用于Jupyteo IDE地球观测处理工具的Python库,支持与QGIS系统在数据科学中使用的互操作性

M. Bednarczyk
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引用次数: 0

摘要

本文描述了JupyQgis——一个新的Python库,用于Jupyteo IDE,支持与QGIS系统的互操作性。Jupyteo是一个用于地球观测数据处理的在线集成开发环境,可在云平台上使用。它的目标是遥感专家、科学家和用户,他们可以通过重用嵌入式开源工具、WPS接口和现有笔记本来开发Jupyter笔记本。近年来,数据科学方法越来越受欢迎,成为许多组织关注的焦点。由于数据驱动的解决方案,许多科学学科正面临着重大变革。在大地测量学、环境科学和地球科学领域尤其如此,这些领域使用的是大型数据集,如地球观测卫星数据(EO数据)和地理信息系统数据。以前使用Jupyteo的经验,无论是这个平台的用户还是它的创建者,都表明需要用GIS分析工具来补充它的功能。本研究分析了将QGIS系统的功能与Jupyteo平台的功能结合在一个工具中的最有效方法。我们发现,最合适的解决方案是创建一个自定义库,为两种环境之间的协作提供API。生成的库使工作更容易,并简化了所创建的Python脚本的源代码。开发的解决方案的功能用一个测试用例来说明。
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A Python Library for the Jupyteo IDE Earth Observation Processing Tool Enabling Interoperability with the QGIS System for Use in Data Science
This paper describes JupyQgis – a new Python library for Jupyteo IDE enabling interoperability with the QGIS system. Jupyteo is an online integrated development environment for earth observation data processing and is available on a cloud platform. It is targeted at remote sensing experts, scientists and users who can develop the Jupyter notebook by reusing embedded open-source tools, WPS interfaces and existing notebooks. In recent years, there has been an increasing popularity of data science methods that have become the focus of many organizations. Many scientific disciplines are facing a significant transformation due to data-driven solutions. This is especially true of geodesy, environmental sciences, and Earth sciences, where large data sets, such as Earth observation satellite data (EO data) and GIS data are used. The previous experience in using Jupyteo, both among the users of this platform and its creators, indicates the need to supplement its functionality with GIS analytical tools. This study analyzed the most efficient way to combine the functionality of the QGIS system with the functionality of the Jupyteo platform in one tool. It was found that the most suitable solution is to create a custom library providing an API for collaboration between both environments. The resulting library makes the work much easier and simplifies the source code of the created Python scripts. The functionality of the developed solution was illustrated with a test use case.
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来源期刊
Geomatics and Environmental Engineering
Geomatics and Environmental Engineering Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
2.30
自引率
0.00%
发文量
27
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