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Multi-source remote sensing of ecologica land in BeijingTianjinTangshan Metropolitan based on threshold segmentation method.

PENG Jian1,2**, LU Hui-ling2, MA Jing1, LIU Yan-xu1   

  1. (1Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China; 2Key Laboratory for Environmental and Urban Sciences, School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong, China)
  • Online:2015-01-10 Published:2015-01-10

Abstract:

Eco-environmental problems have become increasingly prominent during the process of rapid urbanization in China. Quick remote sensing identification of regional ecological land can provide the basic data for solving the problems in urban agglomeration. In view of the merits and defects of different types of remote sensing data on characterization of a particular type of feature, remote sensing retrieval of regional ecological land with integrated multisource information has become a hot direction of current research. Therefore, this paper took BeijingTianjinTangshan Metropolitan as an example, considering the advantages of DMSP/OLS nighttime lights data and SPOT/VGT data in identifying construction land and vegetation coverage. The study first used SPOT/VGT data to quantitatively identify the forest land, grassland and cropland, then based on DMSP/OLS nighttime lights data to distinguish water body from construction land. The results showed that the overall accuracy of remotely sensed land cover patterns in BeijingTianjinTangshan Metropolitan reached 85.64%, and the Kappa coefficient was 0.771. The identification accuracy of forest land was the highest (90.87%), water body took the second place (78.33%), and grassland was the lowest (70.97%). This method was proved to be effective to solve the shortage of monosource remote sensing data to quickly distinguish various types of ecologica land.
 

Key words: precipitation regime, soil water content, transpiration, sap flow, semi-aridarea