CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12158 > Article
Paper
2 March 2022 Research on land use classification with high resolution remote sensing images based on optimal segmentation
Gangfeng Yang, Xiangbing Kong, Yaping Wang, Fuling Wang, Yinan Wang, Jintao Zhao
Author Affiliations +
Proceedings Volume 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021); 1215804 (2022) https://doi.org/10.1117/12.2627370
Event: 2021 International Conference on Computer Vision and Pattern Analysis, 2021, Guangzhou, China
Abstract
Image segmentation is an important step of the object-oriented information extraction method, which is directly related to the accuracy of information extraction with high resolution remote sensing images. This paper mainly researched on the optimal segmentation scales about nine types of ground features in different layers with RMAS indicators, such as cultivated land, woodland, grassland, and so on, which were used to extract land use information. At the same time, the global optimal segmentation scale constructed with RMNE indicators was used to extract land use information, which was based on the five methods, such as Bayes, Nearest neighbor, Decision tree, Random Forest, and SVM under a single scale layer. The classification results of the two methods were compared and analyzed. The research results show that the multiscale optimal segmentation method adopted in this paper could effectively solve the problems of object confusion and ground object fragmentation in the classification results under a single scale layer, and the classification accuracy is better.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Gangfeng Yang, Xiangbing Kong, Yaping Wang, Fuling Wang, Yinan Wang, and Jintao Zhao "Research on land use classification with high resolution remote sensing images based on optimal segmentation", Proc. SPIE 12158, International Conference on Computer Vision and Pattern Analysis (ICCPA 2021), 1215804 (2 March 2022); https://doi.org/10.1117/12.2627370
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 7 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation
Image classification
Remote sensing
Image resolution
Feature extraction
Image processing algorithms and systems
L band
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top