Local search for optimal global map generation using mid-decadal landsat images

Authors:
Robert A. Morris;John Gasch;Lina Khatib;Steven Covington
Affiliations:
Computational Sciences Division, NASA Ames Research Center;Landsat Mission Operations, Goddard Space Flight Center;PSGS and Computational Sciences Division, NASA Ames Research Center;Aerospace Corporation and Landsat Mission Operations, Goddard Space Flight Center
Venue:
IAAI'08 Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3
Year:
2008

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Abstract

NASA and the US Geological Survey (USGS) are generating image maps of the entire Earth using Landsat 5 Thematic Mapper (TM) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensor data from the period of 2004 through 2007. The map is comprised of thousands of scene locations and, for each location, there are tens of different images of varying quality to chose from. Constraints and preferences on map quality make it desirable to develop an automated solution to the map generation problem. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving It usmg local search. The paper also describes the integration of a GMG solver into a user interface for visualizing and comparing solutions.