Monitoring LULC Changes in the Semi-Mountainous Region of Duhok Governorate Utilising Landsat Imagery and SVM - Dastan Fathi Ahmed; Nashwan Shukri Abdullah (Zanco Journal of Human Sciences, 2026)
This study analyses long-term changes in land use and land cover (LULC) in the semi-mountainous region of Dohuk Governorate in the Kurdistan Region of Iraq during the period 2000-2023, utilising Landsat satellite imagery (Landsat 5 TM and Landsat 8 OLI), and Machine Learning (ML) classification techniques. The terrain of the study area is characterised by an intertwined landscape, combining plateaus and agricultural plains. This creates spectral challenges in distinguishing between similar land categories and makes the area an ideal model for testing the effectiveness of ML algorithms in complex environments. Using the ArcGIS 3.5 environment, supervised classification was performed employing a support vector machine (SVM) algorithm. The results demonstrated clear changes in LULC patterns, with the planted/cultivated category increasing from 26.5% to 31.3%. The developed area also increased from 3.5% to 7.4%, while barren land decreased from 42.1% to 35%. Overall classification accuracies were 99.04% for 2000 and 97.10% for 2023, with Kappa values of 0.9868 and 0.9609, respectively, indicating high classification performance. Major LULC changes that occurred in the study are, including the conversion of large areas of barren to planted/cultivated and herbaceous categories, reflecting the effects of urban expansion and unsustainable land use in the study area.