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Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science最新文献

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Interactive mapping and geospatial analysis with Leafmap and Jupyter 交互式制图和地理空间分析与Leafmap和Jupyter
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science Pub Date : 2021-11-02 DOI: 10.1145/3486189.3490015
Qiusheng Wu
{"title":"Interactive mapping and geospatial analysis with Leafmap and Jupyter","authors":"Qiusheng Wu","doi":"10.1145/3486189.3490015","DOIUrl":"https://doi.org/10.1145/3486189.3490015","url":null,"abstract":"Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is built upon several open-source packages, such as ipyleaflet and kepler.gl (for creating interactive maps), WhiteboxTools (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface). Leafmap provides many convenient functions for loading and visualizing geospatial data with only one line of code. Users can also use the interactive user interface to load geospatial data without coding. Anyone with a web browser and Internet connection can use leafmap to perform geospatial analysis and data visualization in the cloud with minimal coding. This workshop will introduce the key features of leafmap for interactive mapping and geospatial analysis in a Jupyter environment. Attendees will learn how to leverage open-source Python packages and free cloud computing platforms for geospatial analysis and data visualization.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
MobilityDB: hands on tutorial on managing and visualizing geospatial trajectories in SQL MobilityDB:在SQL中管理和可视化地理空间轨迹的动手教程
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science Pub Date : 2021-11-02 DOI: 10.1145/3486189.3490016
E. Zimányi, M. Sakr, Mohamed S. Bakli, Maxime Schoemans, Dimitris Tsesmelis, Robin Choquet
{"title":"MobilityDB: hands on tutorial on managing and visualizing geospatial trajectories in SQL","authors":"E. Zimányi, M. Sakr, Mohamed S. Bakli, Maxime Schoemans, Dimitris Tsesmelis, Robin Choquet","doi":"10.1145/3486189.3490016","DOIUrl":"https://doi.org/10.1145/3486189.3490016","url":null,"abstract":"MobilityDB is an open source moving object database. It extends PostgreSQL and PostGIS with types and operations for managing continuous geospatial trajectories. This hand-on tutorial will introduce the attendees to: (1) trajectory data management in MobilityDB, (2) visualization of moving object data in QGIS, and (3) distributed spatiotemporal query processing using MobilityDB. All the tutorial queries will be in SQL.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123792639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A brief introduction to geospatial big data analytics with apache AsterixDB 简要介绍使用apache AsterixDB进行地理空间大数据分析
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science Pub Date : 2021-11-02 DOI: 10.1145/3486189.3490018
Akil Sevim, Mehnaz Tabassum Mahin, Tin Vu, Ian Maxon, A. Eldawy, M. Carey, V. Tsotras
{"title":"A brief introduction to geospatial big data analytics with apache AsterixDB","authors":"Akil Sevim, Mehnaz Tabassum Mahin, Tin Vu, Ian Maxon, A. Eldawy, M. Carey, V. Tsotras","doi":"10.1145/3486189.3490018","DOIUrl":"https://doi.org/10.1145/3486189.3490018","url":null,"abstract":"There is immense potential with spatial data, which is even more significant when combined with temporal or textual features, or both. However, it is expensive to store and analyze spatial data, and it is even more challenging with the combined features due to the additional optimization requirements. There are numerous successful solutions for big spatial data management, but they do not well support non-spatial operations. The options for the systems are even smaller for the open sources systems, and there are not a handful of options that provide good coverage of care about the spatial and non-spatial operations. This tutorial introduces Apache AsterixDB, a scalable open-source Big Data Management System, which supports standard vector spatial data types as well as non-spatial attributes, e.g., numerical, temporal, and textual. The participants will get hands-on experience on how Apache AsterixDB can efficiently process complex SQL++ queries that require multiple special handling by a team from its kitchen.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
The OGC/ISO coverage API standards: Heavy-lifting APIs for massive multi-dimensional data OGC/ISO覆盖API标准:用于大量多维数据的繁重API
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science Pub Date : 2021-11-02 DOI: 10.1145/3486189.3490019
P. Baumann
{"title":"The OGC/ISO coverage API standards: Heavy-lifting APIs for massive multi-dimensional data","authors":"P. Baumann","doi":"10.1145/3486189.3490019","DOIUrl":"https://doi.org/10.1145/3486189.3490019","url":null,"abstract":"The concept of coverages, generally grasping multi-dimensional space/time varying phenomena, has received impressive attention among service implementers and operators. The biggest reason for this success is that coverages conveniently model datacubes, specifically in combination with powerful APIs such as the Web Coverage Service (WCS) with its datacube analytics language, Web Coverage Processing Service (WCPS). OGC, ISO, and EU INSPIRE capitalize on coverages, and leading tools implement them. In this tutorial, we first briefly recapitulate the coverage model and simple access with WCS Core, address the status of OAPI-Coverages, and then proceed to datacube analytics with WPCS. Practical demos based on the EarthServer datacube federation serve to illustrate; participants can recap and modify most of the demos. Altogether, this workshop constitutes a unique opportunity for getting up to speed with coverages and datacubes.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128951837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
CyberGIS-compute for enabling computationally intensive geospatial research CyberGIS-compute使计算密集的地理空间研究成为可能
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science Pub Date : 2021-11-02 DOI: 10.1145/3486189.3490017
Anand Padmanabhan, Ximo Ziao, Rebecca Vandewalle, Furqan Baig, Alexander Michels, Zhiyu Li, Shaowen Wang
{"title":"CyberGIS-compute for enabling computationally intensive geospatial research","authors":"Anand Padmanabhan, Ximo Ziao, Rebecca Vandewalle, Furqan Baig, Alexander Michels, Zhiyu Li, Shaowen Wang","doi":"10.1145/3486189.3490017","DOIUrl":"https://doi.org/10.1145/3486189.3490017","url":null,"abstract":"Geospatial research and education have become increasingly dependent on cyberGIS to tackle computation and data challenges. However, the use of advanced cyberinfrastructure resources for geospatial research and education is extremely challenging due to both high learning curve for users and high software development and integration costs for developers, due to limited availability of middleware tools available to make such resources easily accessible. This tutorial describes CyberGIS-Compute as a middleware framework that addresses these challenges and provides access to high-performance resources through simple easy to use interfaces. The CyberGIS-Compute framework provides an easy to use application interface and a Python SDK to provide access to CyberGIS capabilities, allowing geospatial applications to easily scale and employ advanced cyberinfrastructure resources. In this tutorial, we will first start with the basics of CyberGIS-Jupyter and CyberGIS-Compute, then introduce the Python SDK for CyberGIS-Compute with a simple Hello World example. Then, we will take multiple real-world geospatial applications use-cases like spatial accessibility and wildfire evacuation simulation using agent based modeling. We will also provide pointers on how to contribute applications to the CyberGIS-Compute framework.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133376249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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