Extracting urban areas in China using DMSP/OLS nighttime light data integrated with biophysical composition information  

集成生物物理成分的夜光遥感图像城市用地提取方法（英文）

作　　者：程洋 赵利民 万玮 李玲玲 余涛 顾行发 

机构地区：[1]State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, CAS [2]The Center for National Spaceborne Demonstration [3]University of Chinese Academy of Sciences [4]Department of Hydraulic Engineering, Tsinghua University

出　　处：《Journal of Geographical Sciences》2016年第3期325-338,共14页地理学报（英文版）

基　　金：National Civil Aerospace Pre-research Project(non-disclosure)

摘　　要：DMSP/OLS nighttime light （NTL） image is a widely used data source for urbaniza- tion studies. Although OLS NTL data are able to map nighttime luminosity, the identification accuracy of distribution of urban areas （UAD） is limited by the overestimation of the lit areas resulting from the coarse spatial resolution. In view of geographical condition, we integrate NTL with Biophysical Composition Index （BCl） and propose a new spectral index, the BCl Assisted NTL Index （BANI） to capture UAD. Comparisons between BANI approach and NDVl-assisted SVM classification are carried out using UAD extracted from Landsat TM/ETM＋ data as reference. Results show that BANI is capable of improving the accuracy of UAD extraction using NTL data. The average overall accuracy （OA） and Kappa coefficient of sample cities increased from 88.53% to 95.10% and from 0.56 to 0.84, respectively. Moreover with regard to cities with more mixed land covers, the accuracy of extraction results is high and the improvement is obvious. For other cities, the accuracy also increased to varying de- grees. Hence, BANI approach could achieve better UAD extraction results compared with NDVl-assisted SVM method, suggesting that the proposed method is a reliable alternative method for a large-scale urbanization study in China＇s mainland.DMSP/OLS nighttime light （NTL） image is a widely used data source for urbaniza- tion studies. Although OLS NTL data are able to map nighttime luminosity, the identification accuracy of distribution of urban areas （UAD） is limited by the overestimation of the lit areas resulting from the coarse spatial resolution. In view of geographical condition, we integrate NTL with Biophysical Composition Index （BCl） and propose a new spectral index, the BCl Assisted NTL Index （BANI） to capture UAD. Comparisons between BANI approach and NDVl-assisted SVM classification are carried out using UAD extracted from Landsat TM/ETM＋ data as reference. Results show that BANI is capable of improving the accuracy of UAD extraction using NTL data. The average overall accuracy （OA） and Kappa coefficient of sample cities increased from 88.53% to 95.10% and from 0.56 to 0.84, respectively. Moreover with regard to cities with more mixed land covers, the accuracy of extraction results is high and the improvement is obvious. For other cities, the accuracy also increased to varying de- grees. Hence, BANI approach could achieve better UAD extraction results compared with NDVl-assisted SVM method, suggesting that the proposed method is a reliable alternative method for a large-scale urbanization study in China＇s mainland.

关 键 词：urban area distribution DMSP/OLS biophysical composition index BANI China 

分 类 号：P237[天文地球—摄影测量与遥感]