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Tracking dynamic river networks in the Tibetan Plateau with high-resolution CubeSat imagery

  • role： First author第一作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

  • Email：zhangst_nju@163.com
  • Introduction：章斯腾，1996年生，男，助理工程师，研究方向为水文遥感。E-mail：zhangst_nju@163.com
ZHANG Siteng1,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

LU Xin1,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

LU Yao1,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

    Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210023, China

CHENG Liang123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

    Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210023, China

LI Manchun123,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

    Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210023, China

  • Email：kangyang@nju.edu.cn
  • Introduction：杨康，1986年生，男，副教授，研究方向为水文遥感、冰冻圈遥感。E-mail：kangyang@nju.edu.cn
YANG Kang123*

реферат

River networks play an important role in the terrestrial water. They have become a hotspot in river remotely sensed studies on using remotely sensed imagery to monitor river dynamic changes. Recent development of CubeSat satellite, such as PlanetScope, allows monitoring of river networks at high spatial and high temporal resolution by providing near-daily revisit time imagery at 3 m spatial resolution. We selected the Yangtze headwaters (Tongtian river basin, ~227 km²) located in Tibetan Plateau as the study area. Five CubeSat images from May to October in 2017 were selected to extract river networks at 3 m resolution by enhancing the river cross sectional and longitudinal features, in order to monitor dynamic changes of in river networks at high-spatial resolution. In addition, we compared the 3 m CubeSat river networks with 30 m Landsat 8 and 10 m Sentinel-2 river networks, and the five existing hydrography data products including GRWL, GSW, FROM-GLC, OpenStreetMap, and HydroSHEDS. We concluded that: (1) Rivers in the study area begin to develop in May with drainage density of 0.38 km-1. July and August are the wet seasons, and the drainage density reaches the peak (0.61 km-1). In September, rivers reach the mean discharge with drainage density of 0.53 km-1, and then the rivers degrade gradually with drainage density of 0.37 km-1 and begin to freeze in October. (2) The high spatial resolution CubeSat river networks include more small rivers (3—30 m wide), and the CubeSat river length is 1.6 and 1.3 times larger than Landsat 8 and Sentinel-2 river networks, respectively. (3) The drainage density of CubeSat river networks is 2.9 to 12.4 times larger than existing hydrography data products, thereby compensating for any lack in the spatial and temporal resolution of the existing river network products.

ключеви́че слова́

river network;remote sensing information extraction;dynamic monitoring;CubeSat;Tibetan Plateau

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