Description
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. 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.
