Lidar (terrestrial or bathymetric)

Tracking Spatial and Temporal Habitat Changes for an Endangered Rodent

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The New Mexico meadow jumping mouse (Zapus hudsonius luteus), which was listed as endangered in 2014, historically ranged throughout the Middle Rio Grande River Valley in New Mexico and along perennial high-elevation streams in New Mexico, southern Colorado, and eastern Arizona. After years of drought, river modifications, and changes to habitat, many previously occupied jumping mouse populations are believed to be extirpated.

Convolutional Neural Networks for Detecting Abandoned Oil and Gas Wells

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Abandoned gas and oil wells are commonly a source of greenhouse gas (GHG) emissions and can leak hydrocarbon-related fluids such as oil or brine, particularly when unplugged wells go undetected over long periods. Older wells are challenging to discover when vegetation has overgrown abandoned sites. As in other parts of the country, FWS National Wildlife Refuges (NWR) in Oklahoma and Texas contain a large number of abandoned wells from historical oil and gas development.

Modeling Sea Level Rise Impacts to Wildlife Habitat

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Sea level rise inundation on important Department of Interior (DOI) conservation lands was estimated using U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) high-resolution light detection and ranging (lidar) data coupled with National Oceanic and Atmospheric Administration (NOAA) models. Projections for DOI lands were made from all the Global Sea Level Rise models and time steps from 2000 to 2100 to assist in climate resiliency planning. 

Mapping Endangered Species Potential Habitat

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Nearly 1 million Attwater’s greater prairie-chickens (Tympanuchus cupido attwateri) once occupied 6 million acres of coastal prairie grasslands in Texas and Louisiana. Loss and fragmentation of habitat nearly drove this species to extinction, and it was listed as endangered in 1967. Today, two populations have been established in the wild through release of captive-reared birds.

Fusion of Spaceborne Lidar and Optical Data for Complete Vegetation Maps

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Vegetation structure is a key attribute of forested ecosystems, influencing habitat suitability, water quality and runoff, microclimate, and wildfire behavior. The Fire-Science Team at the USGS EROS Center is fusing spaceborne lidar and passive optical data to create spatially complete maps of vegetation structure at 30-meter resolution.