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Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition
Abstract
Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. As a result, the much-anticipated new edition is significantly expanded and enhanced to reflect growth in the field. The new edition features three new chapters, including: Fuzzy accuracy assessmentPositional accu
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Cited by
Morphological Attribute Profiles for the Analysis of Very High Resolution Images
Dalla Mura, M., Benediktsson, J. A., Waske, B., & Bruzzone, L. (2010) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2010.2048116 · Cited by 722
Semantic segmentation of urban scenes by learning local class interactions
Volpi, M., & Ferrari, V. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2015.7301377 · Cited by 152
Managed wildfire effects on forest resilience and water in the Sierra Nevada
Boisramé, G., Thompson, S., Collins, B., & Stephens, S. (2017) · Ecosystems · doi:10.1007/s10021-016-0048-1 · Cited by 128
Ibrahim Mahmoud, M., Duker, A., Conrad, C., Thiel, M., & Shaba Ahmad, H. (2016) · Remote Sensing · doi:10.3390/rs8030220 · Cited by 105
Uncertainty Assessment of Hyperspectral Image Classification: Deep Learning vs. Random Forest
Shadman Roodposhti, M., Aryal, J., Lucieer, A., & Bryan, B. A. (2019) · Entropy · doi:10.3390/e21010078 · Cited by 65
Metadata
- Authors
- Congalton, R. G., & Green, K.
- Venue
- CRC Press eBooks
- Publisher
- CRC Press
- Published
- 2008-12-12
- OpenAlex
- W4245539475
- Cited by
- 1,270
- References
- 0
- FWCI
- 20.89
- Type
- book
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
