Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/4843
Title: Automated cartographic feature attribution using panchromatic and hyperspectral imagery : DARPA/APGD yearly report 1998-1999
Authors: Carnegie-Mellon University. School of Computer Science.
United States. Defense Advanced Research Projects Agency.
McKeown, David M.
McGlone, J. Chris
Cochran, Stephen Douglas.
Shufelt, Jeffery A.
Wilson, Harvey A.
Yocum, Daniel A.
Keywords: Block adjustment
Linear pushbroom
Geometric constraints
HYDICE/hyperspectral imagery, surface material classification,
Cartographic feature extraction
Data fusion
Issue Date: Jun-2000
Publisher: U.S. Army Topographic Engineering Center.
Engineer Research and Development Center (U.S.)
Series/Report no.: ERDC/TEC CR ; 00-3.
Description: Contract report
Abstract: This report summarizes the primary accomplishments made during the second year of the DARPA Automated Population of Geographic Databases (APGD) program. The first part summarizes work in acquiring and registering the Hyperspectral Digital Imagery Collection Experiment (HYDICE) data. It also describes experiments in classifying the HYDICE data using standard maximum-likelihood techniques, and explores the development and results of the new spectral angle mapper. The second part covers work begun on aggregating the surface material maps to reduce the number of polygons required without degrading classification accuracy.
URI: http://hdl.handle.net/11681/4843
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