Local Search for Optimal Global Map Generation Using Mid-Decadal Landsat Images

AI Magazine

Lina Khatib³  Robert A. Morris²  John Gasch¹ 

[1] Landsat Mission Operations, Goddard Space Flight Center;NASA Ames Research Center;SGT Inc. / NASA Ames Research Center

关键词: scheduling;    Geo Cover;    optimization;    local search;    mixed initiativeLandSat;   

DOI  :  

学科分类：计算机科学（综合）

来源: Association for the Advancement of Artificial Intelligence

【 摘 要 】

NASA and the United States Geological Survey (USGS) are collaborating to produce a global map of the Earth using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) remote 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 using local search. The paper also describes the integration of a GMG solver into a graphical user interface for visualizing and comparing solutions, thus allowing for solutions to be generated with human participation and guidance.

【 授权许可】

Unknown