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Classifying Urban Land Covers Using Local Indices of Spatial ComplexityThe skewed statistical distributions of land cover types in complex, heterogeneous urban areas limits the effectiveness of traditional spectrally based maximum-likelihood classifiers. This work examines the utility of fractal dimension and Moran's I index of spatial autocorrelation in segmenting high-resolution panchromatic and lower-resolution multispectral imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze multi-temporal and multi-platform imagery of Atlanta, Georgia. In this example, land cover change trajectories from forest or grassland to built up land covers lead to decreased spatial autocorrelation. In lower resolution imagery such as Landsat MSS, the complex details of forested land covers and urbanized areas are smoothed, and texture-based change detection is less effective. Although segmentation of panchromatic images is possible using fractal dimension or Moran's I, widely differing land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification.
Document ID
20030062098
Acquisition Source
Marshall Space Flight Center
Document Type
Conference Paper
Authors
Arumugam, Mahesh
(University of Western Michigan Kalamazoo, MI, United States)
Emerson, Charles W.
(University of Western Michigan Kalamazoo, MI, United States)
Lam, Nina Siu-Ngan
(Louisiana State Univ. Baton Rouge, LA, United States)
Quattrochi, Dale A.
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Date Acquired
August 21, 2013
Publication Date
January 1, 2003
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Proceedings of the American Society for Photogrammetry and Remote Sensing
Location: Anchorage, AK
Country: United States
Start Date: May 5, 2003
End Date: May 7, 2003
Sponsors: American Society for Photogrammetry and Remote Sensing
Distribution Limits
Public
Copyright
Other

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