Supporting Climate and Health Research with Google Earth Engine Tools for Environmental Data Access.
Abstract
Research on climate and health often requires accessing, processing, and harmonizing multiple sources of geospatial data. To develop and implement applications such as disease early warning systems, it is essential to automate these steps to facilitate routine data access. Google Earth Engine (GEE) is a cloud-based platform for geospatial analysis that provides access to a variety of environmental data, including gridded climate datasets as well as satellite remote sensing data products. The main purpose of this project was to develop a set of tools for automatically extracting data from the different APIs exposed by GEE to support the analysis and forecasting of climate-malaria relationships in Ethiopia. All data access and processing steps were carried out in the Google cloud and analysis-ready data files were produced in tabular format (CSV) that summarized environmental data by location and time period. We used the JavaScript API with the GEE Code Editor to develop an interactive browser-based application (as an Earth Engine App). We also used the Python API to develop packages that can be implemented using any Python IDE or accessed from R using the reticulate library. These tools were implemented to access temperature, precipitation, soil moisture, and humidity data from the FEWS-Net Land Data Assimilation System (FLDAS) in support of a national district-level assessment of climate-malaria relationships from 2014-2019. They have also been used to access rainfall data from the Global Precipitation Mission (GPM) and remote sensing data from the MODerate-resolution Imaging Spectroradiometer (MODIS) for malaria early warning in the Amhara region of Ethiopia. We found that accessing data through GEE with these tools requires considerably less time and user effort than downloading the geospatial data and processing them on the client side. The code is publicly available via GitHub and can be adapted for use in different applications.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMIN005..14K
- Keywords:
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- 1916 Data and information discovery;
- INFORMATICS;
- 1934 International collaboration;
- INFORMATICS;
- 1976 Software tools and services;
- INFORMATICS;
- 1996 Web Services;
- INFORMATICS