Vegetation indices have been widely used in remote sensing literature for burned land mapping and monitoring. In the present study we used satellite data (IKONOS, LANDSAT, ASTER, MODIS) of multiple spectral (visible, near, shortwave infrared) and spatial (1-500 meters) resolutions, acquired shortly after a very destructive fire occurred in the mountain of Parnitha in Attica, Greece the summer of 2007. The aim of our study is to examine and evaluate the performance of some vegetation indices for burned land mapping and also to characterize the relationships between vegetation indices and the percent of fire-scorched (burned) and non fire-scorched (vegetated) areas. The available satellite images were processed geometrically, radiometrically and atmospherically. The very high resolution IKONOS imagery was served as a base to estimate the percent of cover of burned areas, bare soil and vegetation by applying the maximum likelihood classification algorithm. The percent of cover for each type was then correlated to vegetation indices for all the satellite images, and regression models were fit to characterize those relationships. In total 57 versions of some classical vegetation indices were computed using LANDSAT, ASTER and MODIS data. Most of them were modified by replacing Red with SWIR channel, as the latter has been proved sensitive to burned area discrimination. IPVI and NDVI showed a better performance among the indices tested to estimate the percent of vegetation, while most of the modified versions of the indices showed highest performance to estimate the percent of burned areas.
The application of vegetation indices is a very common approach in remote sensing of burned areas to either map the fire scar or estimate burn severity since they minimize the effect of exogenous factors and enhance the correlation with the internal parameters of vegetation. In a recent study we found that the original spectral channels, based on which these indices are estimated, are sensitive to external parameters of the vegetation as for example the spectral reflectance of the background soil. In such cases, the influence of the soil in the reflectance values is different in the various spectral regions depending on its type. These problems are further enhanced by the non-homogeneous pixels, as created from fractions of different types of land cover. Parnitha (Greece), where a wildfire occurred on July 2007, was established as test site. The purpose of this work is to explore the sensitivity of vegetation indices when used to estimate and map different fractions of fire-scorched (burned) and non fire-scorched (vegetated) areas. IKONOS, a very high resolution satellite imagery, was used to create a three-class thematic map to extract the percentages of vegetation, burned surfaces, and bare soil. Using an overlaid fishnet we extracted samples of completely “burned”, completely “vegetated” pixels and proportions with different burn/vegetation ratios (45%-55% burned – 45%-55% vegetation, 20%-30% burned – 70%- 80% vegetation, 70%-80% burned – 20%-30% vegetation). Vegetation indices were calculated (NDVI, IPVI, SAVI) and their values were extracted to characterize the mentioned classes. The main findings of our recent research were that vegetation indices are less sensitive to external parameters of the vegetation by minimizing external effects. Thus, the semi-burned classes were spectrally more consistent to their different fractions of scorched and non-scorched vegetation, than the original spectral channels based on which these indices are estimated.