Paper
7 October 2009 KH-series satellite imagery and Landsat MSS data fusion in support of assessing urban land use growth
Daniel Civco, Anna Chabaeva, Jason Parent
Author Affiliations +
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel Civco, Anna Chabaeva, and Jason Parent "KH-series satellite imagery and Landsat MSS data fusion in support of assessing urban land use growth", Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 74780I (7 October 2009); https://doi.org/10.1117/12.830943
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Cited by 4 scholarly publications.
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KEYWORDS
Earth observing sensors

Landsat

Image fusion

Data fusion

Satellites

Data modeling

Image classification

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