Automated Tools for Integrating Remote Sensing Data Into Spatial Epidemiology Research

Satellite remote sensing provides valuable information that can be used to map infectious diseases and forecast future health risks. However, amassing and managing the geographic information from diverse datasets is difficult and time-consuming. Therefore, there is a need for a geoinformatics system that integrates the acquisition, processing, management, and analysis of geospatial data sets from various sources.

Here, we present our software model for automated data capture and processing of satellite remote sensing data for public health applications.  The system incorporates land surface temperature and vegetation indices from MODIS precipitation data from TRMM, and a novel measurement of actual evapotranspiration.



The objectives of our system address the following challenges:
1) Capturing and processing satellite remote sensing data automatically.
2) Providing remotely sensed environmental data in a usable format to various public health professionals.
3) Building a computational framework that provides a foundation for future spatial epidemiology research. 

PostgreGIS , remote sensing