Yukio Teraoka, Tsuyoshi Kajisa, Daisuke Higashi, Takashi Sonoda, Kiyomizu Maeda and Kunihiko Hata: Natural drying of standing Sugi trees by girdling treatment for fuel chip production. Jpn. J. For. Plann. 57: 37～44, 2024 Experiments to produce dried fuel chips by natural drying of standing Sugi (Cryptomeria japonica) trees using girdling treatment were performed. Ten trees were sampled from a 48-year-old stand for girdling that had been dried for 16 months, and five control trees without treatment were cut and chipped for each tree. The chip moisture contents (wet-based) were measured by the oven drying method and compared. Thus, nine girdling-treated trees had died from 3.5 to 13.5 months and could produce dried fuel chips with less than 42% moisture content. On the other hand, one girdling-treated tree had survived for 16 months, and the control trees showed high moisture content. Significant differences were observed between the moisture contents of died and survived trees by ANOVA. These results supported the feasibility of producing dried fuel chips from dead trees using girdling, which could be used for wood chip boilers.

Shugo Inoue, Tetsuji Ota and Nobuya Mizoue: Searching for the optimal acquisition month for bamboo area detection using satellite constellation images. Jpn. J. For. Plann. 57: 45～51, 2024 We verified the optimal month of data acquisition for detecting bamboo areas from satellite remote sensing data. The study area was the area around the former Tachibana Village in Fukuoka Prefecture, and a total of 11 PlanetScope data were obtained from January to December 2022. Machine learning models were applied to each of the 11 satellite data sets to classify them into two classes: bamboo area and non-bamboo area. Classification accuracy was then compared. The overall accuracy was highest in June (91.2%) and lowest in April (74.6%). The overall accuracy was low in January, gradually increased, and then peaked in May and June, followed by a decrease. In the bamboo area detection using data acquired in June, the red band had the highest importance, and the vegetation indices using the red band, green, and near-infrared band also had high importance. We concluded that data acquired in May-June by satellites with red, green, and near-infrared bands should be used to detect bamboo forests.