Find research datasets worth reusing

opencc-by-4.0Sep 2021View details →

Material requirements for future low-carbon electricity projections in Africa - dataset

This dataset is provided to supplement the paper "Material requirements for future low-carbon electricity projections in Africa". The paper calculated the material requirements of proposed electricity systems based on the <a href="https://zenodo.org/record/3521841#.YTHYP44zaUk">JRC-TEMBA </a>projections of African electricity systems, including the embodied emissions resulting from such systems from 2015 to 2065. The data included in this repository covers the total mass of materials, embodied emissions, and jobs created given by country, year and/or region.

Smartcow EU project database on feed efficiency in beef cattle and analysis of natural 15N abundance and plasma urea concentration

This is a database built in the frame of the Smartcow H2020 Eu project (N°730924) and gathering individual raw data for animal performances obtained in thirteen beef cattle trials conducted in France, UK and Switzerland as well as animal values for two biomakers of feed efficiency : the natural 15N abundance in animal proteins (plasma or muscle) and plasma urea concentration.

Fig. 8 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 8. Diversity of Trichobranchidae, SEM. A. Terebellides gentili Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, anterior end, lateral view (MNHN-IA-TYPE 1873). B. Terebellides lilasae Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, branchia, lateral view (MNHN- IA-TYPE 1881). C. Trichobranchus glacialis Malmgren, 1866, anterior end, lateral view (SMA-BR- Tricho-05). D. Octobranchus lingulatus (Grube, 1863), anterior end, lateral view (MNHN-IA-PNT 94). E. Terebellides resomari Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, geniculate chaetae (paratype MNHN-IA-TYPE 1892). F. Terebellides lilasae, thoracic uncini (SMA-ARC- Terebellides-VOG8-1). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Gc = Geniculate chaetae; Ll = Lateral lobes.

Fig. 7 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 7. Diversity of Trichobranchidae. A. Terebellides lilasae Lavesque, Hutchings, Daffe, Nygren & Londoño-Mesa, 2019, entire specimen, lateral view (MNHN-IA-TYPE 1879). B. Terebellides lilasae, anterior end, lateral view, methyl green staining (MNHN-IA-TYPE 1879). C. Trichobranchus glacialis Malmgren, 1866, anterior end, lateral view (MNHN-IA-PNT 96). D. Terebellides sp., thoracic acicular uncini (SMA-BR-Terebellides-KER1). Abbreviations: Br = Branchiae; glr = glandular region; Pp = Posterior process.

Fig. 6 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 6. Diversity of Terebellidae Johnston, 1846 (s.s.), SEM. A. Pista sauriauiLavesque, Daffe, Londoño- Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2036). B. Paramphitrite dragovabeci Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2030). C. Lanice kellyslateri Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (paratype MNHN-IA-TYPE 2028). D. Eupolymnia meissnerae Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, ventro-lateral view (paratype MNHN-IA-TYPE 2025). E. Lanice kellyslateri, thoracic uncini (paratype MNHN-IA-TYPE 2028). F. Paramphitrite dragovabeci, uncini SG XIV (paratype MNHN-IA-TYPE 2030). G. Eupolymnia meissnerae, uncini SG VIII (paratype MNHN-IA-TYPE 2025). Abbreviations: Gp = genital papillae; Ll = lateral lobes; Ul = upper lip. Numbers referring to segments.

Fig. 3 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 3. Diversity of Telothelepodidae Nogueira, Fitzhugh & Hutchings, 2013 and Thelepodidae Hessle, 1917. A. Parathelepus collaris (Southern, 1914), anterior end, frontal view (AM W.53063). B. Parathelepus collaris, anterior end, ventral view (NHMUK ANEA 1983.1696). C. Thelepus japonicus Marenzeller, 1884, anterior end, lateral view (AM W.53073). D. Thelepus corsicanus Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, frontal view (AM W.53068). E. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, dorsal view (MNHN-IA- TYPE 2000). F. Thelepus japonicus, anterior end, ventral view (MNHN-IA-PNT 117). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Gp = genital papillae; Ll = Lower lip; Ul = Upper lip.

Fig. 5 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 5. Diversity of Terebellidae Johnston, 1846 (s.s.). A. Eupolymnia lacazei Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, live specimen (paratype MNHN-IA-TYPE 2023). B. Eupolymnia gili Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (holotype MNHN- IA-TYPE 2020). C. Amphitrite edwardsii (Quatrefages, 1866), anterior end, lateral view (MNHN-IA- PNT 126). D. Terebella banksyi Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, anterior end, lateral view (holotype MNHN-IA-TYPE 2037). E. Paramphitrite dragovabeci Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, notochaeta, SG XI (paratype MNHN-IA-TYPE 2030). F. Terebella cf. lapidaria Linnaeus, 1767, notochaetae, SG IX (MNHN-IA-PNT 131). G. Terebella lapidaria, notochaetae, posterior segments (MNHN-IA-PNT 131). Abbreviations: Bs = branchial stem; Ey = eyes; Gp = genital papillae; Ll = lateral lobes; Np = nephridial papillae. Numbers referring to segments.

Fig. 2 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 2. Diversity of Polycirridae Malmgren, 1866. A. Amaeana gremarei Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, lateral view (MNHN-IA-TYPE 2006). B. Polycirrus gujanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, ventral view (MNHN-IA-TYPE 2013). C. Amaeana gremarei, anterior end, ventral view (AM W.53111). D. Polycirrus idex Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, anterior end, ventral view (AM W.53127). E. Polycirrus glasbyi Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, notochaetae SG V (AM W.53118). F. Polycirrus catalanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, abdominal uncini (AM W.53113). G. Polycirrus glasbyi, thoracic uncini (AM W.53118). Abbreviations: Bt = buccal tentacles; Gp = genital papilla; Ll = lower lip; Ne = neuropodia; Ul = upper lip; Vp = ventral pads.

Fig. 1 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 1. Schematic illustrations of different uncini morphologies, in lateral view (following Nogueira et al. 2010). A. Terebellides sp., SG IX (SMA-BR-Terebellides-KER1). B. Polycirrus catalanensis Lavesque, Hutchings, Daffe & Londoño-Mesa, 2020, SG XX (holotype MNHN-IA-TYPE 2007). C. Pista sauriaui Lavesque, Daffe, Londoño-Mesa & Hutchings, 2021, SG V (paratype MNHN-IA- TYPE 2036). D. Lomia ramzega Lavesque, Bonifácio, Londoño-Mesa, Le Garrec & Grall, 2017, SG XII (paratype MNHN-IA-TYPE 1791). E. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, SG VI (holotype MNHN-IA-TYPE 2000). F. Thelepus japonicus Marenzeller, 1884, SG XVII (MNHN-IA-PNT 117). Abbreviations: Af = anterior filament; Ba = base; Ca = capitium; Cext = coma-shape extension; Cr = crest; Db = dorsal button; He = heel; Lh = long handle; Mf = main fang; Oc = occipitium; Pr = prow.

Fig. 4 in The "Spaghetti Project": the final identification guide to European Terebellidae (sensu lato) (Annelida, Terebelliformia)

Fig. 4. Diversity of Telothelepodidae Nogueira, Fitzhugh & Hutchings, 2013 and Thelepodidae Hessle, 1917, SEM. A. Parathelepus collaris (Southern, 1914), anterior end, frontal view (AM W.53063). B. Thelepus corsicanus Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, latero-frontal view (AM W.53069). C. Streblosoma cabiochi Lavesque, Londoño-Mesa, Daffe & Hutchings, 2020, anterior end, lateral view (AM W.53066). D. Thelepus corsicanus, thoracic notochaetae (AM W.53069). E. Parathelepus collaris, abdominal uncini, (AM W.53063). F. Thelepus japonicus Marenzeller, 1884, abdominal uncini, SG48. (SMA-NL-Thele08). Abbreviations: Br = Branchiae; Bt = Buccal tentacles; Lc = lateral crest; Ll = Lower lip; Vl = Ventral lobe of SG I.

opencc-by-4.0Nov 2021View details →

Final project report: The Side Effects of Forced Online Distance Education (FODE)

The outbreak of COVID-19 forced most universities into distance education. Three didacticians and researchers from the University of Maribor, Slovenia: Kosta Dolenc, Mateja Ploj Virtič and Andrej &Scaron;orgo formed a self-initiated initiative project group during the COVID-19 epidemic and started the project with the working title: The Side Effects of Forced Online Distance Education (FODE). The aim of the project, was to investigate the response of university teachers and students to the new situation.

Iron model intercomparison project muti model dissolved iron data

Dataset here includes the dissolved iron multi model mean and variance from the models used in : Tagliabue, A., et al. (2016), How well do global ocean biogeochemistry models simulate dissolved iron distributions?, Global Biogeochemical Cycles, doi:10.1002/2015gb005289. Average and variance calculated using ferret @ave and @var transforms in ferret (https://ferret.pmel.noaa.gov/Ferret) netcdf format and information on the grid is found in the above manuscript Prepared as part of SCOR Workig Group 151 FeMIP

Database containing harmonized datasets - FAIRWAY Project Deliverable 3.3

A database has been developed and delivered during the <a href="https://www.fairway-project.eu/">FAIRWAY project</a>. This database was developed as a response to the need to harmonize datasets and assessment methods related to pressure and state indicators for water quality in the EU member states, in order to compare and assess indicators using a harmonized approach. The dataset that is made available here provides two files: <ul> <li>a public version* of the Excel database, which contains all "tabular" (non-GIS) data related to the 13 case studies that was gathered for the purposes of FAIRWAY's Monitoring & Indicators research theme. It is structured as one "data sheet" and one "summary sheet" per case study. The data sheets contain various parameters (ideally time-dependent data series i.e. time series) that were used, wherever possible, to compute relevant Agri-drinking water quality indicators (ADWIs) such as "nitrogen budget" (a compound Pressure indicator) or "lag time" (a statistically-inferred Link indicator).</li> <li>a ZIP folder containing all GIS data gathered for the FAIRWAY's Monitoring & Indicators research theme. The GIS files are grouped in subfolders, by case study, and then by keywords describing the nature of the spatial data.</li> </ul> The Excel database contains near 385,000 rows of data from the 13 case study sites, with more than 65 parameters and more than 500 sub-parameters. The dataset also contains spatial information in a GIS-data zipped folder. The spatial mapping information can be made visible using basic <a href="https://www.qgis.org/en/site/">QGIS</a> project files (.qgz), so that GIS data from each case study can be explored. The indicators database can be used in several ways. It may be used to explore data or to calculate additional indicators. Depending of the case studies’ interests, the most commonly available State indicators are about nitrate and pesticides concentrations in water. From a practical point of view based on its actual content, the database may notably be used to explore statistical relations (or Links) between related Pressure and State indicators. This database can also be used as a spatial mapping portal for other usages. For more information on the database, follow <a href="https://fairway-is.eu/index.php/farm-management/workpackages/harmonised-indicator-database">this link</a>. * Note that this is a public version of the database, which means that all confidential data was removed from the data sheets.

An Empirical Study on the Survival Rate of GitHub Projects

This zip provides the replication package for the paper titled An Empirical Study on the Survival Rate of GitHub Projects sent to the Mining Software Repositories 2022 conference, currently under review.

Project-KB based Vulnerability Method Dataset

This archive contains the vulnerability method dataset generated from project-KB. Every entry corresponds to a method and  contains metadata regarding the method and the label fixed or vulnerable. Additional details can be found in the readme file.

Dataset produced by Sagremarisco at Sagres (SW Portugal) pilot site as part of the GAIN project

The dataset includes insitu data collected at the Sagres pilot site, data from Hobo Sensors, data from the moored bouy, remote sensing data correspondent to the pixel of the study site. Includes phytoplankton counts, spectrophotometric chlorophyll as well as HPLC phytoplankton pigments.

The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates

This repository contains the socioeconomic and emissions projections generated by the Resources for the Future Socioeconomic Projections (RFF-SPs) model as discussed in Rennert et al., "<a href="https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/">The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates</a>" , forthcoming at the Brookings Papers on Economic Activity. The data take the form of a Monte Carlo simulation with n = 10,000 draws. File structure and column metadata are described here:   ---   emissions/   ---   - rffsp_co2_emissions.csv   - rffsp_ch4_emissions.csv   - rffsp_n2o_emissions.csv   Each file in this folder contains 3 columns: sample, year, and value. For each row:   - sample contains the number identifying which draw a prediction belongs to (from 1 to 10,000).   - year contains the calendar year of the prediction.   - value contains the projected annual global emissions of the gas specified in the filename. IMPORTANT: Units are as follows: "rffsp_co2_emissions.csv" is in gigatons C (not CO2), "rffsp_ch4_emissions.csv " is in megatons CH4, and "rffsp_n2o_emissions.csv " is in megatons N2 (not N2O).  ---   pop_income/   ---   - rffsp_pop_income_run_1.feather   - rffsp_pop_income_run_2.feather   - rffsp_pop_income_run_3.feather   .  .  .  - rffsp_pop_income_run_9999.feather   - rffsp_pop_income_run_10000.feather   This folder contains 10,000 files in the .feather file format (https://arrow.apache.org/docs/python/feather.html), which is optimized for I/O speed and compressed to minimize storage requirements. Each file corresponds to one draw of our socioeconomic data, and contains 4 columns: Country, Year, Pop, and GDP. The number in each filename corresponds to the "sample" column in the emissions data. For each row: - Country contains the ISO Alpha-3 code (https://www.iso.org/iso-3166-country-codes.html) of the country whose GDP and population are projected.  - Year contains the calendar year of the predictions.   - Pop contains the projected population for a given country and year, in units of thousands of people.   - GDP contains the projected GDP for a given country and year, in units of millions of 2011 USD.  ---  The probabilistic population projections were produced by Adrian E. Raftery and Hana &Scaron;evčíková (University of Washington), using the methods described by Raftery and &Scaron;evčíková (2021). Please cite this reference in any publications using these projections. Their research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) under NIH grant number R01 HD-070936.   The probabilistic economic and emissions projections are from Rennert et al. (forthcoming), based in part on those from Müller, Stock, and Watson (forthcoming).  --- References   Müller, U.K, Stock, J.H., and Watson, M.W. (forthcoming). An Econometric Model of International Growth Dynamics for Long-Horizon Forecasting. The Review of Economics and Statistics, available online 30 October 2020. URL: <a href="https://direct.mit.edu/rest/article-abstract/doi/10.1162/rest_a_00997/97738/An-Econometric-Model-of-International-Growth">https://direct.mit.edu/rest/article-abstract/doi/10.1162/rest_a_00997/97738/An-Econometric-Model-of-International-Growth</a>  Raftery, A.E. and &Scaron;evčíková, H. (2021). Probabilistic population forecasting: Short to very long-term. International Journal of Forecasting, available online 7 October 2021. URL: <a href="https://www.sciencedirect.com/science/article/pii/S0169207021001394">https://www.sciencedirect.com/science/article/pii/S0169207021001394</a>   Rennert, K., Prest, B.C., Pizer, W., Newell, R.G., Anthoff, D., Kingdon, C., Rennels, L., Cooke, R., Raftery, A.E., &Scaron;evčíková, H, and Errickson, F. (forthcoming). The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates. Brookings Papers on Economic Activity. Available online 27 October 2021. URL: <a href="https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/">https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/ </a>

mDRONES4rivers-project: UAV-imagery of the project area Nonnenwerth at the Rhine River, Germany

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 &bdquo;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) data was collected at 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 UAS data and metadata of the project site ‘Nonnenwerth’ (center coordinates [WGS84]: 50.637541°N, 7.208834°E; area: 8 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: UAV-imagery of the project area Emmericher Ward at the Rhine River, Germany

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 &bdquo;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) data was collected at 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 UAS data and metadata of the project site ‘Emmericher Ward’ (center coordinates [WGS84]: 50.385264°N, 6.198692°E; area: 53ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_EW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: UAV-imagery of the project area Reitwein at the River Oder, Germany

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 &bdquo;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) data was collected at 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 UAS data and metadata of the project site ‘Reitwein’ (center coordinates [WGS84]: 52.500961°N, 14.629186 °E; area: 60 ha) at the River Oder in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition and flight altitude, as the data was collected here from two different flight altitudes (e.g. mDRONES4rivers_RW_UAV_2020_03_summer_70m.zip = projectname_projectsite_platform_year_no.season_name.season_flightaltitude.zip). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.