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ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) v.124, 2017년, pp.89 - 105   SCIE
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Quantifying annual changes in built-up area in complex urban-rural landscapes from analyses of PALSAR and Landsat images

Qin, Yuanwei (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA ); Xiao, Xiangming (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA ); Dong, Jinwei (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA ); Chen, Bangqian (Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China ); Liu, Fang (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China ); Zhang, Geli (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA ); Zhang, Yao (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA ); Wang, Jie (Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, N ); Wu, Xiaocui ( );
  • 초록  

    Abstract Built-up area supports human settlements and activities, and its spatial distribution and temporal dynamics have significant impacts on ecosystem services and global environment change. To date, most of urban remote sensing has generated the maps of impervious surfaces, and limited effort has been made to explicitly identify the area, location and density of built-up in the complex and fragmented landscapes based on the freely available datasets. In this study, we took the lower Yangtze River Delta (Landsat Path/Row: 118/038), China, where extensive urbanization and industrialization have occurred, as a case study site. We analyzed the structure and optical features of typical land cover types from (1) the HH and HV gamma-naught imagery from the Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and (2) time series Landsat imagery. We proposed a pixel- and rule-based decision tree approach to identify and map built-up area at 30-m resolution from 2007 to 2010, using PALSAR HH gamma-naught and Landsat annual maximum Normalized Difference Vegetation Index (NDVI max ). The accuracy assessment showed that the resultant annual maps of built-up had relatively high user (87–93%) and producer accuracies (91–95%) from 2007 to 2010. The built-up area was 2805km 2 in 2010, about 16% of the total land area of the study site. The annual maps of built-up in 2007–2010 show relatively small changes in the urban core regions, but large outward expansion along the peri-urban regions. The average annual increase of built-up area s was about 80km 2 per year from 2007 to 2010. Our annual maps of built-up in the lower Yangtze River Delta clearly complement the existing maps of impervious surfaces in the region. This study provides a promising new approach to identify and map built-up area, which is critical to investigate the interactions between human activities and ecosystem services in urban-rural systems.


  • 주제어

    Built-up .   Impervious surface .   Urban-rural area .   Landsat .   PALSAR .   Shanghai.  

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