[1796] - Final land use classification of 2016 for the Rur catchment

All available metadata of the dataset is listed below. Some features are available, e.g. download of dataset or additional description file.

By downloading files from this dataset you accept the license terms of TR32DB Data policy agreement and TR32DBData Protection Statement.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Due to the speed of the filesystem and depending on the size of the archive and the file to be extracted, it may take up to thirty (!) minutes until a download is ready! Beware of that when confirming since you may not close the tab because otherwise, you will not get your file!
Waldhoff, G., 2018. Final land use classification of 2016 for the Rur catchment. CRC/TR32 Database (TR32DB). DOI: 10.5880/TR32DB.28.
Citation Options
Export as: Select the file format for your download.Citation style: Select the displayed citation style.
Title(s):Main Title: Final land use classification of 2016 for the Rur catchment
Description(s):Abstract: This data set contains the land use classification of 2016 for the study area of the CRC/Transregio 32: "Patterns in Soil-Vegetation-Atmosphere Systems: monitoring, modelling and data assimilation", which corresponds to the catchment of the river Rur. The study area is mainly situated in the western part of North Rhine-Westphalia (Germany) and parts of the Netherlands and Belgium. The classification is provided in GeoTIFF format. Spatial resolution: 15 m; Projection: WGS84, UTM Zone 32N.
Identifier(s):DOI: 10.5880/TR32DB.28
Relation(s):References: DOI: 10.1016/j.jag.2017.04.009
References: DOI: 10.1016/B978-0-12-409548-9.09636-6
Citation Advice:Waldhoff, Guido (2016): Final land use classification of 2016 for the Rur catchment. TR32DB. DOI:10.5880/TR32DB.28.
Responsible Party
Creator(s):Author: Guido Waldhoff
Contributor(s):Producer: University of Cologne, Institute of Geography
Producer: Transregional Collaborative Research Centre 32, Meteorological Institute, University of Bonn
Funding Reference(s):Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 32: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation
Publisher:CRC/TR32 Database (TR32DB)
TR32 Topic:Land Use
Related Sub-project(s):Z1
Subject(s):CRC/TR32 Keywords: Land Use, Agriculture, ATKIS, Remote Sensing, Crop/s
Topic Category:GeoScientificInformation
File Details
File Name:LU16.zip
Data Type:Dataset
Size(s):1 Datasets
File Size:7700 kB (7.52 MB)
Date(s):Date Submitted: 2018-05-28
Mime Type:application/zip
Data Format:GeoTIFF
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Data
Temporal Extent:2016/01/01 - 2016/12/31
Lineage:The land use classification is derived from supervised, multi temporal remote sensing data analysis using Sentinel-2 (S2) and RapidEye (RE). For the land use analysis datasets of the following acquisition dates were employed: April 20 (S2), May 8 (RE), June 9 (RE), August 16 (RE) and September 8 (RE). Full coverage of the study area was not available for all acquisition dates and thus the crop classification is partly affected in its depth of information. For the assessment of the crop classification accuracy refer to the error matrix on the last page. To enhance the information content of the land use data product, the Multi-Data Approach (MDA) was applied to combine the remote sensing derived land use information with additional data sets like the ‘Authorative Topographic-Cartographic Information System’ (ATKIS Basic-DLM, AAA schema) and ‘Physical Block’ information. Furthermore, OpenStreetMap (OSM) data were integrated to update the information on the road network, settlement areas in the Netherlands where CorineLandCover data were outdated, and the course of the river Rur in the Netherlands. The methodology of the MDA is described in more detail in Waldhoff et al. 2017, Bareth & Waldhoff (2018) and Waldhoff (2014). References: Waldhoff, G., Lussem, U., Bareth, G. (2017): Multi-Data Approach for remote sensing-based regional crop rotation mapping: A case study for the Rur catchment, Germany. International Journal of Applied Earth Observation and Geoinformation 61, 55-69, 10.1016/j.jag.2017.04.009. Bareth, G. and Waldhoff, G. (2018): 2.01 - GIS for Mapping Vegetation A2 - Huang, Bo. Comprehensive Geographic Information Systems, Elsevier, Oxford, 1-27, https://doi.org/10.1016/B978-0-12-409548-9.09636-6 Waldhoff, G. (2014): Multidaten-Ansatz zur fernerkundungs- und GISbasierten Erzeugung multitemporaler, disaggregierter Landnutzungsdaten. Methodenentwicklung und Fruchtfolgenableitung am Beispiel des Rureinzugsgebiets. Dissertation, University of Cologne, Germany, http://kups.ub.uni-koeln.de/id/eprint/5861. Acknowledgements: We thank Geobasis.NRW for the provision of the ATKIS-Basic-DLM. The spatial data for the Netherlands was obtained from geodata.nationaalgeoregister.nl. All OSM data were obtained from Geofabrik GmbH. Furthermore, we thank the Space Administration of the German Aerospace Center (DLR) and Planet Labs Germany GmbH for the provision of RapidEye data via the RapidEye Science Archive (RESA) and ESA for the provision of the Sentinel-2 data.
Metadata Details
Metadata Creator:Guido Waldhoff
Metadata Created:2018-05-28
Metadata Last Updated:2018-05-28
Funding Phase:3
Metadata Language:English
Metadata Version:V42
Metadata Export
Metadata Export:
Select the XML download format.
Dataset Metrics
Page Visits:370
Metadata Downloads:8
Dataset Downloads:9
Dataset Activity