Recent climate change-driven warming and prolonged drought have reduced fuel moisture in forests, increasing the frequency and severity of wildfires. In particular, crown fires have become more frequent, highlighting the importance of quantifying crown fuel characteristics. However, studies on the crown fuel biomass of Pinus densiflora in South Korea remain limited. This study aimed to quantify crown fuel biomass and develop a diameter at breast height (DBH)-based allometric model across major P. densiflora distribution areas. A total of 67 sample trees were destructively sampled across seven regions. Crown fuel components were classified into needles and branch diameter classes, and their dry biomass was measured. A log-transformed allometric model was developed, and its reliability was evaluated using correction factors, confidence intervals, and prediction intervals. Branches accounted for approximately 78% of total crown fuel, while needles accounted for approximately 22%. The model demonstrated high explanatory power, with $R_{adj}^2$ ranging from 0.783 to 0.945. Combustible fuels (≤1.0 cm) accounted for approximately 45% of total crown fuel. The developed model can be used as an input for wildfire spread prediction and provides a basis for crown fire risk assessment and fuel mapping.

Thermal stress induces physiological changes in forest tree seedlings, and multispectral imaging offers a non-destructive approach for monitoring associated changes in spectral reflectance. This study evaluated the responses of Pinus densiflora seedlings to sustained high-temperature stress and short-term extreme thermal exposure using multispectral vegetation indices, photosynthetic pigments, and soil environmental measurements. Seedlings were subjected to four thermal treatments: 38 °C at 60% relative humidity (RH), 38 °C at 40% RH, 45 °C at 60% RH, and short-term exposure to 90 °C. Spectral responses were assessed using NDVI, GNDVI, NDRE, and CIRE. Temporal changes in vegetation indices and soil variables were evaluated using linear mixed-effects models, while pigment contents were analyzed using linear models. NDVI and GNDVI generally declined under sustained heat exposure, whereas NDRE remained comparatively stable and CIRE exhibited treatment-dependent responses. Photosynthetic pigment contents also varied among treatments, with total chlorophyll increasing under 38 °C at 60% RH but decreasing under 38 °C at 40% RH, while carotenoid contents increased under both conditions. Soil temperature and moisture changed significantly over time under all treatments (all $p<0.001$). Soil moisture reached a recorded value of 0% under both sustained 38 °C treatments, whereas relative reductions of 88.7% and 37.0% were observed under the 45 °C and short-term 90 °C treatments, respectively. Time-adjusted association analyses identified only one statistically significant relationship after false discovery rate correction, between GNDVI and soil temperature under 38 °C at 40% RH (FDR-adjusted p = 0.0499). Nevertheless, the observed temporal changes in vegetation indices indicate that multispectral imaging can capture spectral responses of seedlings to thermal stress, although the associations between vegetation indices and physiological or environmental variables were limited.