Limnology Studies
Published November 14, 2014 | Version 1.0
Dataset Open

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Creators

  • 1. ETH Zurich
  • 2. McGill University
  • 3. IWMI
  • 4. IRD-LEGOS
  • 5. Michigan State University

Description

Overview: The Global Inundation Extent from Multi-Satellites (GIEMS; Prigent et al. 2007, Papa et al. 2010) downscaled at 15 arc-second (GIEMS-D15; Fluet-Chouinard et al. 2015) was produced through the downscaling of the GIEMS database (natively at 0.25°).  The downscaling procedure predicts the location of surface water cover with an inundation ranking surface generated by bagged decision trees. The decision trees were trained on binary presence/absence of wetland in the GLC2000 global land cover map (Bartholomé & Belward 2005) and used 13 topographic and hydrographic predictors derived from the SRTM-derived HydroSHEDS database (Lehner, Verdin & Jarvis 2008). The downscaling technique to three temporal aggregation of the GIEMS dataset representing three states of land surface inundation extents: mean annual minimum (MAMin; total area, 6.5 × 106 km2), mean annual maximum (MAMax; 12.1 × 106 km2), and long-term maximum (LTMax; 17.3 × 106 km2). The area of MAMin and MAMax from GIEMS were supplemented with the minimum area value from lakes, river and reservoirs from GLWD (Lehner & Döll 2004; classes 1,2,3). LTMax was corrected as the mean area from 3-year rolling maximum from GIEMS and the total wetland area from GLWD (classes 1-12). The accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates. Yet, a comparison against independent regional wetland maps showed adequate agreement over large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than originally offered by GIEMS, allowing for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems.

Projection: WGS84 (EPSG:4326)

Geographic extent:

  • Longitude: -180° to 180°
  • Latitude: -56° to 84°

Spatial resolution: 15 arc-second (500m at equator)

Legend (for discrete pixel values):

  • 0 = Upland
  • 1 = Mean Annual Minimum (MAMin)
  • 2 = Mean Annual Maximum (MAMax)
  • 3 = Long Term Maximum (LTMax)

Notes

For questions/comments contact: Etienne Fluet-Chouinard (etienne.fluet@env.ethz.ch) Filipe Aires (filipe.aires@obspm.fr)

Files

giemsd15.zip

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Additional details

References

  • Bartholomé, E., & Belward, A.S. (2005). GLC2000: A new approach to global land cover mapping from earth observation data. International Journal of Remote Sensing, 26(9), 1959–1977.
  • Fluet-Chouinard, E., Lehner, B., Rebelo, L. M., Papa, F., & Hamilton, S. K. (2015). Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data. Remote Sensing of Environment, 158, 348-361.
  • Lehner, B., & Döll, P. (2004). Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology, 296(1–4), 1–22.
  • Lehner, B., Verdin, K., & Jarvis, A. (2008). New global hydrography derived from spaceborne elevation data. EOS, 89(10), 93–94
  • Papa, F., Prigent, C., Aires, F., Jimenez, C., Rossow, W.B., & Matthews, E. (2010). Interannual variability of surface water extent at the global scale, 1993–2004. Journal of Geophysical Research, 115(D12111), 1–17.
  • Prigent, C., Papa, F., Aires, F., Rossow, W.B., & Matthews, E. (2007). Global inundation dynamics inferred from multiple satellite observations, 1993–2000. Journal of Geophysical Research, 112(D12107), 1–13.