Drone-Based Community Assessment, Planning, and Disaster Risk Management for Sustainable Development

Accessible, low-cost technologies and tools are needed in the developing world to support community planning, disaster risk assessment, land tenure. Enterprise-scale geographic information system (GIS) software high-resolution aerial or satellite imagery which typically not available affordable for resource-limited communities. In this paper, we present a concept of data collection, 3D cadastre modeling, assessment using drones adapted open-source software. Computer vision/machine learning methods used create classified that contextualizes quantifies potential natural existing planned infrastructure. Building type integrity determined from imagery. Potential flood damage building is evaluated as function three mechanisms: undermining (erosion) foundation, hydraulic pressure damage, collapse due water load. Use Soil Water Assessment Tool (SWAT) provides runoff estimates improved features (urban ecology, erosion marks) improve flow direction estimates. A convolutional neural network (CNN) trained find these flood-induced marks drone metric scaled by property value results individual assessments.