Land suitability assessment for sustainable maize cultivation using analytical hierarchy process based multi criteria evaluation in Gajapati district of Odisha

Published our latest research on GIS and AHP-based land suitability assessment for sustainable maize cultivation in Odisha, India. The study integrates remote sensing, soil, climate, and topographic factors to identify optimal cultivation zones for improving agricultural planning and food security.
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Springer International Publishing
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Landsuitability assessment for sustainable maize cultivation using analytical hierarchy process based multi criteria evaluation in Gajapati district of Odisha - Discover Environment

This study delineates potential areas for Kharif maize cultivation in Gajapati district, Odisha, using a geospatial framework integrating the Analytical Hierarchy Process (AHP) and Multi-Criteria Evaluation (MCE). A combination of climatic, soil, and geomorphological parameters was analyzed to develop a comprehensive land suitability map. Thematic layers—such as elevation and slope were generated from Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data in ArcGIS Version 10.8. Additional spatial layers, including soil texture, temperature, rainfall, nutrient availability, water holding capacity, and pH, were derived from respective datasets. Terrain analysis showed that about 34% of the area has slopes exceeding 30%, representing a major cultivation constraint. Soil texture is dominated by clay (50%) and loam (49%) soils. Climatic assessment indicated favourable Kharif season conditions, with nearly 64% of the area experiencing optimal temperature ranges and over 55% receiving adequate rainfall for maize growth. Soil nutrient analysis revealed adequate nitrogen availability in about 54% of the region, while phosphorus limitations remain a key constraint. Approximately 34% of the area exhibited suitable water-holding capacity, and nearly 44% of the land falls within favourable soil pH conditions, though acidic soils are widespread in several locations. The integrated weighted overlay analysis classified 59.1% of the total area as suitable for maize cultivation, including 43.4% moderately suitable and 15.1% highly suitable land. The results provide spatially explicit guidance for improving crop planning, optimizing land resource utilization, and supporting sustainable maize production and agricultural decision-making.

Glad to share our latest Springer publication focused on sustainable maize cultivation using advanced GIS, Remote Sensing, and Analytical Hierarchy Process (AHP)-based Multi-Criteria Evaluation techniques. This study was carried out in the Gajapati district of Odisha, India, to identify the most suitable areas for Kharif maize cultivation by integrating climatic, soil, and topographic parameters.

The research utilized satellite-derived datasets, soil nutrient information, rainfall, temperature, slope, soil texture, pH, organic carbon, and water holding capacity to generate a comprehensive land suitability map. The findings revealed that nearly 59.1% of the study area is suitable for maize cultivation, including highly and moderately suitable zones, providing valuable insights for sustainable agricultural planning and efficient land resource management.

This work highlights the importance of geospatial technologies in supporting climate-resilient agriculture, improving crop productivity, and strengthening food security in resource-constrained regions.

Honoured to contribute to global research in sustainable agriculture and geospatial applications.

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Remote Sensing/Photogrammetry
Physical Sciences > Earth and Environmental Sciences > Geography > Geographical Information System > Remote Sensing/Photogrammetry
Earth Sciences
Physical Sciences > Earth and Environmental Sciences > Earth Sciences
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