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Title
Japanese: 
English:MERIT DEM: A new high-accuracy global digital elevation model and its merit to global hydrodynamic modeling 
Author
Japanese: 山崎大, 池嶋大樹, Jeffrey C. Neal, Fiachra O'Loughlin, Christopher C Sampson, 鼎信次郎, Paul D Bates.  
English: Dai Yamazaki, Daiki Ikeshima, Jeffrey C. Neal, O'Loughlin Fiachra, Sampson Christopher C, Shinjiro Kanae, Bates Paul D.  
Language English 
Journal/Book name
Japanese: 
English: 
Volume, Number, Page        
Published date Dec. 11, 2017 
Publisher
Japanese: 
English: 
Conference name
Japanese: 
English:AGU Fall Meeting 2017 
Conference site
Japanese: 
English:New Orleans 
Official URL https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/210505
 
Abstract Digital Elevation Models (DEM) are fundamental data for flood modelling. While precise airborne DEMs are available in developed regions, most parts of the world rely on spaceborne DEMs which include non-negligible height errors. Here we show the most accurate global DEM to date at ~90m resolution by eliminating major error components from the SRTM and AW3D DEMs. Using multiple satellite data and multiple filtering techniques, we addressed absolute bias, stripe noise, speckle noise and tree height bias from spaceborne DEMs. After the error removal, significant improvements were found in flat regions where height errors were larger than topography variability, and landscapes features such as river networks and hill-valley structures became clearly represented. We found the topography slope of the previous DEMs was largely distorted in most of world major floodplains (e.g. Ganges, Nile, Niger, Mekong) and swamp forests (e.g. Amazon, Congo, Vasyugan). The developed DEM will largely reduce the uncertainty in both global and regional flood modelling.

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