基于正射影像的植被斑块分析--评估分割质量的新方法

IF 4.2 2区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Remote Sensing Pub Date : 2024-09-09 DOI:10.3390/rs16173344
Witold Maćków, Malwina Bondarewicz, Andrzej Łysko, Paweł Terefenko
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引用次数: 0

摘要

下面的论文将以 Heracleum sosnowskyi Manden 为例,重点评估在特定区域搜索单一物种植物时的图像预测质量。这一过程包括以分割步骤结束的简化分类。由于环境数据的特殊性,如植物出现的大面积区域、种群的显著分区或单个个体的特征,使用标准统计量(如准确度、Jaccard 指数或 Dice 系数)并不能产生可靠的结果,这一点在本研究的后面部分会有所说明。这一问题表明,有必要根据植被斑块检测的独特性,采用一种新的方法来评估预测质量。本研究的主要目的就是提供这样一种指标,并证明其在所讨论的案例中的实用性。我们提出的指标引入了两个新系数 M+ 和 M-,它们分别奖励真阳性区域和惩罚假阳性区域,从而对分割质量进行更细致的评估。该指标的有效性已在不同场景中得到验证,重点是理论植被斑块的空间分布和破碎程度的变化,并将提出的新方法与传统指标进行了比较。结果表明,我们的指标能更灵活、更准确地评估分割质量,尤其是在涉及复杂环境数据的情况下。本研究旨在证明该指标在现实世界植被斑块检测任务中的实用性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orthophoto-Based Vegetation Patch Analyses—A New Approach to Assess Segmentation Quality
The following paper focuses on evaluating the quality of image prediction in the context of searching for plants of a single species, using the example of Heracleum sosnowskyi Manden, in a given area. This process involves a simplified classification that ends with a segmentation step. Because of the particular characteristics of environmental data, such as large areas of plant occurrence, significant partitioning of the population, or characteristics of a single individual, the use of standard statistical measures such as Accuracy, the Jaccard Index, or Dice Coefficient does not produce reliable results, as shown later in this study. This issue demonstrates the need for a new method for assessing the betted prediction quality adapted to the unique characteristics of vegetation patch detection. The main aim of this study is to provide such a metric and demonstrate its usefulness in the cases discussed. Our proposed metric introduces two new coefficients, M+ and M−, which, respectively, reward true positive regions and penalise false positive regions, thus providing a more nuanced assessment of segmentation quality. The effectiveness of this metric has been demonstrated in different scenarios focusing on variations in spatial distribution and fragmentation of theoretical vegetation patches, comparing the proposed new method with traditional metrics. The results indicate that our metric offers a more flexible and accurate assessment of segmentation quality, especially in cases involving complex environmental data. This study aims to demonstrate the usefulness and applicability of the metric in real-world vegetation patch detection tasks.
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来源期刊
Remote Sensing
Remote Sensing REMOTE SENSING-
CiteScore
8.30
自引率
24.00%
发文量
5435
审稿时长
20.66 days
期刊介绍: Remote Sensing (ISSN 2072-4292) publishes regular research papers, reviews, letters and communications covering all aspects of the remote sensing process, from instrument design and signal processing to the retrieval of geophysical parameters and their application in geosciences. Our aim is to encourage scientists to publish experimental, theoretical and computational results in as much detail as possible so that results can be easily reproduced. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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