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首页> 外文期刊>Journal of Korean Forest Society >Use of Unmanned Aerial Vehicle for Forecasting Pine Wood Nematode in Boundary Area: A Case Study of Sejong Metropolitan Autonomous City
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Use of Unmanned Aerial Vehicle for Forecasting Pine Wood Nematode in Boundary Area: A Case Study of Sejong Metropolitan Autonomous City

机译：无人驾驶飞行器在边界地区预测松木线虫的预测 - 以Sejong Metropolitan自治区为例

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摘要

This study was conducted for preliminary survey and management support for Pine Wood Nematode (PWN) suppression. We took areal photographs of 6 areas for a total of 2,284 ha during 2 weeks period from 15/02/2016, and produced 6 ortho-images with a high resolution of 12 cm GSD (Ground Sample Distance). Initially we classified 423 trees suspected for PWN infection based on the ortho-images. However, low accuracy was observed due to the problems of seasonal characteristics of aerial photographing and variation of forest stands. Therefore, we narrowed down 231 trees out of the 423 trees based on the initial classification, snap photos, and flight information; produced thematic maps; conducted field survey using GNSS; and detected 23 trees for PWN infection that was confirmed by ground sampling and laboratory analysis. The infected trees consisted of 14 broad-leaf trees, 5 pine trees (2 Pinus rigida), and 4 other conifers, showing PWN infection occurred regardless of tree species. It took 6 days for 2.3men from to start taking areal photos using UAV (Unmanned Aerial Vehicle) to finish detecting PNW (Pine Wood Nematode) infected tress for over 2,200 ha, indicating relatively high efficacy.
机译：本研究旨在为抑制松材线虫（PWN）提供初步调查和管理支持。从2016年2月15日起的两周内，我们拍摄了6个面积为2284公顷的区域照片，并制作了6张高分辨率的正射影像，分辨率为12厘米GSD（地面样本距离）。最初，我们根据正射影像对423棵疑似PWN感染的树木进行了分类。然而，由于航空摄影的季节特征和林分变化的问题，观测到的精度较低。因此，根据初步分类、快照和航班信息，我们缩小了423棵树中的231棵；制作专题地图；利用全球导航卫星系统进行实地调查；通过地面采样和实验室分析，检测到23棵树感染了PWN。受感染的树木包括14棵阔叶树、5棵松树（2棵松树）和4棵其他针叶树，表明无论树种如何，都会发生PWN感染。从开始使用无人机（UAV）拍摄区域照片到完成检测超过2200公顷受PNW（松材线虫）感染的树木，花了2.3人6天时间，显示出相对较高的效率。

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