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Im, Jungho
Intelligent Remote sensing and geospatial Information Science (IRIS) Lab
Research Interests
  • Remote sensing, Geospatial modeling, Disaster monitoring and management, Climate change

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An automated binary change detection model using a calibration approach

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Title
An automated binary change detection model using a calibration approach
Author
Im, JunghoRhee, JinyoungJensen, John R.Hodgson, Michael E.
Keywords
Automated calibration; Binary change detection; Multiple variables; QuckBird imagery
Issue Date
2007-01
Publisher
ELSEVIER SCIENCE INC
Citation
REMOTE SENSING OF ENVIRONMENT, v.106, no.1, pp.89 - 105
Abstract
An automated binary change detection model using a threshold-based calibration approach was introduced in the study. The burdensome processes required in binary change detection, including calibration, calculation of accuracy, extraction of optimum threshold(s), generation of a binary change mask, and removal of "salt-and-pepper" noise were integrated and automated in the model. For practical purpose, the model was implemented as a dynamic linked library in ESRI ArcMap 9.1 using Visual Basic. This study demonstrated the model with a variety of single and multiple variables (layers) extracted from multiple-date QuickBird imagery for three study sites in Las Vegas, NV and two study sites in Tucson, AZ. The use of multiple variables in binary change detection resulted in significantly better performance than single variables.
URI
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DOI
10.1016/j.rse.2006.07.019
ISSN
0034-4257
Appears in Collections:
UEE_Journal Papers
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