Found 63 datasets matching "spatially-dependent".
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The project team collected and analyzed 224 water samples and 101 matching rock samples. INL's improved method of measuring aqueous REEs allows study of samples previously thought too volume...
Search relevance: 91.85 | Views last month: 0 -
In this work, we propose a novel approach to perform Dependent Component Analysis (DCA). DCA can be thought as the separation of latent, dependent sources from their observed mixtures which is a...
Search relevance: 54.32 | Views last month: 0 -
This data set, ISLSCP II Snow-Free, Spatially Complete, 16 Day Albedo, 2002, contains 9 files for snow-free, spatially complete 16-day global black-sky albedos at local solar noon, white-sky...
Search relevance: 48.75 | Views last month: 0 -
We applied spatially-explicit models to a spatiotemporally robust dataset of greater sage-grouse (Centrocercus urophasianus) nest locations and fates across wildfire-altered sagebrush ecosystems...
Search relevance: 39.58 | Views last month: 0 -
We produced 13 hierarchically nested cluster levels that reflect the results from developing a hierarchical monitoring framework for greater sage-grouse across the western United States. Polygons...
Search relevance: 36.72 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.94 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.94 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.89 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.89 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.89 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.89 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.86 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.86 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.86 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.86 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.86 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.67 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.67 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.67 | Views last month: 0 -
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
Search relevance: 32.62 | Views last month: 0
