David Cocero

Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: Applications in fire danger assessment

The objective of this paper was to define indices based on reflectance measurements performed by the Landsat Thematic Mapper (TM) sensor for estimating water content of live Mediterranean fuels for fire danger estimation. Seven Landsat TM images were processed and correlated with fuel moisture content (FMC) of several live species of Mediterranean grassland and shrubland. Raw bands were converted to reflectances, and several indices potentially related to water content were calculated from them. Pearson r correlation coefficients and linear regression analysis were computed in order to estimate FMC. Those indices based on the short wave infrared bands (SWIR: 1.4-2.5 w m) and on the contrast between this band and the near-infrared band offered the best estimations. For grassland, the integral of visible and SWIR bands provided the highest correlation, but also raw reflectances and Normalized Difference Vegetation Indices (NDVIs) provide significant r values ( r 2 above 0.8). For shrub species, indices that include SWIR reflectances performed much better than NDVI, because the SWIR band is more sensitive to water absorption, whereas NDVI estimates FMC indirectly, only from the effects of chlorophyll changes due to water variation content and leaf area index. The most significant relations were found with the derivatives of bands 4-5 and 2-3, and again the integral of visible and SWIR bands. Multiple regression analysis provided adjusted r 2 values of 0.84 for grasslands and 0.74 for shrublands. Average errors of 23.45-40% in the estimation of FMC for grasslands were found, depending on which variables were included in the multiple regression. For the FMC estimation of shrub species, errors were lower (from 7.94 to 19.40%), since the range of FMC values was also lower.

Design of an empirical index to estimate fuel moisture content from NOAA-AVHRR images in forest fire danger studies

An empirical estimation of live fuel moisture content (FMC) was generated from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived variables. This estimation was based on the ratio of Normalized Difference Vegetation Index (NDVI) and surface temperature ( T s ), and the relative greenness (RGRE). It was derived for the summer season (from June to September). The estimation was calibrated from field measurements collected in central Spain, and included consideration of both herbaceous and shrub live FMC values. The proposed estimation worked reasonably well for other periods in the same study area and also for other similar study areas in Mediterranean environments. This estimation of FMC from remote sensing could be used as an input to standard fire danger and fire behaviour programs, providing spatially comprehensive data, which is critical for regional planning of fire prevention.

Short-term fire risk: foliage moisture content estimation from satellite data

A description of methods used to determine short-term changes in fire danger is reviewed, mainly those based on the estimation of foliage moisture content (FMC). Applications of low-resolution data, acquired by the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA satellites, as well those based on high-resolution data, are examined. Examples of FMC estimation on Mediterranean areas are also presented, both for AVHRR and Landsat-TM data. In both cases, satellite data provide a higher confidence to estimate FMC in grasslands than in shrublands, although in both cases, some variables provide significant correlation, especially when the spring season is taken into account. The most sensitive variables for FMC estimation are based on short-wave infrared bands, and the combination of vegetation indices and surface temperature.