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nrt-data: Demonstration and test data of the nrt python package

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Various dataset used to demonstrate the functionalities of the nrt Python package. The nrt package provides a standardized interface to multiple online time-series monitoring algorithms. The datasets are georeferenced raster and vector layers and multi-dimensional data cubes.

Contributors

Jonas Viehweger; Kenji Ose; Loïc Dutrieux

How to cite

Dutrieux, Loïc; Viehweger, Jonas; Ose, Kenji (2026): nrt-data: Demonstration and test data of the nrt python package. European Commission, Joint Research Centre [Dataset] doi: 10.2905/JRC.KV30G5G PID: http://data.europa.eu/89h/035dfc2d-4101-4215-8f9c-7169e9b428f5

Keywords

forest disturbancesland use changemonitoringsatellitetime-series

Data access

Demonstration and test data of the nrt Python package
CSV

CSV – comma-separated values – files store tabular data (numbers and text) in plain text. Each line of the file is a data record. Each record consists of one or more fields, separated by commas.
Downloadable file

A downloadable file for the dataset.

Use conditions
European Commission reuse notice

According to the European Commission reuse notice, reuse is authorised, provided the source is acknowledged. The reuse policy of the European Commission is implemented by the Decision of 12 December 2011. The general principle of reuse can be subject to conditions which may be specified in individual copyright notices. Therefore users are advised to refer to the copyright notices of the individual websites maintained under Europa and of the individual documents. Reuse is not applicable to documents subject to intellectual property rights of third parties.

Access conditions
No limitations

Anybody can directly and anonymously access the data, without being required to register or authenticate.

  • Various datasets used to demonstrate the functionalities of the nrt Python package. The datasets are georeferenced raster and vector layers as well as multi-dimensional data cubes

Publications

Publication
nrt: operational monitoring of satellite image time-series in Python
Dutrieux, Loïc; Viehweger, Jonas (2024), nrt: operational monitoring of satellite image time-series in Python. Journal of Open Source Software, 9(100), 6815

Temporal coverage

From date To date
2015-08-01 2022-12-21

Additional information

Published by
European Commission, Joint Research Centre
Contact email
loic.dutrieux (at) ec.europa.eu
Update frequency
irregular

The event occurs at uneven intervals.

Language(s)
English

English is a member of the West Germanic group of the Germanic languages. It is an official language of almost 60 sovereign states and is now a global lingua franca.It is the third-most-common native language in the world and it is widely learned as a second language.

Data theme(s)
Agriculture, fisheries, forestry and food

dataset theme covering the domains of agriculture which involves the cultivation of plants and livestock; fisheries which focuses on the harvesting of fish from wild or farmed sources; forestry which relates to the management and conservation of forests and woodlands; and food which includes substances that provide nutritional support to organisms
Environment

dataset theme covering the domain of environment, defined as the interaction of all living species, climate, weather, and natural resources that impact human survival and economic activity
Science and technology

dataset theme covering the domains of science and technology, with science being the systematic pursuit of knowledge through testable explanations and predictions across natural, social, and formal disciplines, and technology encompassing the collective techniques, skills, methods, and processes used in producing goods, providing services, or achieving objectives like scientific research

Geographical name(s)
World
Issued date
2024-08-19
Created date
20 Aug 2024 08:15
Modified date
20 Aug 2024 09:01
Landing page
https://nrt.readthedocs.io/en/latest/index.html 
Dataset identifier
http://data.europa.eu/89h/035dfc2d-4101-4215-8f9c-7169e9b428f5
Other identifiers
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