Enhanced land use classification 2015 of the Rur catchment
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: Enhanced land use classification 2015 of the Rur catchment |
Description: | Abstract: This data set contains the final land use classification of 2015 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: | 10.5880/TR32DB.17 (DOI) |
Citation Advice: | Waldhoff, Guido; Lussem, Ulrike; (2015): Enhanced land use classification 2015 for the Rur catchment. TR32DB. DOI:10.5880/TR32DB.17. |
Responsible Party
Creators: | Guido Waldhoff (Author), 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: | 2015 |
Topic
TR32 Topic: | Land Use |
Related Subproject: | Z1 |
Subjects: | Keywords: Land Use, Agriculture, ATKIS, Remote Sensing |
Geogr. Information Topic: | Geoscientific Information |
File Details
Filename: | TR32_LU2015.zip |
Data Type: | Dataset - Dataset |
Size: | 1 Datasets |
File Size: | 7.3 MB |
Date: | Submitted: 22.12.2015 |
Mime Type: | application/zip |
Data Format: | GeoTIFF |
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: | 01.01.2015, 00:00:00 - 31.12.2015, 23:59:00 |
Lineage: | The land use classification is derived from supervised, multi temporal remote sensing data analysis using Landsat 8 (L8) and RapidEye (RE). For the final land use analysis datasets of the following acquisition dates were employed: April 15 (RE), April 23 (RE), May 15 (L8), June 04 (RE), July 07 (RE), August 01 (RE), August 20 (RE), September 29 (L8), and October 01 (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 in the additional file. 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. Additionally information on cropping areas in the Netherlands were acquired and implemented. Thus, a more disaggregated land use was obtained, especially for the regions in Belgium and the Netherlands. The methodology of the MDA is described in more detail in Waldhoff & Bareth (2008), Waldhoff et al. (2012) 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. & Bareth, G. (2008): GIS- and RS-based land use and land cover analysis: case study Rur-Watershed, Germany. - Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 714626 (November 10, 2008); doi:10.1117/12.813171. Waldhoff, G., Curdt, C., Hoffmeister, D. & Bareth, G. (2012): Analysis of multitemporal and multisensor remote sensing data for crop rotation mapping. - ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-7, 177-182, doi:10.5194/isprsannals-I-7-177-2012. Waldhoff, G. (2014): Multidaten-Ansatz zur fernerkundungs- und GIS-basierten Erzeugung multitemporaler, disaggregierter Landnutzungsdaten. Methodenentwicklung und Fruchtfolgenableitung am Beispiel des Rureinzugsgebiets. Dissertation, University of Cologne, Cologne. |
Subtype: | Natural Science Data |
Metadata Details
Metadata Creator: | Guido Waldhoff |
Metadata Created: | 22.12.2015 |
Metadata Last Updated: | 22.12.2015 |
Subproject: | Z1 |
Funding Phase: | 3 |
Metadata Language: | English |
Metadata Version: | V50 |
Metadata Export
Metadata Schema: |
Dataset Statistics
Page Visits: | 672 |
Metadata Downloads: | 19 |
Dataset Downloads: | 7 |
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.