Abstract
Today, big data is one of the most challenging topics in computer science. To give customers, developers or domain experts an overview of their data, it needs to be visualized. In case data contains geospatial information, it becomes more difficult, because most users have a well-trained experience how to explore geographic information. A common map interface allows users zooming and panning to explore the whole dataset. This paper focuses on an approach to visualize huge sets of geospatial data in modern web browsers along with maintaining a dynamic tile tree. The contribution of this work is, to make it possible to render over one million polygons integrated in a modern web application by using 2D Vector Tiles. A major challenge is the map interface providing interaction features such as data-driven filtering and styling of vector data for intuitive data exploration. A web application requests, handles and renders the vector tiles. Such an application has to keep its responsiveness for a better user experience. Our approach to build and maintain the tile tree database provides an interface to import new data and more valuable a flexible way to request Vector Tiles. This is important to face the issues regarding memory allocation in modern web applications.
Keywords
- Bigdata
- Visualization
- Vector-tiling
- Geospatial data
- Web
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Notes
- 1.
Google Maps—https://maps.google.com.
- 2.
- 3.
OpenLayers—http://openlayers.de.
- 4.
- 5.
Open Geospatial Consortium—https://www.opengeospatial.org/.
- 6.
GeoTrellis—https://geotrellis.io.
- 7.
PostgreSQL—https://www.postgresql.org/.
- 8.
PostGIS—https://postgis.net.
- 9.
- 10.
GeoServer—http://geoserver.org/.
- 11.
ECC Vector Tile Encoder—https://github.com/ElectronicChartCentre/java-vector-tile.
- 12.
GeoRocket—https://georocket.io.
- 13.
MongoDB—https://www.mongodb.com/.
- 14.
Elasticsearch—https://www.elastic.co/products/elasticsearch.
- 15.
ECC Vector Tile Encoder—https://github.com/ElectronicChartCentre/java-vector-tile.
- 16.
Protobuf GitHub—https://github.com/protocolbuffers/protobuf/tree/master/java.
- 17.
OpenLayers—http://openlayers.de.
- 18.
Mapbox GL JS—https://mapbox.com.
- 19.
New versions may be released since, we used version 4.0.
- 20.
DataBio—https://databio.eu.
- 21.
BDV PPP—http://www.bdva.eu/PPP.
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Acknowledgements
Research presented here is carried out within the data-driven bioeconomy project Databio. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 732064. It is also part of the Big Data Value Public-Private Partnership. We would like to thank Prof. Dr. Ir. Arjan Kuijper for his valuable comments and input.
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Zouhar, F., Senner, I. (2020). Web-Based Visualization of Big Geospatial Vector Data. In: Kyriakidis, P., Hadjimitsis, D., Skarlatos, D., Mansourian, A. (eds) Geospatial Technologies for Local and Regional Development. AGILE 2019. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-14745-7_4
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