Remote Sensing of Vegetation Water and Fire Risk

The research presented in this book is aimed at
reviewing, evaluating and improving remote sensing
techniques for vegetation water and fire risk
estimation. Coupled reflectance models, fire spread
models and meteorological data is first used to
estimate expected errors in remote sensing based
vegetation moisture retrievals and understand the
effect of such uncertainties on fire spread rate
predictions. An analysis of the characteristics of
soil and canopy reflectance is then used as a basis
for designing a vegetation water index, which is more
resistant to soil reflectance contamination.
Vegetation water content estimation using the
improved index is shown to reduce soil moisture
related errors over low vegetation areas, where soil
reflectance contamination is a major problem. This
work also uses the physical concept of pre-ignition
energy to propose a new remote sensing based fire
risk index. The physical basis of this new Fire
Susceptibility Index offers several advantages over
other fire risk indices. The new approaches described
in this book would be helpful for fire risk
monitoring, agricultural applications and climate
studies.

Autorentext

Dr. Dasgupta received his Ph.D in Computational Sciences &Informatics from George Mason University in 2007. In 2006 he wasawarded the NASA Earth System Science Fellowship to conductresearch on the remote sensing of fire risk and vegetationmoisture. He is also involved in research and developmentof satellite direct broadcast technologies.

Klappentext

The research presented in this book is aimed atreviewing, evaluating and improving remote sensingtechniques for vegetation water and fire riskestimation. Coupled reflectance models, fire spreadmodels and meteorological data is first used toestimate expected errors in remote sensing basedvegetation moisture retrievals and understand theeffect of such uncertainties on fire spread ratepredictions. An analysis of the characteristics ofsoil and canopy reflectance is then used as a basisfor designing a vegetation water index, which is moreresistant to soil reflectance contamination.Vegetation water content estimation using theimproved index is shown to reduce soil moisturerelated errors over low vegetation areas, where soilreflectance contamination is a major problem. Thiswork also uses the physical concept of pre-ignitionenergy to propose a new remote sensing based firerisk index. The physical basis of this new FireSusceptibility Index offers several advantages overother fire risk indices. The new approaches describedin this book would be helpful for fire riskmonitoring, agricultural applications and climatestudies.