetation cover changes in Kirkuk governorate using remote sensing and GIS techniques

• Main Authors: Khursheed, Nawal Kamal, Mustafa, Mustafa Tariq, Alattar, Alyaa Abbas
• Format: Conference Proceeding
• Language: English
• Subjects: Barley; Classification; Corn; Crops; Land cover; Remote sensing; Spectral signatures; Support vector machines; Vegetation; Wheat
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0212579

This research examined the assessment of changes in land cover, particularly vegetation changes. The study was applied to a specific area, the Al-Rashad district in Kirkuk governorate, northeastern Iraq. It searched for the changes in plant cover areas using the spectral signature of crops and supervised classification. To evaluate the vegetation and land cover in the study area, a comparison was made using different datasets with periods 2015, 2018, and 2021. Besides, a spectral signature was used to specify the type of crops obtained from (the Ministry of Science and Technology Department of Space and Communications). A supervised classification approach (Support Vector Machine SVM), was applied for land cover classifications. The land cover variation rates were derived from the Sentinel2 images of the years (2015, 2018, and 2021). The vegetation classes were based on the spectral-spatial analyses of three crops (wheat, barley, and corn). Each crop area had been calculated in each season for three years in the study area. Based on study findings, it was discovered that the vegetation cover had been increased extremely. Vegetation cover area increased 26% and became 322.81 km2 in 2021. Besides, the area of each crop was calculated where Barley and corn have increased in 2021 to become 146.943km2 and 114.351 km2 respectively, while Wheat decreased to become 61.515 km2. Moreover, classification overall accuracy was equal to 85%, 95%, and 85% for 2015, 2018, and 2021 respectively, with kappa coefficient of 0.76, 0.90, and 0.80 respectively.