Program 4. Advanced the Scientific Management System for Forest Disasters and Forest Pest

Forest disaster risk and disaster vulnerability due to climate change are increasing. In order to realize a safe society from forest disasters, the National Institute of Forest Science has established technologies to predict and reduce the occurrence of forest fires, landslides, forest pests, and is developing advanced disaster management programs. Through this, we intend to protect the safety of the people and protect the forest from forest disasters by implementing a comprehensive management system for forest fires, landslides, and forest pests.

□ Major outcomes
4-1. Development of technology for advanced wildfire prediction and damage reduction
·In a study on the establishment of a mid- to long-term forest fire risk forecast system based on climate change scenarios, the accuracy of forest fire risk prediction has improved to 59% for the long-term forecast (1 month) and 93% for the medium-term forecast (1 week), enabling early warning of large forest fires 7 days in advance.
·3D fuel shape analysis and fuel presentation techniques were developed using LiDAR and drone images, and a Korean forest fire behavior simulator (K-WFDS) was developed by upgrading the individual object fuel extraction techniques using image information.
·Reducing forest fire damage, an automatic calculation program for the forest fire vulnerability index of facilities was established, and new technology for firefighting in response to forest fires at night and inaccessible areas was also fully studied.

4-2 Development of technology to prevent earth and sand disasters
·As long as piloting AI technology applicability analysis and risk maps to actualise the risk map of mountainous soil disasters, all machine learning techniques present an accuracy of more than 80%, and RF (98%) and XGB (98%) show the highest prediction accuracy, enabling probability-based landslide risk rating (5th grade).
·A standard DB construction plan was derived for the construction of landslide DB by data types, such as NDMS, spatial information, and field survey, and three types of landslide site conditions such as damage, measure, and restoration were built in the pilot system.
·In order to investigate the soil movement mechanism in accordance with the characteristics of a mountain torrent, a field survey report was studied for the selection of optimal sites and a site for a monitoring system was created.

4-3 Prediction of major forest diseases and insect pests and development integrated pest management strategies
·The de novo assembly of pine wood nematode (Bursaphelenchus xylophilus, 74Mb) and vector insect (Monochamus alternatus, 804Mb) genome was completed, and the basic data for scientifically epidemiological investigating the spread routes of pine wilt disease was established.
·By proving that pine wood nematodes and vector insects are distributed regardless of the appearance characteristics of dead trees, the criteria for selecting trees to be controlled to improve the quality of control were redefined and reflected in the control guidelines. For supporting a tree care, 7 types of rust diseases and 6 types of leaf-drying diseases with a high frequency of occurrence in trees in major living areas were identified and first described. The 30 pest species of fruit trees such as chestnut, walnut, jujube, and hazel trees that account for 91% of the domestic forest products production were identified, and 6 kinds of pesticides were registered.
·In addition, 50 species of pests were described and 20 kinds of pesticides were registered on medicinal plants. A database of pests that may occur during post-harvest management (drying and storage) was established, produced, and distributed as a forest science newsletter.