Abstract
<p>Severely dry climate plays an important role in the occurrence of wildfires in Thailand. Soil water deficits increase dry conditions, resulting in more intense and longer burning wildfires. The temperature vegetation dryness index (TVDI) and the normalized difference drought index (NDDI) were used to estimate soil moisture during the dry season to explore its use for wildfire risk assessment. The results reveal that the normalized difference wet index (NDWI) and land surface temperature (LST) can be used for TVDI calculation. Scatter plots of both NDWI/LST and the normalized difference vegetation index (NDVI)/LST exhibit the triangular shape typical for the theoretical TVDI. However, the NDWI is more significantly correlated to LST than the NDVI. Linear regression analysis, carried out to extract the maximum and minimum LSTs (LST<sub>max</sub>, LST<sub>min</sub>), indicate that LST<sub>max </sub>andLST<sub>min</sub> delineated by the NDWI better fulfill the collinearity requirement than those defined by the NDVI. Accordingly, the NDWI-LST relationship is better suited to calculate the TVDI. This modified index, called TVDI<sub>NDWI-LST</sub>, was applied together with the NDDI to establish a regression model for soil moisture estimates. The soil moisture model fulfills statistical requirements by achieving 76.65% consistency with the actual soil moisture and estimated soil moisture generated by our model. The relationship between soil moisture estimated from our model and leaf fuel moisture indicates that soil moisture can be used as a complementary dataset to assess wildfire risk, because soil moisture and fuel moisture content (FMC) show the same or similar behavior under dry conditions. <strong></strong></p>
Highlights
Dry climate plays an important role in the occurrence of wildfires
The main goal of this study was to estimate the spatial distribution of soil moisture using temperature vegetation dryness index (TVDI) and normalized difference drought index (NDDI) derived from Landsat 8 OLI/TIRS data for wildfire risk assessment
Results reveal that an accurate estimate of TVDI can be obtained from the relationship between normalized difference wet index (NDWI), which is more significantly correlated to land surface temperature (LST) than the normalized difference vegetation index (NDVI), and LST
Summary
Dry climate plays an important role in the occurrence of wildfires. In Thailand, forest wildfires are prevalent during the dry season and are especially damaging because of forest loss and degradation. The number of wildfires in Thai conserved forest areas were 4207, 4982, and 6685 in 2014, 2015, and 2016, respectively (Forest Fire Control Division, 2016) These numbers indicate that the number of wildfires appears to be increasing because Thailand has been experiencing longer dry seasons and under dry conditions, wildfires can ignite as fuel sources are readily available. Fuel availability, which drives wildfire occurrences and directly affects wildfire behavior, depends on fuel characteristics, which are fuel load (influencing fire intensity) and fuel moisture content (influencing both fire ignition and spread) It appears that recurring dry seasons foster fuel availability and reduce fuel moisture content, resulting in potentially more damaging high-intensity fires, which may spread rapidly during extremely dry conditions
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