Our Retrieving Environmental Analytics for Climate and Health (REACH) applications gathers environmental data via Google Earth Engine (GEE). GEE is a cloud-based platform for hosting satellite imagery. GEE also provides tools to process these remote sensing images and other geospatial datasets. Instead of downloading the raw satellite files and processing them on your own computer, which requires significant internet bandwidth and processing power, these steps are done in the cloud. And at the end, we only need to download the summarized output.
There are three available tools:
- A Javascript version to run in the GEE Code Editor in a browser (this repository).
- A web-based GEE app at https://dawneko.users.earthengine.app/view/epidemiar-ethiopia-demo.
- A python package with functions that interface with GEE and can optionally be called from an R script, see https://github.com/EcoGRAPH/epidemia_gee for python package and R script in this repository.
We use this environmental data to feed into our Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) Forecasting System. This is a set of tools coded in free, open-access software, that integrate surveillance and environmental data to model and create short-term forecasts for environmentally-mediated diseases.
For more information on EPIDEMIA, please see http://ecograph.net/epidemia
Version 3.4 Javascript GEE release notes:
- Updated LST product to MODIS 6.1.
- Added evaluate() asynchronous calls to prevent UI from hanging at different calculation steps.
- Removed .If() statements.
- Aligned formatting and style to GEE style.
Associated article:
Wimberly MC, Nekorchuk DM, Kankanala RR. Cloud-based applications for accessing satellite Earth observations to support malaria early warning. Sci Data. 2022 May 16;9(1):208. doi: 10.1038/s41597-022-01337-y. PMID: 35577816; PMCID: PMC9110363. https://www.nature.com/articles/s41597-022-01337-y
See also Chapter A1.6 in 'Cloud-Based Remote Sensing with Google Earth Engine' for a more in-depth review of an Amhara region version of the Javascript GEE code. Available online at https://www.eefabook.org/