Assessment Inventory and Monitoring (AIM) methods are used to monitor landscape condition and trends across many BLM-managed lands. However, the derived fractional cover estimates, which are used to equate field-based AIM measurements with broad-resolution remotely sensed imagery (e.g. Landsat), only tell a fraction of the ecological story. To supplement and extend information extracted with AIM methods, BLM crews are flying Unmanned Aerial System (UAS) missions to collect very high resolution imagery capable of discriminating individual plants identified during field data collection.
The Cascades Field Office in the Salem District BLM in Oregon has embraced the the power of light detection and ranging (lidar) data for creating 3D visualizations of timber, recreation, and other projects. By creating a point feature class in Esri ArcGIS with height attributes derived from lidar, BLM personnel are able to model individual trees in a project area to create a realistic perspective of the ground-level scenario. These visualizations provide information about and a view of the landscape akin to a field visit, making them useful for conceptualizing project plans for internal t
The national-scale BLM Forest Vegetation Information System (FORVIS) provides data about forest attributes and associated land management activities to inform vegetation inventory and monitoring efforts. Remote sensing technology contributes to this program, facilitating a more efficient and complete inventory of vegetative resources, including non-forested land cover types such as shrublands and grasslands. This multi-year BLM project will give the State of Utah comprehensive coverage of all vegetative data, making the inventory useful for a wide range of resource applications.
Native woody juniper shrubs (Juniperus spp.) are expanding beyond their normal historical ranges as a result of wildfire suppression, prolonged drought, and reduced demand for juniper products such as fencing and building material.
The BLM uses an array of remote sensing technologies to support resource management. The BLM National Operations Center (NOC) is currently employing Unmanned Aerial Systems (UAS) and spaceborne high-resolution imaging systems to assist the Royal Gorge Field Office (RGFO) with mine production verification. For several RGFO mines, the BLM has developed preliminary fine-scale (~1-m) digital surface model elevation products derived from WorldView-2 and WorldView-3 stereo imagery acquired in late 2015 and 2016 that document elevation changes due to ore extration and tailings accumulation.
During analysis of potential impacts to cultural resources as a result of extraction activities at the Meeteetse Draw Bentonite Mine in Wyoming’s Big Horn Basin, concerns of indirect impacts to prehistoric rock art sites from dust abrasion and vibration resulted in the formulation of an annual monitoring plan for seven sites. BLM staff acquired digital stereo imagery of one panel at each site beginning in 2008; regular annual acquisitions began in 2013 after active mining operations began. Stereo images were processed into 3D point clouds using PhotoScan 1.1.6 (A
The National Operations Center (NOC) provides remotely sensed geospatial data products to support fire management officials conducting Emergency Stabilization and Rehabilitation (ESR) activities on wildfire-affected BLM lands. The ESR program is implemented to lessen post-fire effects such as erosion and to restore affected habitats. Remote sensing products assist management officials in completing key objectives, including monitoring vegetation treatments and reforestation, and rehabilitating land cover.
The BLM has increasingly used an emergent computing platform known as Google Earth Engine (GEE) to harness remote sensing data for resource management. GEE provides a development environment that combines over 2 petabytes of imagery and other scientific datasets with a suite of spatial and aspatial analysis tools. GEE offers a cloud computing architecture for accessing, processing, analyzing, and generating products from satellite imagery and other geospatial data without taxing local computer resources with intensive processing.
The BLM National Operations Center (NOC) is using multi-date aerial photography and remotely sensed imagery to delineate recent and historical river channel extents and gradients of the Red River (Texas/Oklahoma) as a continuation of support of the BLM New Mexico State Office (NMSO).