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SCIENTIA GEOGRAPHICA SINICA >

2007 , Vol. 27 >Issue 6: 837 - 842

DOI: https://doi.org/10.13249/j.cnki.sgs.2007.06.837

Application of Object-oriented Classification in Extraction of Impervious Degree of Urban Surface

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  • 1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, Jiangsu 210008;
    2. School of Environment and Water Conservancy, Zhengzhou University, Zhengzhou, Henan 450002;
    3. Graduate University of the Chinese Academy of Sciences, Beijing 100049

Received date: 2006-10-09

  Revised date: 2007-01-13

  Online published: 2007-11-20

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Abstract

In this paper,based on the multi-resolution image segmentation and object-oriented image classification,the information of the impervious degree of urban surface in Nanjing was extracted by using the objects relationship at the different scales.The results indicated that the imperious degree in Nanjing City was mainly concentrated between 50% and 99%,and the area of higher degree was extensively distributed in Jianye District,Xiaguan District and Gulou District,while the lower was mainly in Xuanwu District.The method of object-oriented image classification could realize the quick extraction of the impervious degree of urban surface,and the output was stability and reliability.

Cite this article

SUN Zhi-Ying, ZHAO Yan-Feng, CHEN Jie, LI Gui-Lin, TAN Man-Zhi . Application of Object-oriented Classification in Extraction of Impervious Degree of Urban Surface[J]. SCIENTIA GEOGRAPHICA SINICA, 2007 , 27(6) : 837 -842 . DOI: 10.13249/j.cnki.sgs.2007.06.837

References

[1] Arnold C L,Gbbons C J.Impervious surface:The emergence of a key environmental indicator[J].Journal of the American Planning Association,1996,62(2):243-258.
[2] Dougherty M,Dymond R L,Goetz S J,et al.Evaluation of impervious surface estimates in a rapidly urbanizing watershed[J].Photogrammetric Engineering & Remote Sensing,2004,70(11):1275-1284.
[3] 陈爽,张秀英,彭立华.基于高分辨卫星影像的城市用地不透水率分析[J].资源科学,2006,28(2):41～46.
[4] Dengsheng Lu,QihaoWeng.Use of impervious surface in urban land-use classification[J].Remote Sensing of Environment,2006,102:146-160.
[5] M Baatz,A Sch(a)pe.Object-Oriented and Multi-Scale Image Analysis in Semantic Networks[M].Proc.of the 2nd International Symposium on Operationalization of Remote Sensing,1999.
[6] U C Benz,P Hofmann,G Willhauck,et al.Multi-resolution,object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J].ISPRS Journal of Photogrammetry & Remote Sensing,2004,58:239-258.
[7] K Shackelford.A Combined Fuzzy Pixel-Based and ObjectBased Approach for Classification of High-Resolution Multispectral Data Over Urban Areas[J].IEEE transactions on Geosciece and Remote sensing,2003,41 (10):2354-2364.
[8] 黄慧萍,吴炳方,李苗苗,等.高分辨率影像城市绿地快速提取技术与应用[J].遥感学报,2004,8(1):68～74.
[9] 莫登奎,林辉,孙华,等.基于高分辨率遥感影像的土地覆盖信息提取[J].遥感技术与应用,2005,20(4):411～414.
[10] 吴炳方,许文波,孙明,等.高精度作物分布图制作[J].遥感学报,2004,8(6):688～695.
[11] 周俊,许建刚.小城镇信息图谱分析[J].地理科学,2002,22(3):324～329.
[12] 吴宏安,蒋建军,周杰,等.基于影象融合的干旱区城镇居民地信息提取研究[J].地理科学,2006,26(4):477 482.
[13] 陈果,顾朝林,吴缚龙.南京城市贫困空间调查与分析[J].地理科学,2004,24(5):542～549.
[14] 吴启焰,任东明.改革开放以来我国城市地域结构演变与持续发展研究--以南京都市区为例[J].地理科学,1999,19(2):108～113.
[15] 周素红,闫小培.城市居住-就业空间特征及组织模式--以广州市为例[J].地理科学,2005,25(6):664～670.
[16] 黎夏,叶嘉安.基于元胞自动机的城市发展密度模拟[J].地理科学,2006,26(2):165～172.
[17] 赵春雨,方觉曙,朱永恒.产业结构与就业结构关联研究--以芜湖市为例[J].地理科学,2006,26(5):536～543.
[18] 李震,顾朝林,姚士谋.当代中国城镇体系地域空间结构类型定量研究[J].地理科学,2006,26(5):544～550.
[19] 李同升,徐冬平.基于SD模型下的流域水资源-社会经济系统时空协同分析--以渭河流域关中段为例[J].地理科学,2006,26(5):551～556.
[20] 程江,杨凯,赵军,等.上海中心城区河流水系百年变化及影响因素分析[J].地理科学,2007,27(1):85～91.
[21] 朱永恒,濮励杰,赵春雨.景观生态质量评价研究--以吴江市为例[J].地理科学,2007,27(2):182～187.
[22] 陈群元,尹长林,陈光辉.长沙城市形态与用地类型的时空演化特征[J].地理科学,2007,27(4):273～280.
[23] 吴志勇,陆桂华,张建云,等.基于VIC模型的逐日土壤含水量模拟[J].地理科学,2007,27(4):359～364.
[24] 吕拉昌.全球城市理论与中国的国际城市建设[J].地理科学,2007,27(4):449～456.
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