This study investigated the degree of physical and mental recovery and improvement in sleep, happiness, and work motivation, as well as subsequent behavioral changes, after a two day and one night stay in Fujinomiya City, Shizuoka Prefecture, December 4 and 5, 2021, among participants of a Shinrin-yoku health tour held in Inokashira-ku, Fujinomiya City, Shizuoka, Japan. Twelve participants experienced activities such as E-biking, aroma water making, sunrise experience the sunrise on Mt. Fuji. On the evening of the first day, the participants attended a health seminar given by a medical doctor, where they learned about the concept of Optimum Health and the methodology to change their behavior. In the afternoon of the second day, participants reviewed both days and made plans for future behavior change. On the other hand, in order to measure the participants' physical and mental health before, during, and after their stay, a smartwatch was used for physiological indicators (heart rate, fluctuations in autonomic nervous system activity, and quantity and quality of sleep) and a smartphone was used for psychological indicators (mood, subjective restorativeness, subjective sleepiness, happiness, and work motivation). The results of the analysis showed that the participants' physical and mental health improved during their stay and after returning home compared to before their stay, and some indicators remained statistically significant effects for as long as two months after their return. From subsequent follow-up studies, it was inferred that the health seminars, photographs, and homemade souvenirs given during the tour seemed to contribute to the persistence of the physiological and psychological effects.

Since the start of the feed-in tariff scheme for renewable energy in 2012, the amount of unutilized-wood biomass such as logging residues (“unused wood”) used as fuel for woody biomass power plants has increased to 8.82 million m³ in 2020. However, the demand for unused wood is expected to decrease after 20 years of new operation, because it will be difficult to continue the business of biomass power generation using unused wood as the main fuel. In this study, the possibility of co-firing of unused wood in municipal waste-to-energy plants was examined from the viewpoints of legal system, technology, and business feasibility as one of new ways to utilize unused wood, and the potential of co-firing and its effect on local economy and climate change were measured. The results showed that the legal system allows co-firing of up to 30％ of the amount of waste, including auxiliary combustion materials, and that the technology allows co-firing of about 30％ of the amount of waste. In terms of business feasibility, if the procurement price of unused wood chip is 7 yen/kg, it is possible to co-fire 2.13 million m³ in Japan while ensuring business feasibility, which can be expected to generate 26.8 billion yen/year in regional economic benefits and 720,000 t-CO₂/year in climate change countermeasures if coal-fired power generation is replaced.

Mapping and monitoring of tree seedlings are crucial tasks in silvicultural management. Unmanned aerial vehicles (UAVs), in recent years, have been used as a cost-effective technique to capture high-resolution images. However, the method is still labor-intensive and time-consuming if you use with manual monitoring techniques. For continuous utilization of UAV images in silvicultural management, novel automated monitoring methods are required. This study investigated the potential application of automatic tree seedling detection method based on deep-learning (DL) by comparing the accuracy between images acquired in different seasons. The results showed that high seedlings detection accuracy of about 90％ can be achieved with the DL-based method. Moreover, as automated methods are easily influenced by weed growth, a decrease in the number of detected tree seedlings and an increase in the number of misdetections were observed during seasons of weed growth, such as summer and autumn. These results suggested that aerial images should be obtained during unfavorable weedy growing conditions to enhance the accuracy of automated methods.