Optimizing agricultural land use: A GIS-based assessment of suitability in the Sana River Basin, Bosnia and Herzegovina

Abstract

Abstract The research subject is the application of geographic information systems (GIS) in assessing land suitability for agriculture in the Sana River Basin in Bosnia and Herzegovina. The aim of the research is to apply the analytic hierarchy process (AHP) in identifying suitable areas for agricultural production. Within the AHP framework, the following factors were considered: pedology, land use, elevation, slope, aridity index, and distance from rivers. The results of the suitability assessment underwent reclassification (RP) and cluster analysis processes (CAPs). It was found that very unsuitable land (1) covers an area of 0.15% (RP) or 5.83% (CAP), unsuitable land (2) covers 3.44% (RP) or 17.52% (CAP), conditionally suitable land (3) covers 32.11% or 28.47% (CAP), suitable land (4) covers 56.29% or 28.57% (CAP), and very suitable land (5) covers 7.98% (RP) or 19.59% (CAP). At the study area level, a supervised classification process was conducted to identify land use classes: meadows/pastures, water, forest, agricultural, and built-up areas. RP and CAP results were overlaid with supervised classification results to determine the amount of land used for agricultural purposes within each suitability class. It was determined that currently, for agricultural purposes, 0.04 km2 (RP) or 0.88 km2 (CAP) of very unsuitable land (1) is used, 0.41 km2 (RP) or 7.28 km2 (CAP) of unsuitable land (2), 15.75 km2 (RP) or 27.52 km2 (CAP) of conditionally suitable land (3), 185.15 km2 (RP) or 107.06 km2 (CAP) of suitable land (4), and 42.99 km2 (RP) or 101.65 km2 (CAP) of very suitable land (5). The research findings hold substantial importance in elucidating both the potential and constraints of land use practices as a vital natural resource within agriculture. They also have practical importance for relevant institutions in terms of agricultural sector development and making timely land use planning decisions for sustainable development.