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Dataset . 2022
License: CC BY
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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mDRONES4rivers-project: Classification results based on UAV data of project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany

Authors: Edvinas Rommel; Laura Giese; Frederik Kathoefer; Björn Baschek;

mDRONES4rivers-project: Classification results based on UAV data of project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany

Abstract

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project „Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices. Within the project period (2019-2022) an object oriented image classification was conducted based on UAV and gyrocopter data for different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘. In this dataset, the following classification results and metadata of the project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany is available for download: • Basic & Vegetation Classification (ESRI Shapefile; abbreviation: lvl2_vegetation_units) • Classification of dominant stands (ESRI Shapefile; abbreviation: lvl4_dominant_stands ) • Classification of substrat types (ESRI Shapefile; abbreviation: lvl4_substrate_types) • associated reports (PDF; statistical and additional information on the classifiaction results and workflow) The above-mentioned files are provided for download as dataset stored in one directory per projekt site and season (e.g. mDRONES4rivers_Niederwerth_2019_03_Summer_Classification.zip = projectname_projectsite_year_no.season_name.season_product). To provide an overview of all files and general background information plus data preview the following files are additionally provided: • Portfolios (PDF, Detailed description of classification products and classification workflow, 1x for basic surface types, 1x for classification of vegetation units, 1x for classification of dominant stands, 1x for classification of substrate types) • Color Coding table for the visualization of the classifiaction units (.xlsx)

This dataset results from the joint project "mDRONES4rivers" funded by the research initiative mFUND of the German Federal Ministry for Digital and Transport – BMDV (19F2054A-D). Person in Charge: Bjoern Baschek

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Keywords

geotiff, Rhine, multispectral, UAV, riparian, river, water, near infrared, open data, Nonnenwerth, drone, high-resolution, renaturation, Remote Sensing, DSM, Digital Surface Model, Emmericher Ward, Kuehkopf Knoblochsaue, RGB, orthophoto, Vegetation, Image Classification, Hydromorphology, aerial, Laubenheim, federal waterways, monitoring, mDRONES4rivers, UAS, Niederwerth, Substrate

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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