应用开源离散全球网格系统

A. Kmoch, O. Matsibora, I. Vasilyev, E. Uuemaa
{"title":"应用开源离散全球网格系统","authors":"A. Kmoch, O. Matsibora, I. Vasilyev, E. Uuemaa","doi":"10.5194/agile-giss-3-41-2022","DOIUrl":null,"url":null,"abstract":"Abstract. Discrete Global Grid Systems (DGGS) are spatial reference systems that use a hierarchical tessellation of cells to partition and address the globe and provide alternative spatial data format and indexing methods as compared to traditional vector and raster spatial data. In order to effectively use DGGS, functional software needs to be available and data needs to be indexed into a DGGS. We compare the software APIs of the 5 main open-source DGGS implementations – Uber H3, Google S2, rHEALPix by Landcare Research New Zealand, RiskAware OpenEAGGR, and DGGRID by Southern Oregon University – and present exemplary workflows for converting spatial and vector and raster datasets into DGGS-indexed format. We summarize, that Uber H3 and Google S2 provide more mature software library functionalities and DGGRID provides excellent functionality to construct grids with desired geometric properties and to load point data but does not provide functions for traversal and navigation within a grid after its construction.\n","PeriodicalId":116168,"journal":{"name":"AGILE: GIScience Series","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Applied open-source Discrete Global Grid Systems\",\"authors\":\"A. Kmoch, O. Matsibora, I. Vasilyev, E. Uuemaa\",\"doi\":\"10.5194/agile-giss-3-41-2022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Discrete Global Grid Systems (DGGS) are spatial reference systems that use a hierarchical tessellation of cells to partition and address the globe and provide alternative spatial data format and indexing methods as compared to traditional vector and raster spatial data. In order to effectively use DGGS, functional software needs to be available and data needs to be indexed into a DGGS. We compare the software APIs of the 5 main open-source DGGS implementations – Uber H3, Google S2, rHEALPix by Landcare Research New Zealand, RiskAware OpenEAGGR, and DGGRID by Southern Oregon University – and present exemplary workflows for converting spatial and vector and raster datasets into DGGS-indexed format. We summarize, that Uber H3 and Google S2 provide more mature software library functionalities and DGGRID provides excellent functionality to construct grids with desired geometric properties and to load point data but does not provide functions for traversal and navigation within a grid after its construction.\\n\",\"PeriodicalId\":116168,\"journal\":{\"name\":\"AGILE: GIScience Series\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AGILE: GIScience Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/agile-giss-3-41-2022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AGILE: GIScience Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/agile-giss-3-41-2022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

摘要离散全球网格系统(DGGS)是空间参考系统,它使用单元的分层细分来划分和定位全球,并提供与传统矢量和栅格空间数据相比的替代空间数据格式和索引方法。为了有效地使用DGGS,需要有功能性的软件,并且需要将数据索引到DGGS中。我们比较了5个主要开源DGGS实现的软件api——Uber H3、Google S2、新西兰Landcare Research的rHEALPix、RiskAware OpenEAGGR和南俄勒冈大学的DGGRID——并给出了将空间、矢量和栅格数据集转换为DGGS索引格式的示例工作流程。综上所述,Uber H3和Google S2提供了更成熟的软件库功能,DGGRID在构建具有所需几何属性的网格和加载点数据方面提供了出色的功能,但在网格构建后没有提供网格内部的遍历和导航功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Applied open-source Discrete Global Grid Systems
Abstract. Discrete Global Grid Systems (DGGS) are spatial reference systems that use a hierarchical tessellation of cells to partition and address the globe and provide alternative spatial data format and indexing methods as compared to traditional vector and raster spatial data. In order to effectively use DGGS, functional software needs to be available and data needs to be indexed into a DGGS. We compare the software APIs of the 5 main open-source DGGS implementations – Uber H3, Google S2, rHEALPix by Landcare Research New Zealand, RiskAware OpenEAGGR, and DGGRID by Southern Oregon University – and present exemplary workflows for converting spatial and vector and raster datasets into DGGS-indexed format. We summarize, that Uber H3 and Google S2 provide more mature software library functionalities and DGGRID provides excellent functionality to construct grids with desired geometric properties and to load point data but does not provide functions for traversal and navigation within a grid after its construction.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Is it safe to be attractive? Disentangling the influence of streetscape features on the perceived safety and attractiveness of city streets Satellite parking: a new method for measuring parking occupancy Semantic complexity of geographic questions - A comparison in terms of conceptual transformations of answers Development of an inclusive Mapping Application in a Co-Design Process Visualizing of the below-ground water network infrastructure
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1