Analysis of Land Cover Dynamics in Duhok District Using LandSat Images and the MLC Algorithm: A Temporal Comparative Study
Analysis of Land Cover Dynamics in Duhok District Using LandSat Images and the MLC Algorithm: A Temporal Comparative Study
Abstract
The study examined the dynamics of land cover changes in Duhok District, northern Iraq, for two different years (2000 and 2025). The research relied on Landsat 7 and 9 satellite imagery, utilizing Geographic Information Systems (GIS) and Remote Sensing (RS) techniques. The Maximum Likelihood Classification (MLC) algorithm was employed for land cover classification.
The results revealed significant changes in the study area, showing a substantial decrease in barren land by (98.69 $km^2$), representing a rate of (-13.29%). In contrast, there was an increase in rangelands (73.67 $km^2$, +32.69%), urban areas (17.45 $km^2$, +76.56%), and agricultural lands (6.76 $km^2$, +35.64%).
Classification accuracy was verified using a confusion matrix based on (217) training samples and (217) ground truth samples for both years. The overall accuracy reached 89.11% for the year 2000 and 95.69% for 2025, with Kappa coefficient values of 0.8582 and 0.9421, respectively. These Kappa values indicate a very strong agreement between the actual land cover and the classification results produced by the model, confirming the reliability of the MLC algorithm in land cover analysis.
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