Detecting Burn Severity across Mediterranean Forest Types by Coupling Medium-Spatial Resolution Satellite Imagery and Field Data

Abstract

In Mediterranean countries, in the year 2017, extensive surfaces of forests were damaged by wildfires. In the Vesuvius National Park, multiple summer wildfires burned 88% of the Mediterranean forest. This unprecedented event in an environmentally vulnerable area suggests conducting spatial assessment of the mixed-severity fire effects for identifying priority areas and support decision-making in post-fire restoration. The main objective of this study was to compare the ability of the delta Normalized Burn Ratio (dNBR) spectral index obtained from Landsat-8 and Sentinel-2A satellites in retrieving burn severity levels. Burn severity levels experienced by the Mediterranean forest communities were defined by using two quali-quantitative field-based composite burn indices (FBIs), namely the Composite Burn Index (CBI), its geometrically modified version CBI (GeoCBI), and the dNBR derived from the two medium-resolution multispectral remote sensors. The accuracy of the burn severity map produced by using the dNBR thresholds developed by Key and Benson (2006) was first evaluated. We found very low agreement (0.15 < K < 0.21) between the burn severity class obtained from field-based indices (CBI and GeoCBI) and satellite-derived metrics (dNBR) from both Landsat-8 and Sentinel-2A. Therefore, the most appropriate dNBR thresholds were rebuilt by analyzing the relationships between two field-based (CBI and GeoCBI) and dNBR from Landsat-8 and Sentinel-2A. By regressing alternatively FBIs and dNBRs, a slightly stronger relationship between GeoCBI and dNBR metrics obtained from the Sentinel-2A remote sensor (R2 = 0.69) was found. The regressed dNBR thresholds showed moderately high classification accuracy (K = 0.77, OA = 83%) for Sentinel-2A, suggesting the appropriateness of dNBR-Sentinel 2A in assessing mixed-severity Mediterranean wildfires. Our results suggest that there is no single set of dNBR thresholds that are appropriate for all burnt biomes, especially for the low levels of burn severity, as biotic factors could affect satellite observations.

Do Wildfires Cause Changes in Soil Quality in the Short Term?

“…Meteorological data from September 2016 to September 2018 are reported in Figure A1 . After fire, at 12 field points ( Figure 1 ) inside a high intensity (level 4) burnt area [ 28 ], five subsamples of surface soil (0–10 cm) were collected, after litter removal, and mixed together in order to obtain a homogeneous sample. Before sampling, the litter was removed in order to study only the surface soil system, where the biological activity is higher [ 29 ], and also to allow the comparison with the results of the campaign of 2016.…”

Performance Analysis of Deep Convolutional Autoencoders with Different Patch Sizes for Change Detection from Burnt Areas

“…We recommend that future studies investigate more uses of current Deep Learning techniques to provide better solutions for the detection and mitigation of these threats. In addition, certain spectral vegetation and burn indexes that have been shown to possibly improve the detection of burnt land [76,77] were not used in this study and could be investigated in future works. A few other suggestions for further studies of the theme arose from certain limitations found in this study.…”

Combined Effects of Wildfire and Vegetation Cover Type on Volcanic Soil (Functions and Properties) in a Mediterranean Region: Comparison of Two Soil Quality Indices

“…), originated from the 79 A.D. eruption. In June 2017, the Vesuvius National Park was affected by a severe fire [ 14 ] that caused the loss of more than 50% (approximately 3000 ha) of the existing plant cover [ 17 ]. Before the fire, the different areas inside the National Park were dominated by holm oaks ( Quercus ilex L.), pines ( Pinus pinea L., Pinus nigra L.), herbs and shrubs (such as Myrtus communis L., Laurus nobilis L., Viburnum tinus L., Cistus sp., Ginesta sp.)…”