Post-classification Change Analysis
Post-Classification Change Analysis is a computational method that identifies and quantifies alterations in data instances or model predictions after an initial classification has been performed, distinguishing itself by focusing on temporal or conditional shifts in outcomes rather than on the primary classification task.
73
Publications
4.8K
Citations
229
Authors
108
Institutions
Publications per year
2017–2026
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John R. Jensen, Ken Rutchey, Magaly Koch et al. · Photogrammetric Engineering & Remote Sensing · 1995 · 271 citations
Natural Resources, Earth Sciences, Landscape Change Detection +16
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National Commission for the Knowledge and Use of Biodiversity, Mexico
2 publications · 53 citations
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1–5 of 229
108

Universitat Autònoma de Barcelona
Cerdanyola del Vallès, Spain
2 h-index
4 publications
568 citations
National Commission for the Knowledge and Use of Biodiversity
Tlalpan, Mexico
2 h-index
9 publications
267 citations

University of Twente
Enschede, The Netherlands
2 h-index
4 publications
379 citations

Mansoura University
Al Mansurah, Egypt
2 h-index
2 publications
120 citations
Isfahan University of Technology
Isfahan, Iran
2 h-index
100 publications
1.9K citations
National Authority for Remote Sensing and Space Sciences
Cairo, Egypt
2 h-index
3 publications
104 citations
Wuhan University
Wuhan, China
2 h-index
6 publications
1.3K citations
Tsinghua University
Beijing, China
2 h-index
13 publications
956 citations
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11 publications · 946 citations
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9 publications · 418 citations
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4 publications · 568 citations
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4 publications · 97 citations
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3 publications · 182 citations
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