The segmetric Package: Metrics for Assessing Segmentation Accuracy for Geospatial Data

IF 2.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS R Journal Pub Date : 2023-08-26 DOI:10.32614/rj-2023-030
Rolf Simoes, Alber Sanchez, Michelle C. A. Picoli, Patrick Meyfroidt
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Abstract

Segmentation methods are a valuable tool for exploring spatial data by identifying objects based on images' features. However, proper segmentation assessment is critical for obtaining high-quality results and running well-tuned segmentation algorithms Usually, various metrics are used to inform different types of errors that dominate the results. We describe a new R package, [segmetric](https://CRAN.R-project.org/package=segmetric), for assessing and analyzing the geospatial segmentation of satellite images. This package unifies code and knowledge spread across different software implementations and research papers to provide a variety of supervised segmentation metrics available in the literature. It also allows users to create their own metrics to evaluate the accuracy of segmented objects based on reference polygons. We hope this package helps to fulfill some of the needs of the R community that works with Earth Observation data.
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分割包:用于评估地理空间数据分割准确性的度量
分割方法是一种有价值的工具,可以根据图像的特征来识别物体,从而探索空间数据。然而,正确的分割评估对于获得高质量的结果和运行优化的分割算法至关重要。通常,使用不同的度量来通知影响结果的不同类型的错误。我们描述了一个新的R包,[segmetric](https://CRAN.R-project.org/package=segmetric),用于评估和分析卫星图像的地理空间分割。这个包统一了代码和知识,分布在不同的软件实现和研究论文中,以提供文献中可用的各种监督分割度量。它还允许用户创建自己的度量来评估基于参考多边形的分割对象的准确性。我们希望这个软件包能够帮助R社区满足使用地球观测数据的部分需求。
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来源期刊
R Journal
R Journal COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍: The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R. The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to: - put their contribution in context, in particular discuss related R functions or packages; - explain the motivation for their contribution; - provide code examples that are reproducible.
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