United Nations World Food Program

Success Story

Early-warning flood and drought vulnerability platform for APAC

The World Food Programme (WFP) is the food-assistance branch of the United Nations and the world's largest humanitarian organization addressing hunger and promoting food security. Cambodia is one of the most hazard-prone countries in Southeast Asia, a risk further compounded by poverty levels, population growth, change in land use and climate change models predicting the increase of extreme weather events.

Vulnerability Management
Geographic Reach

The PRISM platform is an Asia Pacific wide early-warning vulnerability platform, piloted in Cambodia, to provide WFP operations with real-time monitoring of flood & drought risk indicators and its visualization on an interactive map-based dashboard overlaid with the locations of the most vulnerable populations. This supports disaster management officers with a real-time, early warning and hazard monitoring system. The PRISM team needed a technology partner to combine, clean up and improve two existing WFP vulnerability systems and prepare the new system for scaled deployment and rollout across the entire Asia Pacific region (from Pakistan to Mongolia).

Project Highlights

Over a period of 10 months, Slash refactored the legacy codebase and extended it by ingesting new data sources and processing the data models to display correctly, developing new user-friendly interfaces with different GIS views (such as administrative boundaries), redesigning workflows, adding new user & administrative functions and multi-language support.

Slash migrated the application’s infrastructure on AWS and configured it for scale.

We integrated and ingested various Earth Observation data sources and remote sensors into the system, including GLOFAS, RHEAS, HydraFloods, IDPoor.

The project was documented and handed over to the PRISM team to ease future maintenance and extendability.

The backend is built on php and the web frontend on ReactJS. The GIS system is on ArcGIS and the application on AWS. We built the visual maps based on an original MangoMap implementation. 

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