Title :
Comparison of extracting the urban green land from satellite images with multi-resolutions
Author :
Yang, Cunjian ; Huang, He ; Zhang, Yang ; Cheng, Jin-an
Author_Institution :
Key Lab. of land resources evaluation & monitoring, Sichuan Normal Univ., Chengdu
Abstract :
The urban green land information is very important for planning urban and improving its environment. Satellite remote sensing provides advanced technology for obtaining the urban green land. Extracting the urban green land respectively from Beijing-1 Micro-satellite (BJ-1MS) and SPOT images is studied and compared in Chengdu city of P.R. of China. The urban green land area can be accurately extracted by combining BJ-1MS panchromatic image and spectral-band images, which is close to the urban green land area extracted from SPOT multi-spectral images. The difference of the urban green land area respectively extracted from SPOT multi-spectral images and BJ-1MS by combining BJ-1MS panchromatic image and spectral-band images is about 1831109 m2 , which accounts for percent 1.9 of the urban green land area from the SPOT. The difference of the urban green land area respectively extracted from BJ-1MS multi-spectral images and SPOT multi-spectral images is very large, which accounts for percent 23 of the urban green land area from the SPOT. It is shown that BJ-1MS can be used to effectively extract the urban green land by combining BJ-1MS panchromatic image and spectral-band images.
Keywords :
land use planning; remote sensing; vegetation; BJ-1MS; Beijing-1 Micro-satellite; Chengdu city; China; SPOT image; Satellite Pour l´Observation de la Terre; land use planning; middle density vegetation region; panchromatic image; remote sensing; satellite image extraction; spectral-band image; urban green land; Cities and towns; Data mining; Image resolution; Multispectral imaging; Nearest neighbor searches; Polynomials; Remote monitoring; Satellites; Solid modeling; Urban planning;
Conference_Titel :
Urban Remote Sensing Event, 2009 Joint
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3460-2
Electronic_ISBN :
978-1-4244-3461-9
DOI :
10.1109/URS.2009.5137678