ADVANCEMENTS AND INTEGRATION OF BIOPHYSICAL, SOCIO-ECONOMIC, AND LOCAL KNOWLEDGE IN AGRICULTURAL LAND SUITABILITY ASSESSMENTS: A SYSTEMATIC LITERATURE REVIEW

Land suitability assessments are pivotal for sustainable land use planning, agricultural productivity, and environmental management. Despite substantial advancements, a comprehensive understanding of methodologies, applications, and sustainability challenges across diverse contexts remains limited. This systematic literature review aims to address these gaps by examining advancements, regional practices, and adaptation strategies in land suitability assessments. Using the PRISMA framework, an advanced search of Scopus and Web of Science databases identified 34 eligible studies (n=34) for analysis. These studies were categorized into three key themes: (1) advancements in methodologies, including GIS-based multi-criteria decision-making (MCDM), machine learning, and hybrid models; (2) applications of land suitability for specific crops and regions, highlighting varying ecological and socio-economic factors influencing implementation; and (3) sustainability and adaptation in land use planning, focusing on the integration of climate resilience and resource conservation. Results indicate that GIS-MCDM approaches dominate, representing 65% of the studies, with machine learning and hybrid methods contributing 20% and 15%, respectively. The review underscores the increasing role of advanced technologies such as remote sensing and IoT in improving precision, yet challenges persist in parameter selection, data quality, and integrating socio-environmental dimensions. This review concludes that while progress in methodologies and applications is evident, future efforts must emphasize sustainability and adaptive strategies to address evolving land use challenges. The findings provide critical insights for researchers and policymakers to enhance land suitability assessments and promote sustainable development practices.