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    Spatially explicit maps of wildlife habitat relationships have proven to be valuable tools for conservation and management applications including evaluating how and which species may be impacted by large scale climate change, ongoing fragmentation of habitat, and local land-use practices. Studies have turned to remote sensing datasets as a way to characterize vegetation for the examination of habitat selection and for mapping realized relationships across the landscape. Potentially one of the more difficult habitat types to try to characterize with remote sensing are the vertically and horizontally complex forest systems. Characterizing this complexity is needed to explore which aspects may represent driving and/or limiting factors for wildlife species. Active remote sensing data from lidar and radar sensors has thus caught the attention of the forest wildlife research and management community in its potential to represent three dimensional habitat features. The purpose of this review was to examine the applications of active remote sensing for characterizing forest in wildlife habitat studies through a keyword search within Web of Science. We present commonly used active remote sensing metrics and methods, discuss recent advances in characterizing aspects of forest habitat, and provide suggestions for future research in the area of new remote sensing data/techniques that could benefit forest wildlife studies that are currently not represented or may be underutilized within the wildlife literature. We also highlight the potential value in data fusion of active and passive sensor data for representing multiple dimensions and scales of forest habitat. While the use of remote sensing has increased in recent years within wildlife habitat studies, continued communication between the remote sensing, forest management, and wildlife communities is vital to ensure appropriate data sources and methods are understood and utilized, and so that creators of mapping products may better realize the needs of secondary users.

    Publication Notes

    • Visit PNW's Publication Request Page to request a hard copy of this publication.
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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Vogeler, Jody C.; Cohen, Warren B. 2016.  A review of the role of active remote sensing and data fusion for characterizing forest in wildlife habitat models. Revista de Teledetección. (45): 1-14.


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    Wildlife habitat, forest, LIDAR, radar, predictive maps, synthetic-aperture radar, airborne LIDAR, vegetation structure, species-diversity, squirrel habitat, nesting habitat, scale, bird, biomass, conservation.

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