%0 Journal Article %1 Yebra2009 %A Yebra, Marta %A Chuvieco, Emilio %D 2009 %J Remote Sensing of Environment %K ecology fire firemafs fires inversions modeling models moisture radiativetransfer remotesensing satellite vegetation wildfire %P - %R DOI: 10.1016/j.rse.2009.07.001 %T Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem %U http://www.sciencedirect.com/science/article/B6V6V-4X00P90-1/2/2cd7da0a168f5956ca57620cdbf18327 %V In Press, Corrected Proof %X Live fuel moisture content (FMC) is a key factor required to evaluate fire risk and its operative and accurate estimation is essential for allocating pre-fire resources as a part of fire prevention. This paper presents an operative and accurate procedure to estimate FMC though MODIS (moderate resolution imaging spectrometer) data and simulation models. The new aspects of the method are its consideration of several ecological criteria to parameterize the models and consistently avoid simulating unrealistic spectra which might produce indetermination (ill-posed) problems when inverting the model. The methodology was operatively applicable to 12 shrubland plots located in different provinces of the Mediterranean region of Spain and tested with field data collected in those areas. The results showed that the proposed method efficiently tracks changes of FMC with average errors around 15%. However the model under-estimates FMC values higher than 135.68% since those situations were not included in the simulation scheme and the inversion precision is also dependent on an accurate estimation of LAI. These limitations will be overcome in future work mainly by including spectral signatures of vegetation with FMC values higher than 135.68% in the simulations, and by exploring new methods for LAI retrieval. Further efforts will also be devoted to extend this approach to other ecosystems.

@article{Yebra2009, abstract = {Live fuel moisture content (FMC) is a key factor required to evaluate fire risk and its operative and accurate estimation is essential for allocating pre-fire resources as a part of fire prevention. This paper presents an operative and accurate procedure to estimate FMC though MODIS (moderate resolution imaging spectrometer) data and simulation models. The new aspects of the method are its consideration of several ecological criteria to parameterize the models and consistently avoid simulating unrealistic spectra which might produce indetermination (ill-posed) problems when inverting the model. The methodology was operatively applicable to 12 shrubland plots located in different provinces of the Mediterranean region of Spain and tested with field data collected in those areas. The results showed that the proposed method efficiently tracks changes of FMC with average errors around 15%. However the model under-estimates FMC values higher than 135.68% since those situations were not included in the simulation scheme and the inversion precision is also dependent on an accurate estimation of LAI. These limitations will be overcome in future work mainly by including spectral signatures of vegetation with FMC values higher than 135.68% in the simulations, and by exploring new methods for LAI retrieval. Further efforts will also be devoted to extend this approach to other ecosystems.}, added-at = {2009-08-12T12:23:17.000+0200}, author = {Yebra, Marta and Chuvieco, Emilio}, biburl = {https://www.bibsonomy.org/bibtex/28665c9eba4206907ffc17b1552aff7b0/jgomezdans}, description = {ScienceDirect - Remote Sensing of Environment : Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem}, doi = {DOI: 10.1016/j.rse.2009.07.001}, interhash = {2588a01786803c19af8c35d2fed22972}, intrahash = {8665c9eba4206907ffc17b1552aff7b0}, issn = {0034-4257}, journal = {Remote Sensing of Environment}, keywords = {ecology fire firemafs fires inversions modeling models moisture radiativetransfer remotesensing satellite vegetation wildfire}, pages = { - }, timestamp = {2009-08-12T12:23:17.000+0200}, title = {Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem}, url = {http://www.sciencedirect.com/science/article/B6V6V-4X00P90-1/2/2cd7da0a168f5956ca57620cdbf18327}, volume = {In Press, Corrected Proof}, year = 2009 }