Shifting cultivation remains a primary farming system in Myanmar’s mountainous regions. However, population growth and economic pressures have disrupted its traditional balance. This study aimed to clarify historical land-use patterns and evaluate vegetation recovery in Lailenpi by integrating field surveys with multitemporal Sentinel-2 imagery from 2019 to 2025. We identified cultivation plots using NDVI differences and quantified recovery trajectories with a Bayesian hierarchical nonlinear model. Results confirmed that a systematic eight-year rotational cycle was maintained. However, the total cultivated area expanded from 0.93% to 3.13%, shifting toward steeper terrain. Bayesian modeling showed that canopy greenness recovered within 24 to 36 months. Despite this resilience, the shift to rugged terrain suggested mounting land-use pressure and soil degradation risks. These findings highlight the importance of combining field surveys with high-resolution monitoring to ensure the long-term ecological sustainability of tropical mountain regions.

The soil temperature controls soil biological activity, carbon and nutrient cycling, and plant regeneration in mountain forests, so its spatial distribution is needed for the sustainable management of forest soils under a changing climate; however, high-elevation monitoring is costly and scarce. This study evaluated whether the daily mean near-surface (2–7 cm) soil temperature in the snow-free season can be predicted from the air temperature alone, enabling low-cost monitoring from freely available data. A random forest model driven by the current and lagged (0–7 d) daily mean air temperature was trained on snow-free season (May–November) observations from 15 measurement points (11 in a single stand) at five forested sites in Nagano Prefecture, Central Japan (914–2082 m, 2017–2025). The pooled grouped cross-validation RMSE was 1.01–1.05 °C (R² = 0.955–0.958), and the site-level RMSE was 1.07–1.53 °C when whole sites were withheld. Replacing the observed air temperature with nationwide 1 km gridded data (Agro-Meteorological Grid Square Data) increased the cross-site RMSE only from 1.05 to 1.18 °C. Lapse rate adjustment barely improved the accuracy, indicating that elevation also represents snow, canopy, and radiation effects. Demonstration maps of the snow-free season produced with a 10 m digital elevation model remain unvalidated away from the monitoring points. The approach could provide a resource-efficient basis for soil thermal monitoring to support sustainable forest management and climate change adaptation in mountain regions.