Next Article in Journal
Dataset on Substrate-Borne Vibrations of Constrictotermes cyphergaster (Blattodea: Isoptera) Termites
Next Article in Special Issue
On-Demand Processing of Data Cubes from Satellite Image Collections with the gdalcubes Library
Previous Article in Journal
Special Issue on the Curative Power of Medical Data
Article Menu
Issue 2 (June) cover image

Export Article

Open AccessArticle

A Topology Based Spatio-Temporal Map Algebra for Big Data Analysis

Institute for Geoinformatics, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach am Main, Germany
Author to whom correspondence should be addressed.
Received: 14 April 2019 / Revised: 26 May 2019 / Accepted: 27 May 2019 / Published: 18 June 2019
(This article belongs to the Special Issue Earth Observation Data Cubes)
PDF [2658 KB, uploaded 18 June 2019]


Continental and global datasets based on earth observations or computational models challenge the existing map algebra approaches. The available datasets differ in their spatio-temporal extents and their spatio-temporal granularity, which makes it difficult to process them as time series data in map algebra expressions. To address this issue we introduce a new map algebra approach that is topology based. This topology based map algebra uses spatio-temporal topological operators (STTOP and STTCOP) to specify spatio-temporal operations between topological related map layers of different time-series data. We have implemented several topology based map algebra tools in the open source geoinformation system GRASS GIS and its open source cloud processing engine actinia. We demonstrate the application of our topology based map algebra by solving real world big data problems using a single algebraic expression. This included the massively parallel computation of the NDVI from a series of 100 Sentinel2A scenes organized as earth observation data cubes. The processing was performed and benchmarked on a many core computer setup and in a distributed container environment. The design of our topology based map algebra allows us to deploy it as a standardized service in the EU Horizon 2020 project openEO. View Full-Text
Keywords: topology based map algebra; data cubes; big data; map algebra; earth oberservation; GRASS GIS topology based map algebra; data cubes; big data; map algebra; earth oberservation; GRASS GIS

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Gebbert, S.; Leppelt, T.; Pebesma, E. A Topology Based Spatio-Temporal Map Algebra for Big Data Analysis. Data 2019, 4, 86.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics



[Return to top]
Data EISSN 2306-5729 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top