Natural Hazards

, Volume 43, Issue 2, pp 285–294 | Cite as

Flood and landslide applications of near real-time satellite rainfall products

  • Yang Hong
  • Robert F. Adler
  • Andrew Negri
  • George J. Huffman
Original Paper

Abstract

Floods and associated landslides account for the largest number of natural disasters and affect more people than any other type of natural disaster. With the availability of satellite rainfall analyses at fine time and space resolution, it has also become possible to mitigate such hazards on a near-global basis. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 h and 0.25° × 0.25°. In combination with global land surface datasets it is now possible to expand regional hazard modeling components into a global identification/monitoring system for flood/landslide disaster preparedness and mitigation.

Keywords

Satellite remote sensing Precipitation Flood Landslide 

Notes

Acknowledgment

This research is carried out with support from NASA’s Applied Sciences program under Steven Ambrose of NASA Headquarters.

References

  1. Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E (2003) The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-Present). J Hydrometeor 4:1147–1167CrossRefGoogle Scholar
  2. Artan G, Verdin J, Asante K (2001) A wide-area flood risk monitoring model. Fifth International workshop on application of remote sensing in hydrology, Montpellier, France, October 2–5Google Scholar
  3. Asante KO, Dezanove RM, Artan G, Verdin J (2005) Developing a flood forecasting system from remotely sensed data for the Limpopo Basin. J Spatial Hydrol, in reviewGoogle Scholar
  4. Caine N (1980) The rainfall intensity-duration control of shallow landslides and debris flows, Geografiska Annaler 62A:23–27CrossRefGoogle Scholar
  5. Cannon SH, (1988) Regional rainfall-threshold conditions for abundant debris-flow activity. In: Ellen SD, Wieczorek GF (eds) Landslides, Floods, and Marine Effects of the Storm of January 3–5, 1982, in the San Francisco Bay Region, California: U.S. Geological Survey Professional Paper 1434, p 35–42Google Scholar
  6. Dai EC, Lee CF, Nagi YY (2002): Landslide risk assessment and management: an overview, Eng Geol 64:65–87CrossRefGoogle Scholar
  7. Finlay PJ, Fell R, Maguire PK (1997) The relationship between the probability of landslide occurrence and rainfall. Can Geotech J 34:811–824CrossRefGoogle Scholar
  8. Gesch DB, Verdin KL, Greenlee SK (1999) New land surface digital elevation model covers the Earth. EOS, T Am Geophys Union, 80(6):69–70CrossRefGoogle Scholar
  9. Hong Y, Hsu KL, Gao X, Sorooshian S (2004) Precipitation estimation from remotely sensed imagery using artificial neural network–Cloud Classification system, J Appl Meteorol 43(12):1834–1853CrossRefGoogle Scholar
  10. Hong Y, Adler R, Huffman G (2006a) Evaluation of the NASA multi-satellite precipitation analysis potential in global landslide hazard assessment, Geophysical Research Letter (in press)Google Scholar
  11. Hong Y, Adler R, Huffman G, Negri A (2006b) A conceptual framework for space-borne flood detection/monitoring system, EOS Transaction, AGU, May 23–27, Baltimore, MarylandGoogle Scholar
  12. Hong Y, Adler R, Huffman G (2006c) An experimental global monitoring system for rainfall-triggered landslides using satellite remote sensing information, IEEE trans. on geosciences and remote sensing (in press)Google Scholar
  13. Hong Y, Adler R, Huffman G, Negri A (2006d) Use of satellite remote sensing data in mapping of global shallow landslides susceptibility, Nat Hazards. DOI 10.1007/s11069-006-9104-zGoogle Scholar
  14. Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2006) The TRMM multi-satellite precipitation analysis: quasi-global, multi-year, combined-sensor precipitation estimates at fine scale. J Hydrometeor (in press)Google Scholar
  15. Iverson RM (2000) Landslide triggering by rain infiltration, Water Resour Res 36:1897–1910CrossRefGoogle Scholar
  16. Janowiak J, Joyce RJ, Yarosh Y (2001) A real-time global half-hourly pixel-resolution infrared dataset and its applications. Bull Amer Meteor Soc 82:205–217CrossRefGoogle Scholar
  17. Katiyar, Nitin Faisal Hossain (2006) An open-book modular watershed modeling framework for rapid prototyping of gpm-based flood forecasting in international river basins, EOS Transaction, AGU, May 23–27, Baltimore, MarylandGoogle Scholar
  18. Larsen MC, Simon A (1993) A rainfall intensity-duration threshold for landslides in a humid-tropical environment, Puerto Rico: Geografiska Annaler, 75A, p 13–23Google Scholar
  19. Mahdi T (2007) Pairing geotechnics and fluvial hydraulics for the prediction of the hazard zones of an exceptional flooding. Nat Hazards. DOI 10.1007/s11069-006-9096-8Google Scholar
  20. Negri A, Burkardt N, Golden JH, Halverson JB, Huffman GJ, Larsen MC, Mcginley JA, Updike RG, Verdin JP, Wieczorek GF (2004a) The Hurricane-Flood-Landslide Continuum, BAMS, DOI:10.1175/BAMS-86-9-1241Google Scholar
  21. Negri AJ, Golden JH, Updike RG (2004) The hurricane-flood-landslide continuum -forecasting hurricane effects at landfall, american meteorology society annual conference, Miami, Florida, Jan, 2004bGoogle Scholar
  22. Verdin K, Verdin J (1999) A topological system for delineation and codification of the Earth’s river basins. J Hydrol 218:1–12CrossRefGoogle Scholar
  23. World Disasters Report (2003) International Federation of Red Cross and Red Crescent Societies (IFRCRCS). Preparedness for climate change, a study to assess the future impact of climatic changes upon the frequency and severity of disasters and the implications for humanitarian response and preparedness. Geneva:IFRCRCS.P239 Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • Yang Hong
    • 1
    • 2
  • Robert F. Adler
    • 2
  • Andrew Negri
    • 2
  • George J. Huffman
    • 2
    • 3
  1. 1.Goddard Earth and Science Technology CenterUMBCBaltimoreUSA
  2. 2.Laboratory for AtmospheresNASA Goddard Space Flight CenterGreenbeltUSA
  3. 3.Science Systems and Applications, Inc.GreenbeltUSA

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