GIPEX
- Enrol and choose a password: gipex-enrol.html (already enrolled? check your status there).
- Sign in to the GIPEX app with your enrolment email and password: portal.placealert.org/gipex/
- Work through the lessons on this page.
- Take the final assessment: gipex-assessment.html. Score 80% or more and your certificate is issued straight away.
About this handbook
GIPEX turns any study grid into 57 satellite and geospatial environmental-exposure indicators — air quality, climate, vegetation, land cover, population, terrain and road-emission proxies — for places where ground monitoring is sparse. This handbook is the full reference: the variable catalogue and a step-by-step walkthrough of the live app.
Access the app
GIPEX runs in your browser — nothing to install.
Log in with your enrolment email + password. Forgot access? Email [email protected].
The 57-variable catalogue
Every cell of your grid is populated with these indicators, grouped by data source.
| Group | Source / Res | # | Variables |
|---|---|---|---|
| Sentinel-2 Spectral Indices | 10–20 m | 9 | NDVI, NDBI, NDWI, MNDWI, SAVI, MSAVI, GCI, ARVI, EVI2 |
| MODIS Composites | 500 m–1 km | 10 | EVI, NDVI_MO, NDWI_MO, LST_C, LSTN_C, ET, FRP, FireMask, BurnedArea, Soil_Moist |
| ERA5-Land Meteorology | daily | 12 | T2M, DEW, TP, SP, U10, V10, SSR, T2M_MAX, T2M_MIN, WIND_GUST, CLOUD_COVER, EVAP |
| ERA5 Daily Atmosphere | daily | 2 | BLH, MSLP |
| Sentinel-5P / TROPOMI | 7 km | 2 | NO₂, AOD_S5P |
| S5P Precursor & Pollutant Gases | 7 km | 4 | SO₂, CO, HCHO, O₃ |
| Quantitative Aerosol & Model PM2.5 | 1 km | 2 | AOD_MAIAC, CAMS_PM25 |
| Population & Built Env (GHSL) | 100 m | 3 | POP, BUILT_V, SMOD |
| ESA WorldCover | 10 m | 1 | LandCover |
| Impervious Surface (Landsat 8) | 30 m | 1 | NDII |
| Dynamic World Land Cover | 10 m | 2 | DW_label, BuiltUp |
| SRTM Terrain (static) | 30 m | 2 | Elevation, Slope |
| VIIRS Night-time Lights | ~500 m | 1 | VIIRS_NTL |
| Derived | computed | 3 | WS (wind speed), WD10 (wind dir), RH (rel. humidity) |
| Road (OSM) | vector | 3 | EM_m, EH_m, WRND_km_km2 (emission / road-network density) |
What GIPEX does
Study grid (lat/lon cells) → Choose variable groups + date range → Extract from Google Earth Engine + OSM → 57 indicators per cell → Maps · time series · correlations · distributions → Export (GeoTIFF / NetCDF / CSV)
It's a proxy environmental-exposure engine: where ground sensors are scarce, satellites and geospatial data stand in to characterise exposure across space and time.
Your study grid
Upload a grid of points (or a CSV with latitude/longitude), map your coordinate and ID columns, and set the area of interest. GIPEX previews your points on the live map before extraction.
Run an extraction
Pick the variable groups you need, a date range and the number of workers. GIPEX handles the Google Earth Engine sourcing, computes derived variables (wind, humidity) and road metrics, and shows progress as it runs.
Maps
Explore results as point maps or a 100 m pixel surface. Switch basemaps (dark / light / streets / satellite), overlay OSM roads, and read the labelled colour scales. Hover any cell to see the exact value.
Relationships
Use time series, correlation matrices and distribution plots to see how indicators co-vary — and how they relate to PM2.5.
QA & export
Run quality checks (missing data, value ranges, outliers), then export indicators as GeoTIFF, NetCDF or CSV for your own analysis.
Capstone
Build a proxy-exposure surface for your own study area: pick a grid, extract a relevant set of indicators over a meaningful period, map the surface, and export it — with a short paragraph interpreting the pattern.
Final assessment and certificate
When you have finished the lessons and the capstone, take the final assessment: 14 multiple-choice questions, pass mark 80%, up to 3 attempts in 24 hours. Passing issues your Place Alert Labs certificate straight away, with a QR code that anyone can scan to verify it.