Professor Masato Kato of Shinshu University (Forestry Resources Research Division, Mountain Science Institute) has been commissioned by JAXA (Japan Aerospace Exploration Agency) to conduct research in the forestry field using advanced optical satellite sensors.There are almost no demonstration cases using artificial satellites in the forestry field, and if the investigation using inexpensive domestic artificial satellites begins in earnest, the cost will be reduced and it will be a precedent case to be used by local governments nationwide.
The earth observation satellite scheduled to be launched in 32 is equipped with a large, high-performance sensor.It will continuously observe the land area on a global scale and will be used for disaster prevention / disaster countermeasures and environmental conservation.Using this observation band, the technology developed by Professor Kato will be used to evaluate the usefulness of tree species classification and pine worm damage classification in collaboration with Nagano Prefecture, Matsumoto City, Ina City, and Kita Shinshu Forestry Association. conduct.
In Nagano prefecture, the damage caused by pine worms has increased explosively in recent years, and the current situation is that there are many omissions in the visual observation of the damage situation by human wave tactics.Matsumoto City and Ina City are expecting precise damage classification for each single tree by artificial satellite in order to cut down infected trees at the forefront of damage and suppress the spread of pine wilt.The satellite data before and after the damage of the pine worm are compared, and healthy trees, infected trees, and dead trees are classified.
The sensor is also effective for grasping the composition of broad-leaved trees and coniferous trees in the forest and for utilizing the forest resources of sugi, cypress, and larch, and will be implemented by the Kita Shinshu Forestry Association (Nakano City).The canopy of each single tree is extracted from the analysis of satellite images, and forest information such as tree species classification, number of trees, tree height, diameter at breast height, and volume is analyzed.
