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Detection and characterisation of the forest road network using LiDAR

使用 LiDAR 检测和表征森林道路网络

基本信息

批准号：
556210-2020
负责人：
Achim, Alexis
金额：
$ 3.44万
依托单位：
Université Laval
依托单位国家：
加拿大
项目类别：
Alliance Grants
财政年份：
2020
资助国家：
加拿大
起止时间：
2020-01-01 至 2021-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=706189
关键词：
Detection characterisation forest road network

项目摘要

Forest roads are an essential prerequisite for sustainable forest management providing access for silvicultural operations, such as planting, stand tending, and harvesting, as well as being critical for other activities such as fire suppression and access. Roads are also used to provide access for recreational activities including camping, hiking or hunting. Critical to the management of the roads network is maintaining up-to-date and accurate information on both the quantity and the quality of road surfaces within a forest estate. The aims of this project are first to develop and validate new approaches to accurately locate forest roads across Quebec, and second to predict the condition (or attributes) of forest roads. For location will take advantage of the high spatial accuracy and province-wide coverage of the most recent airborne laser scanning (ALS) data acquisition in Quebec. Road attribute predictions and temporal updates will be derived from a mixture of satellite imagery analysis, participatory GIS and deep learning. Our research will be conducted in four core areas, covering a range of environmental conditions affecting road development and condition across Quebec. The team is highly committed to advancing the use of ALS Canada. The updated road layers will be made available on an open-access platform (https://www.foretouverte.gouv.qc.ca/) supported by the Quebec Ministry of Forests, Wildlife and Parks, which will enable interested users to gain direct access to the research outcomes.

森林道路是可持续森林管理的一个基本先决条件，为植树、林分抚育和采伐等造林作业提供通道，对灭火和通道等其他活动也至关重要。道路也被用来提供休闲活动的通道，包括露营，徒步旅行或狩猎。对公路网管理至关重要的是保持关于森林区内公路路面数量和质量的最新和准确的信息。该项目的目的是首先开发和验证新的方法，以准确地定位整个魁北克的森林道路，其次预测森林道路的条件（或属性）。定位将利用魁北克最新机载激光扫描（ALS）数据采集的高空间精度和全省范围。道路属性预测和时间更新将来自卫星图像分析，参与式GIS和深度学习的混合。我们的研究将在四个核心领域进行，涵盖了一系列影响魁北克道路发展和状况的环境条件。该团队高度致力于推进ALS加拿大的使用。更新后的道路图层将在魁北克森林、野生动物和公园部支持的开放获取平台（https：//www.foretouvert.gouv.qc.ca/）上提供，这将使感兴趣的用户能够直接获取研究成果。