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remote sensing

Displaying 31 - 40 of 52

Multitemporal LiDAR improves estimates of fire severity in forested landscapes

Year of Publication
2018
Publication Type

Landsat-based fire severity maps have limited ecological resolution, which can hinder assessments of change to specific resources. Therefore, we evaluated the use of pre- and post-fire LiDAR, and combined LiDAR with Landsat-based relative differenced Normalized Burn Ratio (RdNBR) estimates, to increase the accuracy and resolution of basal area mortality estimation.

A LiDAR-based analysis of the effects of slope, vegetation density, and ground surface roughness on travel rates for wildland firefighter escape route mapping

Year of Publication
2017
Publication Type

Escape routes are essential components of wildland firefighter safety, providing pre-defined pathways to a safety zone. Among the many factors that affect travel rates along an escape route, landscape conditions such as slope, low-lying vegetation density, and ground surface roughness are particularly influential, and can be measured using airborne light detection and ranging (LiDAR) data.

Landscape-scale quantification of fire-induced change in canopy cover following mountain pine beetle outbreak and timber harvest

Year of Publication
2017
Publication Type

Across the western United States, the three primary drivers of tree mortality and carbon balance are bark beetles, timber harvest, and wildfire. While these agents of forest change frequently overlap, uncertainty remains regarding their interactions and influence on specific subsequent fire effects such as change in canopy cover.

Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach

Year of Publication
2016
Publication Type

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements.