"*" indicates required fields
Content Type
Persona
When Nearby Nearby Network came to the ESRB with a challenge of delivering hazard information to rural North Carolina communities before disasters cut off connectivity, a panel of experts identified a stack of NASA and open data products already suited to the task.
Nearby Nearby Network brought a challenge to the Earth Science Review Board: How do you get the right hazard information to the right rural community hub before a disaster cuts off connectivity?
Rhonda Jean, founder and CEO of Nearby Nearby Network, is building a resilience hub coordination system in North Carolina that needs to serve communities where cellular service can disappear in a storm and where road access is often the first thing to go. The ESRB convened a panel to help identify appropriate NASA and open data products that can support rural pre-disaster planning.
What the Panel Found
The experts agreed that many of the datasets Nearby Nearby needs already exist and are publicly available through NASA and ESA portals. The recommendation was to prioritize integration and operationalization over building new hazard scoring systems from scratch.
The panel walked through a stack of products matched to specific hazard signals: OPERA DSWx-S1 for flood footprint validation, FIRMS (MODIS/VIIRS) for near-real-time fire detection, GPM IMERG for rainfall accumulation, SMAP for antecedent soil moisture, LHASA v2 for landslide situational awareness, NASADEM for terrain and drainage analysis, and ECOSTRESS for heat stress mapping. Commercial and crowdsourced resources including Maxar Open Data, OpenAerialMap, OpenStreetMap, and Mapillary were also discussed.
From Risk Scores to Actionable Triggers
A major theme of the discussion was the need to move away from abstract numerical risk scores and toward clear, actionable outputs. Instead of telling a community leader that a road has a “95 out of 100 risk,” the panel recommended outputs like: road undrivable, high probability of flooding, or pre-stage alternate route.
The panel outlined a trigger-based workflow model: if rainfall exceeds a threshold and soil moisture is elevated, then elevate landslide watch and push a polygon-based notification to hubs within the affected area. The emphasis was on generating lightweight vector layers tied to specific triggers, not pushing raw raster data to devices.
Designing for Disconnected Communities
Given the rural North Carolina context, the panel recommended an offline-first architecture. The mobile application would serve MBTiles of OpenStreetMap basemaps, push lightweight hazard polygons during connectivity windows, and allow hubs and citizens to submit local updates that synchronize when connectivity is restored. James Haithcoat referenced the Guinea Worm Eradication Program mobile application developed with The Carter Center as a working model for this kind of offline sync pattern.
What This Case Illustrates
This review reinforced something we hear consistently in ESRB sessions. The gap is rarely about missing data. It is about designing systems that translate environmental signals into operational decisions, particularly for communities with limited connectivity and infrastructure. Nearby Nearby Network’s next steps include evaluating the recommended data products, prototyping trigger-based alert workflows, and designing the offline-capable architecture to serve rural resilience hubs.
