Advances on Urban Impervious Surface Extraction Using Remote Sensing Data

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Abstract:

Urban impervious surface is an artificial surface features of the city, affecting urban surface runoff, the hydrological cycle, water quality, local climate and biodiversity, is one of the important indicators of the modern urbanization and urban ecosystem monitoring. With the development of urban remote sensing, various resolution remote sensing images have been used in urban impervious surface extraction. In this paper, image source remote sensing image classification criteria focus on the application of the various resolution remote sensing image, application methods and applications; summary evaluation of the existing methods, finally pointed out the future prospects.

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Advanced Materials Research (Volumes 726-731)

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4552-4557

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Sheng Li. Study on the Information Extraction of the Urban Heat Island, Run-off and Impervious Surface in Xiamen City of SE China with Remote Sensing Technology[D], Fuzhou University, (2005).

Google Scholar

[2] Li-ming JIANG, Ming-sheng LIAO, Hui LIN, Li-min Yang, Journal of Remote Sensing (2008).

Google Scholar

[3] Slonecker E T, Jennings D, Garofalo D. Remote Sensing Reviews (2001).

Google Scholar

[4] Jie CHEN, Object-oriented classification method research for high-resolution remote sensing images [D], Central South University, (2010).

Google Scholar

[5] M Baatz, A Schape. Object-oriented and multi-scale image analysis in semantic networks [A]. Proc of the 2nd International Symposium on Operationalization of Remote Sensing[C]. (1999).

Google Scholar

[6] U C Benz, P Hofmann, G Willhauck, et al. ISPRS Journal of Photogrammetry & Remote Sensing (2004).

Google Scholar

[7] Cai-li LI, Jin-kang Du, Tian-hui ZUO. Remote Sensing Applications (2009).

Google Scholar

[8] Shuang CHEN, Xiu-yin ZHANG, Li-hua PENG. Resources Science (2006).

Google Scholar

[9] YUAN F, BAUER M E. Remote Sensing of Environment (2007).

Google Scholar

[10] WN Li, J Yang, JL Zhang, et al. Remote Sensing for Land and Resources (2013).

Google Scholar

[11] Shahtahmassebi Amirreza, Yu Zhoulu, Wang Ke, Xu Hongwei, Deng Jinsong, Li Jiadan, Luo Ruisen, Wu Jing, Moore Nathan. Journal of Zhejiang University-Science A (2012).

Google Scholar

[12] Luo Li, Mountrakis Giorgos. International Journal of Remote Sensing (2012).

Google Scholar

[13] Luo Li, Mountrakis Giorgos, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2011).

Google Scholar

[14] Qihao Weng , Xuefei Hu & Dengsheng Lu (2008), International Journal of Remote Sensing.

Google Scholar

[15] Ridd M K. International Journal of Remote Sensing (1995).

Google Scholar

[16] Phinn S, Stanford M, Scarth P, et al. International Journal of Remote Sensing (2002).

Google Scholar

[17] SMALLL C. Remote Sensing of Environment (2004).

Google Scholar

[18] WU C S, MURRAY A T. Remote Sensing of Environment (2003).

Google Scholar

[19] Weng Q H, Lu D S. Remote Sensing of Environment (2004).

Google Scholar

[20] Lu D, Weng Q. Remote Sensing of Environment (2006).

Google Scholar

[21] C. Wu. Remote Sensing of Environment (2004).

Google Scholar

[22] Rashed T, Weeks J R., Roberts D, et al. Photogrammetric Engineering and Remote Sensing (2003).

Google Scholar

[23] Lin-shan YUAN, Pei-jun DU, Hua-peng ZHANG, Hai-rong ZHANG. Remote Sensing For Land & Resources. (2008).

Google Scholar

[24] X F HU, Q H WENG. Remote Sensing of Environment(2009).

Google Scholar

[25] Flanagan M, Civco D L. Sub-pixel impervious surface mapping[C]. ASPRS Annual Conference Proceedings, St. Louis, Missouri, April 2001(Unpaginated CD ROM).

Google Scholar

[26] Xi CHENG, Zhanfeng SHEN, Jianceng LUO, Changming ZHU, Yanan ZHOU, Xiaodong HU. Journal of Remote Sensing(2011).

Google Scholar

[27] Chan Yong Sung & Ming-Han Li(2012), International Journal of Remote Sensing.

Google Scholar

[28] Zhongchang Sun, Huadong Guo, Xinwu Li, Linlin Lu, Xiaoping Du. Journal of Applied Remote Sensing (2011).

Google Scholar

[29] Xuefei Hu, Qihao Weng. Remote Sensing of Environment(2009).

Google Scholar

[30] Bo WU, Liang-pei ZHANG, Ping-xiang LI. Journal of Remote Sensing (2006).

Google Scholar

[31] Jun-shi XIA, Pei-jun DU, Yun-feng PANG, Wen CAO, Xiao-ling WANG et al. Journal of China University of Mining & Technology (2011).

Google Scholar

[32] Qihao Weng, Xuefei Hu, Dengsheng Lu (2008). International Journal of Remote Sensing.

Google Scholar

[33] Dengsheng Lu, Guiying Li, Emilio Moran, Mateus Batistella, Corina C. Freitas. ISPRS Journal of Photogrammetry and Remote Sensing(2011).

Google Scholar

[34] Limin Yang, Limin Jiang, Hui Lin, Mingsheng Liao. GISCIENCE & REMOTE SENSING(2009).

Google Scholar

[35] Liming Jiang, Mingsheng Liao, Hui Lin & Limin Yang. International Journal of Remote Sensing (2009).

Google Scholar

[36] LU D S, WENG Q H. International Journal of Applied Earth Observation and Geoinformation (2008).

Google Scholar