Management of 264 million acres of public lands in the western United States is no easy task for the Department of Interior Bureau of Land Management (BLM). In fact, the responsibility for ensuring the sustainability of the economic, social, and natural resources of the lands has never been more challenging and complex. Increased and sometimes competing land uses, population growth, rapid expansion of noxious weeds, and increased frequency and extent of wildfires are just a few of the reasons why the BLM needs expedient and cost-efficient ways to obtain current information about the health and condition of the land. Land managers not only require monitoring information for large land areas but also need adequate resolution to detect the subtle changes in the condition of the land that may indicate the need to modify land management practices.

A technical experts team of ecologists, remote sensing, geographical information system specialists, and data analysis experts at the U.S. Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) is adapting remote-sensing techniques to address the problems of inventorying and monitoring rangelands. The team believes the best and most cost-effective approach for monitoring rangelands is through the combined use of remote-sensing imagery, ground-based data, and existing supporting data.

At PNNL, scientists are adapting a strategy that fuses remote sensing and supporting data using a hierarchical and stratified design. Data fusion is the process of combining information collected at various times, resolutions, and spatial extent to better characterize features that would not be as obvious in an individual data set. The hierarchical aspect of the strategy employs observations at an array of spatial and temporal resolutions, aerial coverage, and instrument sensitivity to determine the most effective combination of sensors.

Examples of supporting data sets include high-resolution Digital Elevation Models, climate data, and soils maps. The landscape is stratified into homogenous zones that can be further characterized with remotely sensed information. This stratification is expected to increase the ability to identify the most effective sensors and indices to characterize distinct zones in a landscape mosaic.

BLM’s mission is to sustain the health, diversity, and productivity of nearly one-eighth of the land in the United States for the use and enjoyment of present and future generations. Perhaps one of its greatest challenges is to develop more effective land-management practices while increasing management efficiency. Remote sensing and data fusion hold the promise for more timely and efficient monitoring to support effective land-management decisions.

For more information, contact Larry L. Cadwell at (509) 376-5659, larry.cadwell@pnl.gov.

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