35 research outputs found
Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with landsat thematic mapper
In this study several pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment are evaluated. GeoCBI (Geo Composite Burn Index) field data of burn severity were correlated with remotely sensed measures, based on the NBR (Normalized Burn Ratio), the NDMI (Normalized Difference Moisture Index) and the NDVI (Normalized Difference Vegetation Index). In addition, the strength of the correlation was evaluated for specific fuel types and the influence of the regression model type is pointed out. The NBR was the best remotely sensed index for assessing burn severity, followed by the NDMI and the NDVI. For this case study of the 2007 Peloponnese fires, results show that the GeoCBI-dNBR (differenced NBR) approach yields a moderate-high R(2) = 0.65. Absolute indices outperformed their relative equivalents, which accounted for pre-fire vegetation state. The GeoCBI-dNBR relationship was stronger for forested ecotypes than for shrub lands. The relationship between the field data and the dNBR and dNDMI (differenced NDMI) was nonlinear, while the GeoCBI-dNDVI (differenced NDVI) relationship appeared linear
Assessing the temporal sensitivity of the differenced Normalized Burn Ratio (dNBR) to estimate burn severity using MODIS time series
A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT)
Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire-burn severity using multitemporal MODIS imagery
This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (a), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed a and LST as indicators for fire-burn severity. Immediately after the fire event, mean a dropped up to 0.039 (standard deviation = 0.012) (P < 0.001), mean LSTd increased up to 8.4 (3.0) K (P < 0.001), and mean LSTn decreased up to -1.2 (1.5) K (P < 0.001) for high-severity plots (P < 0.001). After this initial alteration, fire-induced changes become clearly smaller and seasonality starts governing the a and LST time series. Compared with the fire-induced changes in a and LST, the post-fire NDVI drop was more persistent in time. This temporal constraint restricts the utility of remotely sensed a and LST as indicators for fire-burn severity. For the times when changes in a and LST were significant, the magnitude of changes was related to fire-burn severity, revealing the importance of vegetation as a regulator of land surface energy fluxes