Enhanced land use classification 2014 of the Rur catchment

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Title:Main Title: Enhanced land use classification 2014 of the Rur catchment
Description:Abstract: This data set contains the land use classification of 2014 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.12 (DOI)
Citation Advice:Lussem, Ulrike; Waldhoff, Guido (2014): Enhanced land use classification of 2014 for the Rur catchment. CRC/TR32 Database (TR32DB). DOI: 10.5880/TR32DB.12
Responsible Party
Creators:Ulrike Lussem (Author), Guido Waldhoff (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:2014
Topic
TR32 Topic:Land Use
Related Subproject:Z1
Subjects:Keywords: Land Use, Agriculture, ATKIS, Remote Sensing
Geographic Information Topic:Geoscientific Information
File Details
Filename:TR32_LU2014.zip
Data Type:Dataset - Dataset
Sizes:1 Datasets
7789 Kilobytes
File Size:7.6 MB
Date:Submitted: 25.11.2014
Mime Type:application/zip
Data Format:GeoTIFF
Language:English
Status:Completed
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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
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Specific Information - Data
Temporal Extent:01.01.2014, 00:00:00 - 31.12.2014, 23:59:00
Lineage:The land use classification is derived from supervised, multi temporal remote sensing data analysis using Landsat 8 and ASTER. For the land use analysis datasets of the following acquisition dates were employed: March 27 (Landsat 8), May 05 (Landsat 8), May 20 (ASTER), June 06 (Landsat 8), July 24 (Landsat 8). Full coverage of the study area was not available for all acquisition dates and thus the crop classification was partly affected in its depth of information. For the assessment of the crop classification accuracy refer to the error matrix on the last page of the documentation. 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. Thus, a more disaggregated landuse 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) and in Waldhoff et al. (2012). 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.
Subtype:Natural Science Data
Metadata Details
Metadata Creator:Guido Waldhoff
Metadata Created:26.11.2014
Metadata Last Updated:26.11.2014
Subproject:Z1
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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Metadata Downloads:20
Dataset Downloads:5
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