Jeffrey S. Evans mostly deals with Lidar, Remote sensing, Ecology, Random forest and Landscape ecology. His Lidar study integrates concerns from other disciplines, such as Linear regression, Basal area, Forest management, Canopy and Regression analysis. His work on Panchromatic film and Digital elevation model as part of general Remote sensing study is frequently connected to Ranging and Contextual image classification, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Ecology study combines topics in areas such as Sample and Scale. His Landscape ecology research is multidisciplinary, incorporating elements of Ecoinformatics, National park, Species richness, Impervious surface and Biological dispersal. His work carried out in the field of Habitat brings together such families of science as Tree canopy, Forest inventory, Forest ecology and Understory.
His scientific interests lie mostly in Ecology, Remote sensing, Habitat, Lidar and Environmental resource management. Jeffrey S. Evans has researched Remote sensing in several fields, including Canopy, Terrain and Statistic. His study in Habitat is interdisciplinary in nature, drawing from both Agroforestry and Wildlife.
His Lidar research integrates issues from Basal area, Forest management, Forest inventory, Tree canopy and Algorithm. His studies in Environmental resource management integrate themes in fields like Ecology and Land use. His research in the fields of Landscape epidemiology overlaps with other disciplines such as Process.
His primary areas of study are Agroforestry, Ecology, Habitat destruction, Habitat and Grouse. His research related to Prosopis, Overgrazing and Range might be considered part of Ecology. His biological study spans a wide range of topics, including Endangered species, Marxan, Resistance and Wildlife.
His Endangered species research incorporates elements of Protected area, Rangeland, Livelihood and Predation. His work deals with themes such as Ecosystem and Land management, which intersect with Habitat. His Grouse research is multidisciplinary, incorporating perspectives in Juniper, Woody plant and Tree canopy.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Putting the "landscape" in landscape genetics.
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Heredity (2007)
Empirical Analyses of Plant‐Climate Relationships for the Western United States
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International Journal of Plant Sciences (2006)
Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data
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Remote Sensing of Environment (2008)
Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics
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Ecology (2010)
A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments
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IEEE Transactions on Geoscience and Remote Sensing (2007)
Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA
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Remote Sensing of Environment (2009)
Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability
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Remote Sensing of Environment (2009)
Modeling species distribution and change using random forest [Chapter 8]
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In: Drew, A. C.; Wiersma, Y.; Huettmann, F., eds. Predictive Species and Habitat Modeling in Landscape Ecology. New York, NY: Springer. p.139-159. (2011)
Gradient modeling of conifer species using random forests
Jeffrey S. Evans;Samuel A. Cushman.
Landscape Ecology (2009)
Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral satellite data
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Canadian Journal of Remote Sensing (2006)
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