Data


Geodata set of 'Spatial loess distribution in the eastern Carpathian Basin: a novel approach based on geoscientific maps and data'

Abstract

The provided geodata contain the digitized areas covered by loess and loess-like sediments in Hungary (after Balogh et al. 1956) and the respective coverage in the border region of northwest Romania which has been derived from geoscientific maps and data: soil type and texture after Florea et al. (1971), land cover data after CLC 2006 published by EEA (2012) and geomorphometric data based on the DEM SRTM 1 Arc-Second Global provided by USGS (2015)). Therefrom, digitized and reclassified soil types after the Romanian soil map, and two raster datasets of derived morphometric indices are published. Additionally, a merged shapefile of the resulting loess and loess-like sediments, designed for a scale of about 1:500.000, is published.

This geodataset is linked to the publication by Lindner, H., Lehmkuhl, F., Zeeden, C. (2017): Spatial loess distribution in the eastern Carpathian Basin: a novel approach based on geoscientific maps and data. – In: Journal of Maps, Vol. 2(13), p: 173-181, DOI: 10.1080/17445647.2017.1279083

Resources

zip SOIL_RO.zip Accessed 11 times | Last updated 20.02.2017
zip LD_RO.zip Accessed 9 times | Last updated 20.02.2017
zip LD_HU_RO.zip Accessed 8 times | Last updated 20.02.2017
zip LD_HU.zip Accessed 7 times | Last updated 20.02.2017
file README_Metadata.docx Accessed 23 times | Last updated 20.02.2017
zip Mean_DEV_RO_3k.zip Accessed 23 times | Last updated 23.03.2017
zip TPI_RO_300.zip Accessed 9 times | Last updated 23.03.2017

Bibliography

Lindner, H., Lehmkuhl, F., Zeeden, C. (2017): Geodata set of 'Spatial loess distribution in the eastern Carpathian Basin: a novel approach based on geoscientific maps and data'. DOI: 10.1080/17445647.2017.1279083

Authors Lindner, Heiko and Lehmkuhl, Frank and Zeeden, Christian
Type dataset
Title Geodata set of 'Spatial loess distribution in the eastern Carpathian Basin: a novel approach based on geoscientific maps and data'
DOI 10.1080/17445647.2017.1279083
Year 2017
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