PS 12-95
Big data for ecologists: Highlighting the ORNL DAAC

Monday, August 11, 2014
Exhibit Hall, Sacramento Convention Center
Alison G. Boyer, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Robert Cook, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Ranjeet Devarakonda, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Pete I. Eby, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Michele M. Thornton, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Peter E. Thornton, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Suresh K.S. Vannan, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Makhan Virdi, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Yaxing Wei, Environmental Sciences Division & Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Background/Question/Methods

Ecologists are increasingly confronted by questions that can be addressed only by integrating data from numerous sources, often across large geographic areas and broad time periods. The supply of ecological “big data” is increasing at a rapid pace as researchers are publishing their data sets and large, public science and data infrastructures (such as NEON, DataONE, LTER, & NCEAS) are producing and curating extensive volumes of complex data and metadata. While supply of, and demand for, ecological data is on the rise, many ecologists now face a new challenge in locating and synthesizing the data relevant for their particular question. Here we highlight selected popular big data products applicable to ecological research available from the NASA Distributed Active Archive Center (DAAC) located at Oak Ridge National Laboratory (ORNL).

Results/Conclusions

Recently-released data products and services at the ORNL DAAC include Daymet and subsetting tools for MODIS land data products. Daymet products are daily gridded surface weather variables, including temperature, precipitation, snow water equivalent, humidity, and radiation, at a 1-km x 1-km spatial resolution for North America for 1980 - 2012. With over 10,000 individual data requests since its release, the Daymet dataset has proven to be a useful resource for ecologists, the climate change research community, and has found many other applications as well. MODIS (or Moderate Resolution Imaging Spectroradiometer) is a satellite-based instrument that produces images of the entire Earth's surface every 1 to 2 days from 2000 to the present, acquiring data in 36 spectral bands. MODIS land data products, which are highly useful for terrestrial ecology research, include: land cover, albedo, leaf area index, NDVI, evapotranspiration, gross primary production, net primary production & surface reflectance. The ORNL DAAC provides online tools to select spatial and temporal subsets of both Daymet and MODIS data for any site, area (from 1 pixel up to 201 x 201 km) and time period. In addition, the DAAC provides pre-processed MODIS data for more than 1,000 field sites and flux towers around the world, interactive data visualizations (time series plots and summary data for user-selected sites and time periods), and teaching exercises for the classroom. ORNL DAAC data and tools are an important resource for the ecological community and aim to help ecologists discover, access, understand, and use data to facilitate their science.  Related Links: http://daymet.ornl.gov | http://daac.ornl.gov/MODIS