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Web-based Visualization and Analysis of NASA Ecological Data

The Terrestrial Observation and Prediction System (TOPS) at NASA Ames Research Center’s Ecological Forecasting Lab generates a suite of gridded data products in near real-time that are designed to enhance management decisions related to droughts, forest fires, human health, as well as crop, range, and forest production. Our data products hold great potential for supporting research and real-world applications. In order to provide enhanced access to our data and to promote multidisciplinary collaboration we implement web-based tools for visualization and analysis.

Rich Analysis – Web-based tools not only provide an accessible platform for presenting our data, but also enable rich analysis of trends and anomalies in ecological conditions. The client-server model allows data to remain on our servers while the researcher performs analysis and requests in-situ data processing, all from within a web browser.

Temporal information – As NASA satellites are constantly scanning the earth’s surface, our growing archive of geospatial data produces a valuable temporal record of ecological conditions. The resulting time-series data allows researchers to better understand earth system dynamics and monitor for significant anomalous events or conditions.

Crisis Mapping – Spatio-temporal analysis tools allow us to identify current (or past) anomalies in geophysical conditions, providing early warning and monitoring capabilities for phenomena related to climate change, wild fires, pest infestations, etc. By leveraging geospatial web technology we are able to present valuable information to managers in charge of mitigating the negative impacts of such phenomena.

Open Source – Our system is built on an open source software stack. This provides us flexibility in design and implementation, and frees us from proprietary licensing restrictions. We will discuss the software that have enabled us to reach our objective of extending the use of our data to a wider audience, illustrating how the latest in FOSS for Geospatial provide a solution for each component of our software system.

This presentation is intended for those interested in seeing how data from Earth observing satellites and weather station networks are being put to use in order to solve real-world problems. The audience need not be familiar with remote sensing nor software development, however programmers and scientists alike will benefit from seeing this fusion of science and technology for practical applications.

We will demonstrate our web-based tools for visualization and analysis, discussing the motivations and benefits of our monitoring efforts as well as illustrating the value of providing web-based access to such information.

Photo of Sam Hiatt

Sam Hiatt

NASA Ecological Forecasting Lab

Sam Hiatt graduated from Utah State University in 2007 with a BS in Geography and minors in Geographical Information Science, Computer Science, and Mathematics. While at USU he worked with Dr. Michael White to develop a new method for monitoring plant phenology using MODIS Direct Broadcast satellite imagery. He currently works with Dr. Rama Nemani at NASA Ames Research Center’s Ecological Forecasting Lab leveraging open source software to enhance data access and usability.

Sam is very interested in open source and collaborative geospatial technology as well as a variety of topics related to satellite remote-sensing and ecology. He participated in the Free and Open Source Software for Geospatial conference in Victoria, Canada in 2007, and as a member of the American Geophysical Union he participates annually in the AGU Fall Meetings in San Fancisco, CA.

Andrew Michaelis

NASA Ecological Forecasting Lab

Andrew is a software engineer at the NASA Ecological Forecasting Lab. He mainly works in the earth science domain supporting scientists on numerous projects. He is also owner/manager of a small LLC that is registered in the state of California as well as a NASA ‘certified’ systems administrator.