Methods
Beautiful maps are only the beginning. Here is how we make them, which data we use, and what we do when we get something wrong.
Not "glaciers" but "how fast are glaciers shrinking above the cities that depend on them?" The question decides the data.
Open, documented datasets with a clear licence. We note the version, the dates and the resolution.
In QGIS, Python or Earth Engine. Results are compared with a second source or a published figure where one exists.
An honest projection for the question, colour scales readable with colour blindness, and a title that states the finding.
Every map page ends with its data, projection and tools, and links to the original datasets.
House rules
Areas are compared in equal-area projections. Web Mercator is used only for interactive basemaps, and we say so.
Sequential scales for amounts, diverging scales for change around zero. Palettes are checked for common forms of colour blindness.
Estimates, projections and gaps are labelled on the map. Satellite results carry the dates and the cloud cover limits.
Colours are adjusted only for readability, never to change what the image shows. False-colour images are always labelled.
The datasets behind our maps, with their licences and the credit line we use.
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| ERA5 reanalysisCopernicus Climate Change Service (C3S) / ECMWF | Hourly temperature, precipitation, wind and other variables; the reference for climate anomalies | Global, 1940 to about 5 days ago | 0.25° (about 30 km), hourly | CC BY 4.0 (Climate Data Store, since July 2025)Credit: Contains modified Copernicus Climate Change Service information |
| ECMWF open forecast dataECMWF | IFS and AIFS forecasts: temperature, rain, wind, cyclone tracks | Global, up to 15 days ahead; rolling archive of the last 2–3 days | 0.25° | CC BY 4.0, commercial use allowed with attributionCredit: Source: ECMWF |
| Open-Meteo APIOpen-Meteo | Easy API for forecasts and historical weather from national weather models and reanalyses | Global | Depends on the model | Data CC BY 4.0. The free API is for non-commercial use only; sites with ads or subscriptions need a paid planCredit: Weather data by Open-Meteo.com |
| GPM IMERGNASA | Satellite precipitation, every 30 minutes | Global; Early run about 4 hours after observation, Final run after about 3.5 months | 0.1° (about 10 km) | NASA open data; cite the productCredit: NASA GPM IMERG |
| Sea Ice Index v4National Snow and Ice Data Center | Daily and monthly sea ice extent and concentration | Arctic and Antarctic, October 1978 to present | 25 km | Free; citation requiredCredit: Fetterer et al. (2025), Sea Ice Index, NSIDC |
| GlaMBIEWorld Glacier Monitoring Service | Annual glacier mass change by region | Global, 2000 to 2023 | 19 glacier regions | Open access with citationCredit: The GlaMBIE Team (2024), WGMS |
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| USGS Earthquake CatalogU.S. Geological Survey | Earthquake locations, magnitudes and depths; ShakeMap shaking estimates | Global; feeds for the past hour, day, week and month, updated every minute | Event points | U.S. public domainCredit: Source: U.S. Geological Survey |
| NASA FIRMS active firesNASA LANCE | Active fire detections from MODIS and VIIRS | Global, near real time | 375 m (VIIRS), 1 km (MODIS) | NASA open data; include the FIRMS citation and disclaimerCredit: NASA FIRMS |
| Copernicus EMS Rapid MappingEuropean Commission | Flood extent and damage maps for disasters, within hours to days | Activations worldwide | Vector, event scale | Free to view and download (except sensitive activations); check each product’s termsCredit: Copernicus Emergency Management Service |
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| Global Surface WaterEC Joint Research Centre / Google | Monthly water presence | Global, March 1984 to December 2021 | 30 m | Free, without restriction of use; cite the datasetCredit: Source: EC JRC/Google |
| GHSL population and built-up surface (P2023A)EC Joint Research Centre | Population and built-up area by epoch; used to count people exposed to an event | Global, 1975 to 2030 in 5-year steps (2025 and 2030 projected) | 100 m | Reuse authorised with acknowledgementCredit: Source: European Commission, GHSL |
| GHS-SMOD Degree of Urbanisation (R2023A)EC Joint Research Centre | Urban centres, towns, suburbs, villages and rural areas; used to mask out fires in settlements | Global, 1975 to 2030 in 5-year steps (2025 and 2030 projected) | 1 km (30 arc-seconds) | CC BY 4.0, © European UnionCredit: Schiavina, Melchiorri, Pesaresi (2023), GHS-SMOD R2023A, European Commission JRC |
| Global Forest Change v1.13University of Maryland (Hansen et al.) | Tree cover and annual tree cover loss | Global, 2000 to 2025 | 30 m | CC BY 4.0Credit: Hansen et al. 2013, Global Forest Change |
| ESA WorldCoverEuropean Space Agency | Land cover classes, including tree cover | Global, 2020 and 2021 | 10 m | See ESA WorldCover termsCredit: © ESA WorldCover project |
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| Copernicus Sentinel-1 and Sentinel-2European Space Agency / European Commission | Radar images that see through clouds (floods), and optical images (before and after) | Global, every few days | 10 m | Free for everyone, including commercial useCredit: Contains modified Copernicus Sentinel data [year] |
| Landsat Collection 2 Level-2USGS / NASA | Surface reflectance and surface temperature | Global, 1982 to present | 30 m | No restrictions on useCredit: Landsat imagery courtesy of the U.S. Geological Survey |
| Black Marble VNP46A4NASA | Yearly night-time lights | Global, 2012 to present | 15 arc-seconds (about 500 m) | NASA open data; cite the productCredit: NASA Black Marble, VNP46A4 |
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| World Development IndicatorsWorld Bank | GDP, trade, energy, population and hundreds of other indicators by country | About 200 economies, from 1960 | Country, yearly | CC BY 4.0Credit: Source: World Bank, World Development Indicators |
| Our World in DataGlobal Change Data Lab | Curated datasets on energy, health, economy and environment | Global, by country | Country, yearly | OWID charts and data CC BY; third-party data keeps its own licenceCredit: Our World in Data and the original data provider |
| Dataset | What it shows | Coverage | Resolution | Licence |
|---|---|---|---|---|
| Natural EarthNatural Earth (volunteers, NACIS) | Country borders, coastlines, cities, rivers | Global | 1:10m to 1:110m | Public domainCredit: Made with Natural Earth |
| OpenStreetMapOpenStreetMap contributors | Roads, buildings, places; the basemap behind our interactive maps | Global, continuously updated | Vector | ODbLCredit: © OpenStreetMap contributors |
Found a mistake? Write to info@spatialstat.com.
When we find an error, we fix the map or text and add a note at the end of the story saying what changed and when. Significant corrections are also listed here. We do not silently replace published maps.
No corrections so far.
QGIS for most analysis and cartography, Python for repeatable processing, Google Earth Engine for large satellite archives, and MapLibre for interactive maps on this site. Basemaps come from OpenFreeMap and OpenStreetMap.
Field notes
Field notes: one map a week, the story behind it and the data used to make it. Free.