Land use classification of 2018 for the CRC/TR32 measurement region Selhausen/Merken/Merzenhausen, preliminary results
This page lists all metadata that was entered for this dataset. You can download the dataset and view an additional description file.
Features
Citation
Citation Options
Identification
| Title: | Main Title: Land use classification of 2018 for the CRC/TR32 measurement region Selhausen/Merken/Merzenhausen, preliminary results |
| Description: | Abstract: This data set contains the preliminary land use classification of 2018 for the measurement region Selhausen/Merken/Merzenhausen of 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: | 10.5880/TR32DB.32 (DOI) |
| Related Resources: | References Text 10.1016/j.jag.2017.04.009 (DOI) References Text 10.1016/B978-0-12-409548-9.09636-6 (DOI) |
| Citation Advice: | Lussem, Ulrike (2018): Land use classification of 2018 for the CRC/TR32 measurement region Selhausen/Merken/Merzenhausen, preliminary results. TR32DB. DOI:10.5880/TR32DB.32 |
Responsible Party
| Creator: | Ulrike Lussem (Author) |
| Contributors: | University of Cologne (Institute of Geography) (Producer), Transregional Collaborative Research Centre 32 (Meteorological Institute, University of Bonn) (Producer) |
| Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 32: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation |
| Publisher: | CRC/TR32 Database (TR32DB) |
| Publication Year: | 2018 |
Topic
| TR32 Topic: | Land Use |
| Related Subproject: | Z1 |
| Subjects: | Keywords: Land Use, Agriculture, ATKIS, Remote Sensing, Crop/s |
| Geogr. Information Topic: | Geoscientific Information |
File Details
| Filename: | TR32_LU2018_Selhausen.zip |
| Data Type: | Dataset - Dataset |
| Size: | 1 Datasets |
| File Size: | 1.8 MB |
| Date: | Submitted: 04.10.2018 |
| Mime Type: | application/zip |
| Data Format: | ZIP |
| Language: | English |
| Status: | Completed |
Archive Content
Constraints
| Download Permission: | Free |
| 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 |
Geographic
Specific Information - Data
| Temporal Extent: | 01.05.2018, 00:00:00 - 30.08.2018, 11:15:00 |
| 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 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. |
| Subtype: | Natural Science Data |
Metadata Details
| Metadata Creator: | Ulrike Lussem |
| Metadata Created: | 04.10.2018 |
| Metadata Last Updated: | 04.10.2018 |
| Subproject: | Z1 |
| Funding Phase: | 3 |
| Metadata Language: | English |
| Metadata Version: | V50 |
Metadata Export
| Metadata Schema: |
Dataset Statistics
| Page Visits: | 613 |
| Metadata Downloads: | 29 |
| Dataset Downloads: | 5 |
Dataset Activity
Features
By downloading this dataset you accept the license terms of [TR32DB] Data policy agreement and TR32DB Data 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.
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.
