Employing Spatial Metrics in Urban Land-Use / Land-Cover Mapping: Comparing the Getis and Geary Indices

Authors

Soe W. Myint, Arizona State University - Tempe Campus
Elizabeth A. Wentz, Arizona State University - Tempe Campus
Samuel J. Purkis, Nova Southeastern UniversityFollow

ResearcherID

B-8552-2013

Document Type

Article

Publication Title

Photogrammetric Engineering & Remote Sensing

ISSN

0099-1112

Publication Date

12-2007

Abstract

We examine the potential of supplementing per-pixel classifiers with the Getis index (Gi) in comparison to the Geary’s C on a subset of Ikonos imagery for urban land-use and land-cover classification. The test is pertinent considering that the Gi is generally considered more capable of identifying clusters of points with similar attributes. We quantify the impact of varying distance thresholds on the classification product and demonstrate how well the Gi identified cold and hot spots in comparison to Geary’s C. The exercise also provides a rule of thumb for effectively measuring spatial association in connection to adjacency. We are able to support existing literature that measuring local variability improves classification over spectral information alone. The results, however, neither confirm nor deny the challenge on whether measuring cold and hot spots rather than just spatial association improves classification accuracy.

Volume

73

Issue

12

First Page

1403

Last Page

1415

Comments

©2007 American Society for Photogrammetry and Remote Sensing

Additional Comments

NSF grant #: 0351899

NSUWorks Citation

Soe W. Myint, Elizabeth A. Wentz, and Samuel J. Purkis. 2007. Employing Spatial Metrics in Urban Land-Use / Land-Cover Mapping: Comparing the Getis and Geary Indices .Photogrammetric Engineering & Remote Sensing , (12) : 1403 -1415. https://nsuworks.nova.edu/occ_facarticles/240.