[1880] - Land use classification of 2018 for the Rur catchment

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Lussem, U., Herbrecht, M., 2019. Land use classification of 2018 for the Rur catchment. CRC/TR32 Database (TR32DB). CRC/TR32 Database (TR32DB). DOI: 10.5880/TR32DB.38.
Title(s):Main Title: Land use classification of 2018 for the Rur catchment
Description(s):Abstract: This data set contains the land use classification of 2018 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 and in ASCII format. Spatial resolution: 15 m; projection: WGS84, UTM Zone 32N.
Identifier(s):DOI: 10.5880/TR32DB.38
Relation(s):References: DOI: 10.1016/j.jag.2017.04.009, related data type: Text
References: DOI: 10.1016/B978-0-12-409548-9.09636-6, related data type: Text
Citation Advice:Lussem, Ulrike & Herbrecht, Marina (2019): Land use classification of 2018 for the Rur catchment. TR32DB. DOI:10.5880/TR32DB.38
Responsible Party
Creator(s):Owner: Ulrike Lussem
Author: Marina Herbrecht
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:TR32_LU2018.zip
Data Type:Dataset
Size(s):1 Datasets
File Size:6687 kB (6.53 MB)
Date(s):Date Submitted: 2019-04-04
Mime Type:application/zip
Data Format:ZIP
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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:2018/05/01 - 2018/08/30
Lineage:The land use classification is derived from supervised, multi temporal remote sensing data analysis using Sentinel-2 data. For the land use analysis datasets of the following acquisition dates were employed: May 05, May 28, July 02, July 07, and August 06. For the assessment of the crop classification accuracy please refer to the error matrix on the last page of the documentation file (pdf). 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 Basis-DLM) and ‘Physical Block’ information. The methodology of the MDA is described in more detail in Waldhoff et al. 2017, Bareth & Waldhoff (2018) and Waldhoff (2014). The classification is provided in GeoTIFF and in ASCII format. Spatial resolution: 15 m; Projection: WGS84, UTM Zone 32N. 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-Basis-DLM and Copernicus/European Space Agency (ESA) for providing Sentinel-2 data.
Metadata Details
Metadata Creator:Ulrike Lussem
Metadata Created:2019-04-04
Metadata Last Updated:2019-04-04
Funding Phase:3
Metadata Language:English
Metadata Version:V43
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