A GIS and MCDA Framework for Land Suitability Analysis in Sustainable Agriculture - Vaishnavi Joshi; Shreya Singh (International Journal of Land, 2024)
This study examines land suitability for sustainable agriculture by integrating Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) as tools to optimize agricultural planning. Sustainable agricultural practices are increasingly critical to meet global food demands without depleting essential land resources. This research focuses on assessing specific parameters that determine the agricultural viability of land, including soil characteristics, topography, climatic conditions, and water availability. These criteria are integral to understanding how different land areas may support or limit agricultural productivity, and, by extension, their sustainability for long-term farming. The study applies GIS to create spatial models, enabling a detailed visual representation of geographic and environmental factors relevant to agriculture. Through GIS, spatial data can be effectively mapped and analyzed, revealing critical insights about land attributes that may impact crop suitability and productivity. Additionally, MCDA is used to weigh the various criteria, combining quantitative and qualitative data to prioritize land areas based on their agricultural suitability. This dual approach allows for a holistic analysis, as MCDA enables the ranking of land parcels by assigning scores to different factors, making it easier to pinpoint optimal zones. Results show that the GIS-MCDA framework provides accurate and reliable assessments, identifying areas best suited for sustainable agricultural use. This approach can significantly contribute to strategic agricultural planning, enabling decision-makers to focus resources on areas with the highest potential for sustainable crop production. The study findings indicate that areas with high soil fertility, adequate water resources, gentle slopes, and favorable climate conditions rank highest in suitability. Conversely, regions lacking these attributes are deemed less suitable, highlighting areas that may require resource inputs or alternative land management strategies to support agricultural activities. By identifying the most promising agricultural zones, this study supports more efficient resource allocation and sustainable land management practices. The GIS-MCDA methodology introduced here could be instrumental for policymakers, land-use planners, and agricultural managers in developing targeted, location-specific strategies to boost agricultural productivity without compromising future land quality. The integration of spatial data analysis with multi-criteria decision-making presents a robust framework for understanding land potential, providing an evidence-based foundation for sustainable agriculture planning. Through this model, agricultural stakeholders can make informed decisions to enhance productivity sustainably, aligning with the broader goals of food security and environmental stewardship.
Keywords: GIS; Land Management; Land Suitability Analysis; Multi-Criteria Decision Analysis; Sustainable agriculture