Urban land cover mapping with TerraSAR-X using an edge-aware region-growing and merging algorithm
2014 (English)In: 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE , 2014, 4836-4839 p.Conference paper (Refereed)
TerraSAR X data has been analyzed for its suitability of urban land cover mapping using our recently developed object based image analysis tool KTH-SEG, which is based on an edge aware region growing and merging algorithm and a support vector machine classifier. Classification results over the Shanghai International Airport area using 8 classes, Water, Grass, Roads, Buildings, Crops, Forest, Bare Crops and Green Houses have proven with an overall accuracy just shy of 84% that this is very well the case. It has further been investigated which segment sizes and image configuration yield the best results.
Place, publisher, year, edition, pages
IEEE , 2014. 4836-4839 p.
, IEEE International Symposium on Geoscience and Remote Sensing IGARSS, ISSN 2153-6996
OBIA, SAR, Urban, Land Cover Mapping, Image Classification
Other Computer and Information Science
Research subject Geodesy and Geoinformatics
IdentifiersURN: urn:nbn:se:kth:diva-147141DOI: 10.1109/IGARSS.2014.6947577ISI: 000349688106174ScopusID: 2-s2.0-84911454836ISBN: 978-1-4799-5775-0OAI: oai:DiVA.org:kth-147141DiVA: diva2:727737
Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014, Quebec Convention Centre Quebec City, Canada, 13 July 2014 through 18 July 2014
QC 201406252014-06-232014-06-232015-04-08Bibliographically approved