Rangeland Management Support
One of BLM’s primary responsibilities is to effectively manage approximately 160 million acres of rangelands for multiple uses including grazing, energy development, recreation, and conservation. Geospatial technologies (i.e. remote sensing, GIS, and photogrammetry) provide tools for the inventory, assessment, monitoring, and modeling of these extensive lands. Whether it is monitoring changes in sage-grouse habitat over time, calculating Animal Unit Months, determining grazing schedules, or used as a stratification tool to assist with land health assessments; geospatial technologies can assist with many common range management tasks.
| The needs and questions being asked by land manager go a long way in determining what data and processes should be employed. Below are a few examples to selecting the appropriate data resolution certain tasks may require. Though the discussion below focuses on remote sensing systems, all the geospatial technologies are needed in an integrated framework to support rangeland management needs. |  |
The Resource Technology Branch is here to assist BLM field managers with selecting the appropriate technologies for their management needs. From project scoping through implementation and technology transfer, we can assist in all stages of the project lifecycle
Coarse Resolution (100 – 1000 meters) Example Sensors: MODIS/AVHRR
Coarse resolution systems are designed to support national and broad regional scale analyses. Vegetation response to drought, monitoring greenness over season, identification of land areas underperforming that may need special attention are examples of research currently being conducted that can assist land managers in their work. The greatest advantage of these coarse resolution sensors is what they lack in spatial resolution they make up for in very high temporal resolution with revisit times on a daily basis. Data from these sensors are usually free or nearly so.
Moderate Resolution (10 – 60 meter) Example Sensors: Landsat, SPOT
Moderate resolution systems are designed to support more regional to local scale studies. This category of data is dominated by Landsat level land cover mapping. There are several national vegetation products available based on Landsat data that rangeland scientist can use for their work. These include the National Land Cover Database, LANDFIRE, Regional GAP, Shrubmap, and more. These moderate resolution datasets can be used to map sage-grouse habitats, estimate fire condition classes, estimate forage productivity, and more.
High Resolution (1 – 10 meters) Ex. IKONOS, QuickBird, NAIP, LIDAR
Commercial satellites and national orthophotography programs (e.g., NAIP) are the main providers of this type of data and are ideally suited for more local scale studies. Many studies have shown the utility of high resolution imagery as the base data to map invasive species, calculate biophysical characteristics of sagebrush (i.e., height, cover density), and monitoring treatment progress. Through photogrammetric processes detailed digital terrain and surface models can be generated that allow for detailed hydrological analyses.
Very High Resolution (< 1 meter)
New technologies and processes such as close range photogrammetry, unmanned airborne vehicles (UAV), advanced software/hardware, and smaller cheaper imaging systems are opening up a new world in remote sensing. On-going studies in Idaho and through the USDA Agricultural Research Service are exploring the use of very high resolution imagery as a means of supplement land health assessments. The extremely detailed imagery that these systems generate enables scientists to produce very accurate terrain models and explore individual plant communities like never before. Past studies have shown that many of the individual land health indicators can be captured though these means. The resulting imagery additionally provides a foundation for long-term monitoring of the plots to look at not only changes in ground cover, but quantifying soil loss due to erosion by comparing terrain models over the years.
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