Title :
Urban ecological land extraction from Chinese Gaofen-1 data using object-oriented classification techniques
Author :
Jinjie Meng;Huazhong Ren;Qiming Qin;Chen Du;Jianhua Wang;Lian He;Jing Li;Huawei Wan
Author_Institution :
Institute of Remote Sensing and GIS, School of Earth and Space Science, Peking University, Beijing 100871, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
The urbanization process changed the urban ecological land and consequently affected the quality of urban residents´ environment, and it was very important to obtain urban ecological land cover information. In this paper, an object-oriented method was proposed to extract urban ecological land cover from the multiple-channel images acquired by Chinese Gaofen-1 (GF-1) satellite. Taking Beijing City as an example, five ecological land covers, including water, vegetation, road, building land and bare land, were classified using new classification rules based on the spectral, geometry and texture information in the GF-1 image. The result showed that the urban land covers were accurately identified and its validation accuracy was up to 90%.
Keywords :
"Accuracy","Buildings","Vegetation mapping","Image segmentation","Roads","Data mining","Remote sensing"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326466