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Proceedings Paper

KH-series satellite imagery and Landsat MSS data fusion in support of assessing urban land use growth
Author(s): Daniel Civco; Anna Chabaeva; Jason Parent
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Paper Abstract

Multi-temporal land use data, circa 1990 and 2000, have been analyzed an our urban growth model which identifies three levels of the urban extent - the impervious surface, the urbanized area, and the urban footprint - to account for the differing degrees of open space degradation associated with the city. The model also generates metrics such as cohesion, proximity, population densities, average openness, open space contiguity, and depth which quantify spatial characteristics that are indicative of urban sprawl. We plan on expanding this time-series further, and for additional cities, with mid-decadal, gap-filled Landsat ETM data, as well as resolution-enhanced Landsat MSS data from the 19070's. The cities used in this pilot project consisted of: (a) Kigali, Rwanda; (b) Portland, Oregon; (c) Tacoma, Washington; and (d) Plock, Poland. Based on research done in this project, complemented by results from other efforts, the Ehlers data fusion approach was used in the resolution enhancement of Landsat MSS imagery. In this paper, using Portland and Kigali as the principal examples, we discuss the procedures by which (a) the KH-series declassified military intelligence imagery was geometrically-corrected and registered to Landsat data, (b) the Ehlers Fusion of the KH-data with Landsat MSS, (c) the derivation of 1970's urban land use information, and (d) the calculation of select urban growth metrics. This paper illustrates the power of leveraging the high resolution of the military reconnaissance imagery with the multispectral information contained in the vintage Landsat MSS data in historical land use analyses.

Paper Details

Date Published: 7 October 2009
PDF: 12 pages
Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 74780I (7 October 2009); doi: 10.1117/12.830943
Show Author Affiliations
Daniel Civco, Univ. of Connecticut (United States)
Anna Chabaeva, Univ. of Connecticut (United States)
Jason Parent, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 7478:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX
Ulrich Michel; Daniel L. Civco, Editor(s)

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