# Remote Sensing of Forest Burnt Area, Burn Severity, and Post-Fire Recovery: A Review
## 4 Results and Discussions  
### BA and BS Estimates  
#### 4.1.1 Spectral Indices and Mapping Techniques  
The remote sensing of forest BA mapping has a long history, starting in the early 1970s, and during 2000-2020, it is still an active research topic employing advanced techniques that integrate geo-statistics, as well as object-oriented and machine learning methods [46]. During the last two decades, a wide range of products have been developed and applied in BA mapping at the global, regional, and local scales [47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64]. A reduction in the visible-to-near-infrared reflectance of vegetation cover and an increase in the short and middle infrared surface reflectance of most satellite sensors that occur following a wildfire can facilitate the identification of BA patterns [65, 66, 67, 42, 68]. Among the commonly used optical features, vegetation indices (VI) play a major role in the studies of remote sensing of forest BA and BS. During two decades, the most frequently used VI compared to other indices was the normalized difference vegetation index (NDVI) (128 studies, 23.4%), followed by the delta Normalized Burn Ratio (dNBR) (81 studies, 14.8%), Normalized Burn Ratio (NBR) (77 studies, 14.1%), and the relative differenced Normalized Burn Ratio (RdNBR) (32 studies, 5.8%) (Table 2). A total of 34 studies (6.2%) employed the composite burn index (CBI) to correlate remote sensing data with field characteristics of burn severity observed after wildfire [45]. A number of studies have observed the enhanced vegetation index (21 cases, 3.8%), the burn area index (BAI) (18 cases, 3.3%), the normalized difference water index (NDWI) (17 cases, 3.1%), the mid-infrared burnt index (MIRBI) (12 cases, 2.2%), and the global environmental monitoring index (GEMI) (12 cases, 2.2%). In order to minimise soil background reflectance, the soil-adjusted vegetation index (SAVI) (13 cases, 2.4%), modified SAVI (MSAVI) (12 cases, 2.2%) and the char soil index (CSI) (6 cases, 1.1%) were also applied. \begin{table}
\begin{tabular}{l c c c} \hline
**Tree Species** & **Number of Studies** & **Tree Species** & **Number of Studies** \\ \hline Ponderosa pine (_Pinus ponderosa_) & 26 & Siberian larch (_Larix shiprica_) & 9 \\ Maritime pine (_Pinus pinster_) & 24 & Dahurian Larch (_Larix spmelini_) & 7 \\ Black pine (_Pinus nigra_) & 19 & Evergreen oak (_Quercus lex_) & 18 \\ Scots pine (_Pinus sylesstris_) & 15 & Cork oak (_Quercus suber_) & 10 \\ Aleppo Pine (_Pinus halepensis_) & 14 & Kermes oak (_Quercus cocifena_) & 8 \\ Lodgepole pine (_Pinus contorta_) & 11 & Pyrenean oak (_Quercus pyrenacia_) & 8 \\ Turkish pine (_Pinus bruttia_) & 5 & Downy oak (_Quercus pubscens_) & 5 \\ Jack pine (_Pinus banksiana_) & 5 & Portuguese oak (_Quercus faginea_) & 4 \\ Jeffrey pine (_Pinus jeffrevi_) & 5 & Douglas fir (_Pseudóstuga menizesii_) & 19 \\ Siberian pine (_Pinus sibrica_) & 4 & Subalpine fir (_Abies lasiocarrua_) & 6 \\ Pitch pine (_Pinus rigida_) & 4 & White fir (_Abies concolor_) & 5 \\ Stone pine (_Pinus pinea_) & 4 & Trembling aspen (_Populus tretmuloides_) & 17 \\ Sugar pine (_Pinus Lambertiana_) & 4 & Common aspen (_Populus tretmula_) & 6 \\ Longleaf pine (_Pinus palustris_) & 4 & Siberian silver birch (_Betula Platynphylla_) & 6 \\ Black spruce (_Picea Mariana_) & 16 & European white birch (_Betula pendula_) & 5 \\ White spruce (_Picea glauca_) & 12 & American white birch (_Betula papruifera_) & 5 \\ Siberian spruce (_Picea obovata_) & 4 & Blue gum (_Eucalyptus globulus_) & 4 \\ Engelmann spruce (_Picau euglemmanti_) & 5 & Darwin stringybark (_Eucalyptus tetrodenta_) & 4 \\ \hline \end{tabular}
\end{table} 
Table 1: Tree species on the burnt sites described in more than four cases (156 articles in total). In early 2000, the use of AVHRR, MODIS, IRS, SPOT/HRVIR, and Landsat to detect hotspots based on dNDVI images has been widely applied to estimate BA in many studies [69; 80; 81; 82; 83].