Flood and drought monitoring pipelines in Google Earth Engine

The problem

Agencies responsible for disaster response or agriculture often have access to free satellite archives but not the processing chain that turns them into timely, trustworthy maps. One-off analyses go stale after a season, and mountainous terrain, cloud cover and inconsistent preprocessing make results hard to compare from one event to the next. What is needed is a documented, repeatable pipeline that produces the same product every time new data arrives.

What you get

• Google Earth Engine scripts (JavaScript or Python API) for flood-extent and/or drought-indicator time series over the agreed area
• Export workflow to GeoTIFF or NetCDF with consistent naming, projections and metadata
• Scheduled update procedure (cron or equivalent) with basic QA/QC checks
• Validation notes comparing outputs against available reference data supplied by the client
• Technical documentation and a hand-over session for the client's analysts

How it works

1. 1

   Scope

   Agree the hazard, area of interest, time window, update frequency and who will use the output, and identify which satellite and reanalysis datasets suit the question (for example Sentinel-1 SAR for flood extent under cloud, or rainfall and vegetation records for drought).

2. 2

   Prototype

   Build the time-series method in Earth Engine for a reference event or season and review the maps with the client's technical staff.

3. 3

   Validate

   Check results against reference data or local knowledge, tune thresholds and masks, and record known limitations.

4. 4

   Automate

   Turn the prototype into a scripted pipeline with exports, logging and QA/QC so new data is processed without manual steps.

5. 5

   Hand over

   Deliver code, documentation and a walkthrough so the client's team can run and adapt the pipeline themselves.

Tools

• Google Earth Engine
• Python (xarray, NumPy, Pandas)
• Sentinel-1 GRD
• Sentinel-2 L2A
• CHIRPS
• MODIS
• GDAL
• Git