Journal
EUROPEAN JOURNAL OF REMOTE SENSING
Volume 47, Issue -, Pages 389-411Publisher
TAYLOR & FRANCIS LTD
DOI: 10.5721/EuJRS20144723
Keywords
Remote sensing image classification; Spatio-contextual information; Geographic information analysis techniques; Land use land cover classification
Categories
Funding
- National Natural Science Foundation of China [41030743, 41171322, 41171412]
- University of Wisconsin-Milwaukee Graduate School, as well as Open Research Fund of Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences
Ask authors/readers for more resources
This paper reviewed major remote sensing image classification techniques, including pixel-wise, sub-pixel-wise, and object-based image classification methods, and highlighted the importance of incorporating spatio-contextual information in remote sensing image classification. Further, this paper grouped spatio-contextual analysis techniques into three major categories, including 1) texture extraction, 2) Markov random fields ( MRFs) modeling, and 3) image segmentation and object-based image analysis. Finally, this paper argued the necessity of developing geographic information analysis models for spatial-contextual classifications using two case studies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available