Identifying and Prioritizing Spatial Data Required for Effective Agriculture Policymaking: A Comprehensive Analysis Using Analytical Hierarchy Process

This paper aims to identify and prioritize spatial data required for effective agriculture policymaking. The data are identified with the help of a literature review and organized under five dimensions to ease the process of prioritization through the analytical hierarchy process (AHP). The relative importance of the data is determined through an analysis of their priority weights, derived from a comprehensive data analysis. The results reveal that land and resource use emerge as the highest-priority dimension, followed by production and efficiency, climate and environmental resilience, social and economic development, and information and data management. Furthermore, the study identified specific data within each dimension that carry significant weight in policy formulation. The findings highlight the need for a holistic approach that integrates these dimensions and data to develop comprehensive and sustainable agriculture policies. This research provides valuable insights for policymakers, researchers, and stakeholders seeking to address the complex challenges faced by the agricultural sector and foster sustainable and resilient agricultural practices.