Expanding Earth Science Data Access for Public Health Research and Applications
Michael Wimberly - PI, South Dakota State University
Increased awareness of the effects of climate and land use change on human health has highlighted the need to incorporate remotely-sensed environmental monitoring data into epidemiological research and public health applications. Satellite remote sensing is a critical source of information about climatic variability that provides consistent, repeatable environmental measurements across nearly the entire surface of the Earth. However, disciplinary and technological barriers still limit its widespread application in the public health arena. To bridge this gap, we have developed the Epidemiological Applications of Spatial Technologies (EASTWeb) software tool to provide health scientists with automated and customizable access to earth science data.
EASTWeb is an open-source, client-based application that automatically connects to online archives and acquires reprojects, mosaics, and acquires, processes, and summarizes selected remote sensing datasets. The raw data are then used to calculate and summarize a variety of environmental metrics which are summarized and stored in a relational database. The software first builds a historical database, and then automatically updates it as new data become available. Users can query these data and integrate them into geographic information system (GIS) and statistical analysis software for analysis and modeling. EASTWeb is programmed using JAVA for user interface development and overall system control. Spatial analyses are carried out using the Geospatial Data Abstraction Library (GDAL) open source geospatial library. PostgreSQL is used to store and manipulate the resulting data summaries. The current version processes and integrates data from multiple online archives including NASA's Land Process Distributed Active Archive Center (LP DAAC) and Goddard Earth Science Data and Information Services Center (GES DISC), and US Geological Survey Famine Early Warning Systems Network.
To date, the software has been successfully implemented on multiple systems with multiple users to support two public health applications: malaria early warning in the Ethiopian highlands and West Nile virus risk forecasting in the northern Great Plains of the US. These successful prototypes have highlighted the tool’s broader potential for use in public health and other fields. Therefore, the overarching goal of this project is to improve software extensibility, customizability, documentation, and distribution to the point where it can be used more broadly within the public health community (RRL 8-9). To achieve this goal, we will (1) Extend the capabilities for processing multi-mission, multi-instrument earth science data by developing a plug-in framework for integrating existing and new data streams; (2) Enhance the user interface to facilitate customized data screening and processing into a format useful to the public health community and other end users; and (3) Expand documentation and develop a distribution strategy that will make the EASTWeb software more accessible to health scientists and other members of the scientific community.
This work will specifically address the needs of the public health research and applications user communities, although we expect that the resulting tool will also be useful in a wider range of fields. We will leverage the existing software that we have developed through our previous NIH-and NASA-funded research by adding enhancements that will better address the varied needs of the user community. This work will be accomplished through collaboration between an Earth system scientist with experience in public health application of remote sensing (Wimberly) and a computer scientist with experience developing applications for automated acquisition and processing of remotely-sensed Earth science datasets (Liu). The resulting tool will greatly expand end users ability to automatically access data from online archives in near real time and to effectively synthesize heterogeneous data from multiple sources to produce usable information that will support novel research and effective applications in the health sciences and related fields.
Last Updated: Oct 19, 2018 at 2:25 PM EDT