Geoinformatics-Based Automated Landform Classification and Analysis of Their Relationship with Landslide Susceptibility in Akre District, Kurdistan Region, Iraq

Landforms are fundamental components of landscapes and pivotal elements within geomorphology. The comprehensive classification of landforms necessitates an advanced quantitative methodological approach capable of extracting discernible integral elements and patterns from Digital Elevation Models (DEMs). Identifying these patterns constitutes a crucial initial stage in recognizing and delineating landforms. The main objective of this research is to employ the Geomorphons technique at various scales, including neighborhood sizes of 5x5(3.9 km2), 10x10(15.6 km2), and 25x25(97.6 km2) cells to autonomously categorize Geomorphic units (landforms) derived from 12.5-meter resolution ALOS PALSAR DEM within the SAGA-GIS software framework. Geomorphon is an effective model for characterizing the earth's morphology, encapsulating micro-landscape structures. Subsequently, the landform classes were correlated with landslide susceptibility zones through sophisticated spatial analysis functions in the designated area. The study area was classified into 10 distinct types of the most prevalent geomorphic units, including flat, valley, slope, foot slope, peak, pit, ridge, hollow, shoulder, and spur. The results indicated that the predominant landform type observed is closely associated with slopes, while the least prevalent is flat terrain. Landform patterns exhibit a strong correlation with natural hazards, particularly landslides. Notably, approximately 100% of the flat regions are situated within low and very low landslide susceptibility zones, while more than 45% of the summit, ridge, shoulder, spur, and slope areas are characterized by high to very high landslide risk zones. The insights gained from this study are valuable for categorizing zones susceptible to landslide challenges. Understanding landforms is a critical parameter applicable to natural calamity assessment and future master planning in the Akre district of northern Iraq.