2004
DOI: 10.1007/s00267-003-1084-0
|View full text |Cite
|
Sign up to set email alerts
|

Potential of Multivariate Quantitative Methods for Delineation and Visualization of Ecoregions

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
202
0
1

Year Published

2010
2010
2017
2017

Publication Types

Select...
7
2

Relationship

1
8

Authors

Journals

citations
Cited by 251 publications
(203 citation statements)
references
References 64 publications
0
202
0
1
Order By: Relevance
“…The result is the ordination of the abiotic signatures according to the relative prevalence of each genospecies, weighted by the number of times each genospecies was reported in the target area. All of the procedures adhered to details published previously (11,19) and are available in File S3 in the supplemental material.…”
Section: Methodsmentioning
confidence: 99%
“…The result is the ordination of the abiotic signatures according to the relative prevalence of each genospecies, weighted by the number of times each genospecies was reported in the target area. All of the procedures adhered to details published previously (11,19) and are available in File S3 in the supplemental material.…”
Section: Methodsmentioning
confidence: 99%
“…Multivariate Spatio-Temporal Clustering (MSTC) (Hoffman & Hargrove, 1999;Hargrove & Hoffman, 2004;Hoffman et al, 2008;Kumar et al, 2011) and network representativeness analysis (Hargrove et al, 2003;Hoffman et al, 2013) Fifty ecoregions were delineated using MSTC (Kumar et al, 2011). The regions produced by this unsupervised classification method were then labeled with ecoregion or land cover type names derived from a suite of expert maps compared with the spatial clusters using the Mapcurves algorithm developed by Hargrove et al (2006).…”
Section: Multivariate Spatial Clustering Analysismentioning
confidence: 99%
“…This map follows the suggestion of Hargrove and Hoffman (2004) that the clustering of the three color mixing maps into map classes can improve the multivariate interpretation.…”
Section: Histogram Ranking and Visualization Techniquesmentioning
confidence: 99%
“…The second map is an RGB (red, green, blue) composition of the three univariate layers, relying on the theory of color mixing. Although the RGB approach is generally used in remote sensing visualizations, its use in other quantitative contexts still has few documented applications (Hargrove and Hoffman 2004;Craig et al 2006).…”
Section: Histogram Ranking and Visualization Techniquesmentioning
confidence: 99%