Geographical planning of space quarterly journal

Geographical planning of space quarterly journal

Agricultural Land Suitability Assessment Using the LESA Model: A New Approach to Sustainable Land Management in West Golestan

Document Type : Research Paper

Authors
1 Department of Geography, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran
2 . Department of Desert Areas Management, Faculty of Rangeland and Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Iran
Abstract
In arid and semi-arid regions, the availability of land suitable for sustainable agriculture is often limited by both physical and socio-economic constraints. this study evaluates the agricultural land suitability of the western region of golestan province through the application of the land evaluation and site assessment (LESA) model, integrating geographic information system (GIS) data with local knowledge. the LESA model comprises two principal components: land evaluation (LE), which encompasses soil properties such as salinity, texture, drainage, and topography; and site assessment (SA), which accounts for spatial attributes including proximity to roads, urban centers, water resources, and land-use compatibility. the criteria were weighted using the analytic hierarchy process (AHP) in conjunction with expert judgments from 15 local specialists, maintaining a consistency ratio (CR) of less than 0.1. the final land suitability map was generated using GIS-based tools such as the raster calculator and weighted overlay analysis. the results indicate that only 10.23% of the study area is free from significant agricultural constraints, whereas over 53% of the land is classified as marginally stable or unsuitable for cultivation. comparison with the FAO land classification framework demonstrated that the LESA model yields higher accuracy, primarily because it incorporates socio-economic variables such as accessibility and land-use interaction. field validation and spatial accuracy assessment, based on the kappa index (k = 0.81), confirmed the robustness and reliability of the LESA model. the findings suggest that the participatory and location-specific design of the LESA model provides a more accurate and context-sensitive framework for identifying suitable agricultural lands than conventional evaluation systems. the model can support land-use planners in promoting sustainable land management, particularly in semi-arid regions experiencing intensified pressure on arable resources. future research should aim to enhance the LESA model through the integration of artificial intelligence algorithms and extend its application to other arid and semi-arid regions of iran, thereby improving decision-making processes in land-use planning and natural resource management.
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