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NAXA came to the Earth Science Review Board with a question that often sits at the center of climate-informed municipal planning. How do you measure heat and cold stress at the scale a local government actually plans at? NAXA is implementing heat-related health risk studies in Sainamaina Municipality and Biratnagar Metropolitan City in Nepal’s Terai…
NAXA came to the Earth Science Review Board with a question that often sits at the center of climate-informed municipal planning. How do you measure heat and cold stress at the scale a local government actually plans at?
NAXA is implementing heat-related health risk studies in Sainamaina Municipality and Biratnagar Metropolitan City in Nepal’s Terai region, in collaboration with IFRC, Swiss Red Cross, Finnish Red Cross, Nepal Red Cross Society, and the Red Cross Red Crescent Climate Centre.
The pilot uses Earth observation data combined with local observations to generate bias-corrected spatial layers of temperature, humidity, and wind, then derives heat and cold stress indices that reflect how people experience thermal extremes at the ward and neighborhood level.
The two pilot areas present different challenges. Biratnagar is a relatively dense urban center in eastern Nepal. Sainamaina includes urban settlements, peri-urban areas, and surrounding vegetative landscapes. Both require analysis that accounts for heterogeneous land cover and settlement structures, not a one-size-fits-all urban heat island study.
What the ESRB Panel Recommended
The expert panel recommended a layered data strategy. For thermal data, MODIS provides temporal consistency and multi-year seasonal coverage, while ECOSTRESS captures higher spatial resolution and diurnal variability. Land cover indicators including NDVI, impervious surface area, and tree canopy cover from Landsat and Sentinel-2 help explain spatial variation in thermal exposure across wards.
For understanding the built environment, experts pointed to building footprint datasets from RAMP, Google Open Buildings, Microsoft, and the Global Human Settlement Layer. GHSL’s recently released DEGURBA classification was flagged as particularly relevant for characterizing the urban-rural gradient across the pilot wards.
A key theme was going beyond temperature alone. NAXA expressed interest in a heat perceptive index that incorporates temperature, humidity, and wind. Experts supported this direction and recommended ERA5-Land for humidity and 10-meter wind speed components, with explicit planning for bias correction against available ground station data.
What This Case Illustrates
This review reflects a pattern we see across ESRB cases. The data often already exists. The real challenge is selecting the right combination of products for the context, designing an analytical workflow that accounts for local conditions, and translating spatial outputs into something a municipal planner can act on. For the NAXA team, the next steps were to assess data availability for the two municipalities, confirm ground station data for bias correction, evaluate building footprint coverage in the Terai, and design the composite stress index workflow.
If your organization is working on climate-informed planning at subnational scale and could benefit from expert guidance on Earth observation data selection, the ESRB is open for case submissions.
