spect to the N charac- Corresponding author address: Forrest M. Hoffman, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831--6036 USA; e-mail: forrest@climate.ornl.gov Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract number DE--AC05--00OR22725. Matter Organic 1 2 3 4 5 6 A B C D E G H C B E FG H 4 2 1 Temperature Organic Matter Rainfall Perform multivariate clustering. non-hierarchical statistical 1 3 4 2 Cluster Bins F2 H1 D6 E4 D5 C6 B7 A8 A6 F8 G8 G7 variables become axes of the data space. Map cell values become coordinates for the respective axis. Descriptive Group map cells with similar values for these descriptive ...
An aggregation approach is needed to overcome the prohibitive expense involved in exercising the Reg...
The authors present an application of multivariate non-hierarchical statistical clustering to geogra...
Abstract The authors present an application of multivariate non-hierarchical statistical cluster-ing...
A multivariate statistical clustering technique— based on the iterative k-means algorithm of Hartiga...
Hoffman and Hargrove previously used k-means clustering to detect brine scars from hyperspectral dat...
Hoffman and Hargrove previously used k-means clustering to detect brine scars from hyperspectral dat...
Climatologically homogeneous regions in the Carolinas were delineated using a multi-step approach in...
Clustering – the automated grouping of similar data – can provide powerful and unique insight into l...
<p>SPG South Pacific Gyre, HNLC High Nutrient Low Chlorophyll region, DCM Deep Chlorophyll Maximum; ...
This dataset contains the manual cloud classifications of the EUREC4A field campaign time period as ...
Climate is a tremendously complex topic, affecting many aspects of human activity and constantly cha...
The authors present an application of multivariate non-hierarchical statistical clustering to geogra...
Data and code associated with the article Spatial replication can best advance our understanding of ...
Classifying the land surface according to different climate zones is often a prerequisite for global...
Abstract Changing climate conditions will complicate efforts to match seed sources with the environm...
An aggregation approach is needed to overcome the prohibitive expense involved in exercising the Reg...
The authors present an application of multivariate non-hierarchical statistical clustering to geogra...
Abstract The authors present an application of multivariate non-hierarchical statistical cluster-ing...
A multivariate statistical clustering technique— based on the iterative k-means algorithm of Hartiga...
Hoffman and Hargrove previously used k-means clustering to detect brine scars from hyperspectral dat...
Hoffman and Hargrove previously used k-means clustering to detect brine scars from hyperspectral dat...
Climatologically homogeneous regions in the Carolinas were delineated using a multi-step approach in...
Clustering – the automated grouping of similar data – can provide powerful and unique insight into l...
<p>SPG South Pacific Gyre, HNLC High Nutrient Low Chlorophyll region, DCM Deep Chlorophyll Maximum; ...
This dataset contains the manual cloud classifications of the EUREC4A field campaign time period as ...
Climate is a tremendously complex topic, affecting many aspects of human activity and constantly cha...
The authors present an application of multivariate non-hierarchical statistical clustering to geogra...
Data and code associated with the article Spatial replication can best advance our understanding of ...
Classifying the land surface according to different climate zones is often a prerequisite for global...
Abstract Changing climate conditions will complicate efforts to match seed sources with the environm...
An aggregation approach is needed to overcome the prohibitive expense involved in exercising the Reg...
The authors present an application of multivariate non-hierarchical statistical clustering to geogra...
Abstract The authors present an application of multivariate non-hierarchical statistical cluster-ing...