An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: usingRumex obtusifoliusas a case study

编号 030025501

推送时间 20200907

研究领域 森林经理 

年份 2020 

类型 期刊 

语种 英语

标题 An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: usingRumex obtusifoliusas a case study

来源期刊 EUROPEAN JOURNAL OF REMOTE SENSING

期 第255期

发表时间 20200705

关键词 Weed mapping;  grassland management;  open-source;  unmanned aerial vehicle (UAV);  RGB imagery;  neural network; 

摘要 Weed control is one of the biggest challenges in organic farms or nature reserve areas where mass spraying is prohibited. Recent advancements in remote sensing and airborne technologies provide a fast and efficient means to support environmental monitoring and management, allowing early detection of invasive species. However, in order to perform weed classification, current studies mostly relied on object-based image analysis (OBIA) and proprietary software which required substantial human inputs. This paper proposes an open-source workflow for automated weed mapping using a commercially available unmanned aerial vehicle (UAV). The UAV was flown at a low altitude between 10 m and 20 m, and collected true-colour RGB imagery over a weed-infested nature reserve. The aim of this study is to develop a repeatable and robust system for early weed detection, with minimum human intervention, for classification ofRumex obtusifolius(R. obtusifolius). Preliminary results of the proposed workflow achieved an overall accuracy of 92.1% with an F1 score of 78.7%. The approach also demonstrated the capability to mapR. obtusifoliusin datasets collected at various flight altitudes, camera settings and light conditions. This shows the potential to perform semi- or fully automated early weed detection system in grasslands using UAV-imagery.

服务人员 付贺龙

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