Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Comp Stat

Clustering of multivariate geostatistical data

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Multivariate data indexed by spatial coordinates have become increasingly popular in many geoscientific fields. This type of data imposes new analysis challenges, including the clustering of irregularly sampled data locations into spatially contiguous clusters given a set of regionalized variables. Clusters of data locations created through general‐purpose clustering techniques turn out to show poor spatial contiguity, a characteristic obviously inconvenient for many geoscience applications. This article reviews clustering methods designed explicitly for multivariate geostatistical data in which spatial dependency plays an important role. These clustering techniques are modifications of general‐purpose clustering methods. They provide spatially contiguous clusters by accounting for the spatial dependency of data locations. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification Data: Types and Structure > Image and Spatial Data
Log‐transformed and standardized variables for clustering purpose
[ Normal View | Magnified View ]
Contribution of each variable in the formation of the two optimal spatial clusters: (a) spectral clustering based on a spatial similarity measure and (b) spectral clustering based on spatial contiguity constraints
[ Normal View | Magnified View ]
Number of spatial clusters versus Caliński–Harabasz index: (a) spectral clustering based on a spatial similarity measure and (b) spectral clustering based on spatial contiguity constraints
[ Normal View | Magnified View ]
(a and d) Classical spectral clustering; (b and e) spectral clustering based on a spatial similarity measure; (c and f) spectral clustering based on spatial contiguity constraints
[ Normal View | Magnified View ]

Browse by Topic

Data: Types and Structure > Image and Spatial Data
Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts