QGIS 海岸线变化分析工具 (QSCAT)：QGIS 的快速、开源海岸线变化分析插件

IF 4.8 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software Pub Date : 2024-11-19 DOI:10.1016/j.envsoft.2024.106263

Louis Philippe Facun , Ma. Yvainne Sta Maria , Rodel Ducao , Jamela Jirah Clemente , Ellen Mae Carmelo , Angelo Maon , Ara Rivina Malaya , Floribeth Cuison , Fernando Siringan

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引用次数: 0

摘要

海岸侵蚀对大多数沿海社区构成重大威胁。这就需要更好地了解海岸侵蚀动态，因此，海岸线变化分析（SCA）工具将非常有用。然而，许多可用的工具都需要商业软件和/或更快的计算平台。为了解决这些问题，我们开发了 QGIS 海岸线变化分析工具（QSCAT），这是一个用 Python 构建的新 QGIS 插件。QSCAT 可执行基于断面和基于区域的分析。QSCAT 基于断面的算法以数字海岸线分析系统（DSAS）为蓝本。而基于区域的算法类似于变化多边形方法。同时运行 QSCAT 和 DSAS，结果表明 QSCAT 得出的结果与 DSAS 相同，但总体速度比 DSAS 快 8 倍。QSCAT 可以估算海滩面积损失和侵蚀海岸线长度，从而确定侵蚀热点。这些特点证明了 QSCAT 作为更高效、同样可靠的 SCA 工具的潜力。

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QGIS Shoreline Change Analysis Tool (QSCAT): A fast, open-source shoreline change analysis plugin for QGIS

Coastal erosion poses a significant threat to most coastal communities. This necessitates a better understanding of coastal erosion dynamics, and thus, shoreline change analysis (SCA) tools would be handy. However, many available tools require commercial softwares and/or a faster computing platform. To address these issues, QGIS’ Shoreline Change Analysis Tool (QSCAT), a new QGIS plugin built with Python, was developed. QSCAT can perform transect-based and area-based analyses. The transect-based algorithm of QSCAT was patterned after the Digital Shoreline Analysis System (DSAS). Whereas, the area-based algorithm is similar to the change polygon method. Running QSCAT and DSAS together demonstrated that QSCAT generated the same results as DSAS but its overall speed is 8 times faster than DSAS. QSCAT can estimate beach area loss and length of eroding shorelines, which can identify erosion hotspots. These features attest to QSCAT’s potential as a more efficient and an equally reliable SCA tool.

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来源期刊

Environmental Modelling & Software 工程技术-工程：环境

CiteScore

9.30

自引率

8.20%

发文量

241

审稿时长

60 days

期刊介绍： Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.