Abstract
The Customized Online Aggregation & Summarization Tool for Environmental Rasters (COASTER) system (www.COASTERdata.net) was developed by Yellowstone Ecological Research Center (YERC) (www.yellowstoneresearch.org) in response to the information needs of end-user communities interested in decision-support for natural resource management. The purpose of COASTER is to greatly simplify the process of creating predictor datasets for research exploring environmental impacts driven by climate change, land-use activities, disturbance, and invasive spread. COASTER achieves this goal by providing users with a web-based system for processing environmental (gridded, raster) datasets, using a set of standardized functions, to create output customized to meet their analytical needs. In doing so, COASTER effectively translates large and cumbersome datasets into user-specified information useful for parameterizing statistical models and for visualizing spatial and temporal patterns within environmental datasets. The COASTER system currently contains over 10 terabytes of climate data from several sources. These datasets have daily temporal resolutions, spatial resolutions ranging from 1km to 330km, and temporal extents ranging from 30 to 64 years (1948-2011). COASTER datasets are primarily limited to North America, but gridded datasets from other regions can easily be added to the system. Variables within the climatic datasets available on COASTER include metrics quantifying temperature, precipitation, shortwave radiation, vapor pressure deficit, humidity, and wind conditions. Notable features of COASTER include a conceptually simple yet flexible set of functions capable of producing a wide range of outputs, a design applicable to many types of raster datasets, and results formatted for seamless integration within most GIS and remote sensing software packages.
Highlights
Environmental variables that characterize changing habitat conditions over time are highly valuable for assessing species vital rates and community and ecosystem health, and for supporting informed resource management decisions
The Customized Online Aggregation & Summarization Tool for Environmental Rasters (COASTER) system is designed to reduce or eliminate these challenges by providing: 1) access to highly soughtafter datasets, starting with interpolated climate datasets that have daily temporal resolutions; 2) a set of tools that reduce the computation and data storage capabilities required of users by processing the data on a remote server; and 3) delivering customized products that are readily integrated, explored, and analyzed within a GIS or remote sensing software environment
To simplify the process of updating datasets on COASTER, we have developed a collection of tools and procedures for rapidly integrating new data, including approaches for 1) preprocessing; 2) producing new projection translation functions; 3) modifying the details stored in the dataset SQL database to reflect the new temporal extent of the updated dataset; and 4) modifying the COASTER interface to reflect the presence of the expanded years available
Summary
Environmental variables that characterize changing habitat conditions over time are highly valuable for assessing species vital rates and community and ecosystem health, and for supporting informed resource management decisions. Variables of particular interest for such tasks include raster datasets (i.e., gridded, wall-to-wall geospatial datasets) that capture climatic conditions, vegetation phenology and/or productivity, and moisture/ water information with temporal and spatial resolutions sufficient for analyzing the phenomena of interest Utilizing such variables is challenging, for reasons including: 1) the high cost and level of technological expertise required to produce the underlying datasets; 2) the data management capabilities necessary to acquire and store existing datasets; and 3) the computational infrastructure, software packages, and computer programming skills necessary to extract and synthesize useful information from large datasets. Notable projects that produce and/or distribute data at comparable or finer resolutions include DAYMET (daymet.ornl.gov), PRISM (www.prism.oregonstate.edu) [4], Climate Western North America (www.genetics.forestry.ubc.ca/cfcg/ClimateWNA/Climat eWNA.html) [8,9], the Climate Research Unit (CRU) (www.cru.uea.ac.uk/) [10], WorldClim (www.worldclim.org/) [11], CliMond (www.climond.org) [12], and Arctic RIMS (rims.unh.edu) These projects are differentiated by the datasets they contain, the underlying models used to create the data, and the data distribution methods they employ. Users can make matching products from different datasets and examine the results, in combination with the accompanying metadata, to determine which dataset is best suited to meet their needs
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