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sarn-method's Introduction

SARN (Sentinel-ArcticDEM merged River Network)

Environment

Python with ArcPy package

Prepare data

  • DEM-modeled drainage network.shp: the DEM-modeled drainage network polyline
  • RS-mapped river network.shp: the river centerlines of the RS water body mask. We used the river detection method proposed by Kang Yang (https://github.com/njuRS/River_detection.git). You can use the customed RS water body mask instead.
  • RS water mask.tif: the binary water body mask, water is set to 1, non-water is 0

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In order to ensure this code runs correctly, please make sure the coordinates are consistent

Create Geodatabase

Create a File Geodatabase.gdb and import the three files in it. All process data will be saved in this database.

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Run river connection code

  • Open connect_river.py in Python.
  • Set input 6 parameters.
parameters description
workspace the path of the geodatabaseset
DEM the name of the DEM-modeled drainage network
RS_vector the name of the RS-mapped river centerlines
RS_Raster the name of the RS binary water body mask
cell size the cell size of the images, Sentinel-2 imagery is 10
delete_length river length less than 300 m will be deleted
  • Click run.

  • These two shapefiles in the red box are the result. unspit_split_coincide + DEM name.shp is the RS-mapped river segments, and unspit_split_connect + DEM name.shp is the DEM-modeled river segments.

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Acknowledgements

Cite

Lu, X., Yang, K., Lu, Y., Gleason, C.J., Smith, L.C., & Li, M. (2020). Small Arctic rivers mapped from Sentinel-2 satellite imagery and ArcticDEM. Journal of Hydrology, 584, 124689

Corresponding Author

  • Xin Lu ([email protected], ph:15951756762, School of Geography and Ocean Science, Nanjing University)
  • Kang Yang ([email protected], School of Geography and Ocean Science, Nanjing University)
  • Yao Lu ([email protected], School of Geography and Ocean Science, Nanjing University)

sarn-method's People

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