大型河流中水生植被的无人机辅助监测——多瑙河中部(塞尔维亚)

IF 0.9 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES Carpathian Journal of Earth and Environmental Sciences Pub Date : 2023-06-30 DOI:10.26471/cjees/2023/018/261
Maja Novković, Dušanka Cvijanović, Minučer Mesaroš, D. Pavić, N. Drešković, Đurađ Milošević, Ana A. Anđelković, Bojan Damnjanović, S. Radulović
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引用次数: 1

摘要

无人机技术为各种环境监测领域提供了时间和成本效益的框架。它还提高了数据分辨率,并为观测到的物体和现象提供了新的见解,特别是在难以进入和复杂的水生栖息地监测中。本研究的目的是开发基于无人机采集和基于gis的图像处理指南,用于大型温带河流水生植物的检测和监测。根据欧洲标准CEN EN -14184:2014,水生大型植物的评估应采用样条法进行。大型河流,如多瑙河,是一个例外,应该使用1公里的横断面进行评估。因此,采用传统的野外方法和新型无人机技术同时调查了塞尔维亚多瑙河中部的七个样带。使用固定翼无人机携带的RGB和多光谱相机获取无人机图像。利用基于对象的图像分析(OBIA)对图像进行处理和正形图分类,创建河流断面的数字GIS地图。在传统监测方法中,沿样带记录了22种大型植物的相对丰度。利用无人机技术和OBIA方法,根据优势植物类群或植物生命形态特征划分出8个植物类。水生植物与正形植物的区分“几乎完美”,RGB方法的分类精度为96% / 88% / 0.84,多光谱方法的生产者/用户精度/Kappa指数为94% / 97% / 0.95。单个大型植物分类精度在0.5 ~ 1 Kappa之间变化,多光谱成像方法通常更高。虽然分类数据的分辨率较低,但无人机监测提供了必要的大植物分布空间背景和大植物占据的绝对面积。它还提供了关于河流沿岸生境多样性和分布的信息。因此,本研究中描述的无人机辅助监测方法可以有效地整合到JDS等大型河流考察期间的大型植物监测中。
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TOWARDS UAV ASSISTED MONITORING OF AQUATIC VEGETATION WITHIN LARGE RIVERS – THE MIDDLE DANUBE (SERBIA)
UAV technologies provide a time- and cost-efficient framework for a variety of environmental monitoring domains. It also increases data resolution and provides new insights into observed objects and phenomena, especially within the difficult-to-access and complex for monitoring aquatic habitats. The objective of this study was to develop UAV-based acquisition and GIS-based image processing guidelines for aquatic macrophyte detection and monitoring in large temperate rivers. According to the European standard CEN EN -14184:2014, the assessment of aquatic macrophytes should be performed using the transect approach. Large rivers, such as the Danube, represent an exception and should be evaluated using 1km transects. Therefore, seven transects of the Middle Danube in Serbia were simultaneously surveyed using traditional field methods and novel UAV technology. UAV images were acquired using RGB and multispectral cameras carried by a fixed-wing drone. The images were processed and orthomosaics were classified using Object Based Image Analysis (OBIA), to create digital GIS maps of the river transects. During the traditional monitoring approach, the relative abundance of 22 macrophyte species was recorded along the transects. Using the UAV technology and OBIA approach eight macrophyte classes were distinguished based on dominant macrophyte taxa or plant life form traits. Aquatic macrophytes were 'almost perfectly' distinguished from the orthomosaics, achieving a high classification accuracy of 96 % / 88 % / 0.84 for RGB and 94 % / 97 % / 0.95 Producers /Users accuracy/Kappa index for the multispectral approach. Individual macrophyte classes accuracy varied between 0.5 and 1 Kappa and were generally higher for the multispectral imagery approach. Although the resolution of the taxonomic data is lower, UAV monitoring provided the necessary spatial context of macrophytes distribution and absolute area occupied by macrophytes. It also provided information on the diversity and distribution of habitats along the river. Therefore, the UAV-assisted monitoring approach described in this study can be effectively integrated into macrophyte monitoring during large river expeditions such as the JDS.
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来源期刊
CiteScore
2.30
自引率
25.00%
发文量
42
审稿时长
12-24 weeks
期刊介绍: The publishing of CARPATHIAN JOURNAL of EARTH and ENVIRONMENTAL SCIENCES has started in 2006. The regularity of this magazine is biannual. The magazine will publish scientific works, in international purposes, in different areas of research, such as : geology, geography, environmental sciences, the environmental pollution and protection, environmental chemistry and physic, environmental biodegradation, climatic exchanges, fighting against natural disasters, protected areas, soil degradation, water quality, water supplies, sustainable development.
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