Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper

Abstract

In this study several pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment are evaluated. Therefore 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 non-linear, while the GeoCBI-dNDVI (differenced NDVI) relationship appeared linear.

Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data

“…The few studies in the California chaparral shrublands demonstrated that the NBR is reasonably well related to fire severity, however, none of them conducted an inter-indices comparison. In Mediterranean shrublands in Europe similar findings were obtained by De Santis and Chuvieco [18], Veraverbeke et al [32,33], Escuin et al [42] and Tanase et al [43]. Limited comparisons with other spectral indices were undertaken by De Santis and Chuvieco [18], Veraverbeke et al [32,33] and Escuin et al [42] concluding that the NBR outperformed the Normalized Difference Vegetation Index (NDVI) for assessing fire severity in Mediterranean shrublands.…”

“…In Mediterranean shrublands in Europe similar findings were obtained by De Santis and Chuvieco [18], Veraverbeke et al [32,33], Escuin et al [42] and Tanase et al [43]. Limited comparisons with other spectral indices were undertaken by De Santis and Chuvieco [18], Veraverbeke et al [32,33] and Escuin et al [42] concluding that the NBR outperformed the Normalized Difference Vegetation Index (NDVI) for assessing fire severity in Mediterranean shrublands. In addition, several authors indicated that the post-fire temperature increase as observed in the thermal infrared (TIR) domain [44,45] is complementary to the NBR for discriminating burned areas [46][47][48].…”

“…The standard ATCOR4 desert aerosol model was chosen. The visible through SWIR bands (1-25) were processed to surface reflectance, the MIR bands (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40) were not atmospherically corrected and the thermal bands (41)(42)(43)(44)(45)(46)(47)(48)(49)(50) were atmospherically corrected to surface radiance. The surface radiance of the thermal bands was then separated into surface temperature (T s ) and surface emissivity ( ) using the emissivity normalization method [54].…”

“…Previous research has demonstrated that the performance of the NBR approach varies among ecoregions and vegetation types [26,27,[31][32][33]. Consequently, there is need to independently validate the approach for specific regions and vegetation types [13,26,34,35] to determine if the technique is capable of inferring fire/burn severity from satellite imagery [31].…”

Evaluating the Best Spectral Indices for the Detection of Burn Scars at Several Post-Fire Dates in a Mountainous Region of Northwest Yunnan, China

“…Despite low discrimination capabilities, NDMI and NBR are the best choice, while Wetness could offer a valuable support in shrublands starting from two years after the fires. In more vegetated areas such as broadleaved and needleleaved forests, fire scars are more persistent and NBR has often shown to perform better than in sparsely vegetated land [20,77]. From one to five years after the fire, the best SI are NBR and NDMI, followed by NDVI in broadleaved vegetation and BAIML in needle leaved vegetation.…”