I conducted two separate studies, both related to the impacts of spring and fall prescribed fire on ponderosa pine (Pinus ponderosa Dougl. ex Loud.) forest soils in Eastern Oregon. The studies were either conducted at or linked to four stands of ponderosa pine, in the Malheur National Forest. Each stand...
This chapter is divided into three main sections. The first section discusses land cover map development. It begins by providing background information on the regional division of labor and the regional land cover legend. It then focuses on our land cover mapping methods, including a description of data sources, the...
This data set contains RCode designed for mapping correlated vegetation summary variables via univariate (modified random forest regression) and multivariate (random forest nearest neighbor) methods. It also contains a small vegetation plot dataset to illustrate the type of information needed to support such an analysis.
AIM: Landscape management and conservation planning require maps of vegetation
composition and structure over large regions. Species distribution models
(SDMs) are often used for individual species, but projects mapping multiple species
are rarer. We compare maps of plant community composition assembled by
stacking results from many SDMs with multivariate maps...
AIM: Landscape management and conservation planning require maps of vegetation
composition and structure over large regions. Species distribution models
(SDMs) are often used for individual species, but projects mapping multiple species
are rarer. We compare maps of plant community composition assembled by
stacking results from many SDMs with multivariate maps...
Full Text:
plant communities:
stacked single species or multivariatemodelling
approaches?
EmilieB. Henderson
AIM: Landscape management and conservation planning require maps of vegetation
composition and structure over large regions. Species distribution models
(SDMs) are often used for individual species, but projects mapping multiple species
are rarer. We compare maps of plant community composition assembled by
stacking results from many SDMs with multivariate maps...
This study investigated how lidar-derived vegetation indices, disturbance history from Landsat time series (LTS)
imagery, plot location accuracy, and plot size influenced accuracy of statistical spatial models (nearest-neighbor
imputation maps) of forest vegetation composition and structure. Nearest-neighbor (NN) imputation maps were
developed for 539,000 ha in the central Oregon Cascades,...
Full Text:
, EmilieB. Henderson b,
Robert J. McGaughey c, Justin Braaten a
a Department of Forest Ecosystems and
This study investigated how lidar-derived vegetation indices, disturbance history from Landsat time series (LTS)
imagery, plot location accuracy, and plot size influenced accuracy of statistical spatial models (nearest-neighbor
imputation maps) of forest vegetation composition and structure. Nearest-neighbor (NN) imputation maps were
developed for 539,000 ha in the central Oregon Cascades,...
Full Text:
. Gregory, EmilieB.
Henderson, Robert J. McGaughey, Justin Braaten
Figure S1. Detailed plot layouts
This study investigated how lidar-derived vegetation indices, disturbance history from Landsat time series (LTS)
imagery, plot location accuracy, and plot size influenced accuracy of statistical spatial models (nearest-neighbor
imputation maps) of forest vegetation composition and structure. Nearest-neighbor (NN) imputation maps were
developed for 539,000 ha in the central Oregon Cascades,...
