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Land Surface Data Assimilation

  • Paul R. HouserEmail author
  • Gabriëlle J.M. De Lannoy
  • Jeffrey P. Walker
Chapter

Abstract

Accurate knowledge of spatial and temporal land surface storages and fluxes are essential for addressing a wide range of important, socially relevant science, education, application and management issues. Improved estimates of land surface conditions are directly applicable to agriculture, ecology, civil engineering, water resources management, rainfall-runoff prediction, atmospheric process studies, climate and weather prediction, and disaster management (Houser et al. 2004).

Keywords

Soil Moisture Kalman Filter Data Assimilation Brightness Temperature Extend Kalman Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paul R. Houser
    • 1
    Email author
  • Gabriëlle J.M. De Lannoy
    • 1
    • 2
  • Jeffrey P. Walker
    • 3
  1. 1.George Mason UniversityFairfaxUSA
  2. 2.Ghent UniversityGhentBelgium
  3. 3.Department of Civil and Environmental EngineeringThe University of MelbourneVictoriaAustralia

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