This community innovation has been accepted at the 2025 DHIS2 Annual Conference
Geospatial Analytics for Agricultural Productivity
Edo State’s agricultural sector is critical to its economy, but it faces challenges from inconsistent productivity, which are explained by uneven farmer distribution, inadequate distribution of farming support, lack of insights into the agricultural potential per community and environmental hazards such as flooding. This study leverages geospatial analytics and NDVI (Normalized Difference Vegetation Index) to optimize agricultural planning and resource allocation. NDVI analysis identifies areas with the highest vegetation health and agricultural potential, providing a foundation for strategic investments in farming practices and crop planning. Additionally, flood susceptibility highlights areas prone to flooding and quantifies the impact on farmland and affected farmers. By overlaying flood-prone regions with farmer distribution data, this research identifies communities most at risk, offering insights for disaster preparedness and mitigation strategies. These maps are essential for designing early warning systems, prioritizing resilient infrastructure investments, and planning the reallocation of resources to areas less vulnerable to environmental shocks. The integration of geospatial tools into agricultural policy has broad implications for improving food security and farmer livelihoods in Edo State. This robust body of work is integrated into DHIS2 dashboard where national and subnational stakeholders monitor the impact of flooding within their region. The study demonstrates that combining NDVI with flood susceptibility analysis can guide precision agriculture and safeguard farming communities from climatic risks. The intentional integration of these maps into DHIS2 creates a channel to equip policymakers with data-driven insights, to support sustainable agricultural development, aligning with global efforts to strengthen resilience against climate change and enhance food production systems.
Primary Author: Chinazo Anebelundu
Keywords:
agricultural sector, geospatial analytics, NDVI, agricultural planning, resource allocation, flood susceptibility, vegetation health, crop planning, environmental hazards, disaster preparedness, climate change resilience, sustainable agriculture, precision agriculture, food security