ID:
publications-1549
Type:
PEER REVIEWED ARTICLE
Year:
2017
Authors:
Filipe Aires , Léo Miolane , Catherine Prigent , Binh Pham , Etienne Fluet-Chouinard , Bernhard Lehner , Fabrice Papa
Title:
A global dynamic long-term inundation extent dataset at high spatial resolution derived through downscaling of satellite observations
Venue/Journal:
DOI:
10.1175/jhm-d-16-0155.1
Research type:
Simulation & Modeling
Water System:
Precipitation & Ecological Systems
Technical Focus:
Abstract:
Abstract A new procedure is introduced to downscale low-spatial-resolution inundation extents from Global Inundation Extent from Multi-Satellites (GIEMS) to a 3-arc-s (90 m) dataset (known as GIEMS-D3). The methodology is based on topography and hydrography information from the HydroSHEDS database. A new floodability index is introduced and an innovative smoothing procedure is developed to ensure a smooth transition, in the high-resolution maps, between the low-resolution boxes from GIEMS. Topography information is pertinent for natural hydrology environments controlled by elevation but is more limited in human-modified basins. However, the proposed downscaling approach is compatible with forthcoming fusion of other, more pertinent satellite information in these difficult regions. The resulting GIEMS-D3 database is the only high-spatial-resolution inundation database available globally at a monthly time scale over the 1993–2007 period. GIEMS-D3 is assessed by analyzing its spatial and temporal variability and evaluated by comparisons to other independent satellite observations from visible (Google Earth and Landsat), infrared (MODIS), and active microwave (synthetic aperture radar).
Link with Projects:
603608
Link with Tools:
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