The dataset contains maps of the main classes of agricultural land use (dominant crop types and other land use types) in Germany, which are produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire open landscape, i.e., the agriculturally used area (UAA) and e.g., uncultivated areas. The map was derived from time series of Sentinel-1, Sentinel-2, Landsat 8 and additional environmental data. Map production is based on the methods described in Blickensdörfer et al. (2022).

All optical satellite data were managed, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software FORCE - Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019), in which SAR and environmental data were integrated.

The map extent covers all areas in Germany that are defined in the respective year as cropland, grassland, small woody features, heathland, peatland or unvegetated areas according to ATKIS Basis-DLM (Geobasisdaten: © GeoBasis-DE / BKG, 2020).

Version v201:
Post-processing of the maps included a sieve filter as well as a ruleset for the reduction of non-plausible areas using the Basis-DLM and the digital terrain model of Germany (Geobasisdaten: © GeoBasis-DE / BKG, 2015).

The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the provided URL to the datasets (right click on the respective data set --> “copy link address”). By doing so the entire map area or only the regions of interest can be accessed. QGIS legend files for data visualization can be downloaded separately.

Class-specific accuracies for each year are proveded in the respective tables. We provide this dataset "as is" without any warranty regarding the accuracy or completeness and exclude all liability.

References:

Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P. (2022). Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sensing of Environment, 269, 112831.

BKG, Bundesamt für Kartographie und Geodäsie (2015). Digitales Geländemodell Gitterweite 10 m. DGM10. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/dgm10.pdf (last accessed: 28. April 2022).

BKG, Bundesamt für Kartographie und Geodäsie (2020). Digitales Basis-Landschaftsmodell.
https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/basis-dlm.pdf (last accessed: 28. April 2022).

Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.

Statistisches Bundesamt, Deutschland (2024). Ökosystematlas Deutschland
https://oekosystematlas-ugr.destatis.de/ (last accessed: 08.02.2024).

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National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) © 2024 by Schwieder, Marcel; Tetteh, Gideon Okpoti; Blickensdörfer, Lukas; Gocht, Alexander; Erasmi, Stefan; licensed under CC BY 4.0.

Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (MonViA, Monitoring of biodiversity in agricultural landscapes).

The study was financially supported by the European Environment Agency and the European Union’s Horizon Europe Research and Innovation programme under Grant Agreement No 101060423 (LAMASUS).

WORKING VERSION. All layers are visible in this linked webgis app along with estimated error. The layers available in this dataset are in a WGS84 geographic coordinate reference system (EPSG:4326) where latitude and longitude coordinates at 0.0008983 degrees ground sampling distance per cell, which corresponds to about 1 ha, i.e. ~100 m x ~100 m at the equator, but decreases in area with increasing latitude as the coordinate system is not equal-area, e.g. ~70 m at 45° latitude and ~50 m at 60° latitude. Aspect.tif, slope.tif and elevation.tif represent Earth surface morphology biomass2020fireres.tif - Biomass values at year 2020 Mg/ha CanopyBulkDensity.tif - Amount of canopy biomass per volume of canopy (kg/m³) CanopyBaseHeight.tif - Height of lower canopy from the ground (m) CanopyHeight.tif - Total height of canopy from the ground (m) Fuel Model FuelModelClasses_ScottBurgan.tif - the category of Fuel Model according to Scott&Burgan 2005 FuelModelClasses_Aragonese.tif - the category of Fuel Model according to Aragonese et al. 2023 DOI: 10.5194/essd-15-1287-2023 - values are from 1 to 24, with a Look Up Table for correspondence (values are ordered matching the order in table 1 of the article) . FuelModelClasses_ScottBurgan.clr/qml CLR/QML - style file for QGIS FuelModelClasses_Aragonese.clr/qml CLR/QML - style file for QGIS FuelModelPercent - the percent of fuel model category belonging to that pixel, between 0 and 100 FuelModelAllPerc - multi-band raster with percent of each fuel model category to belong to each pixel.

Data acquired in Australia through the EU Horizon2020 MSCA-Global fellowship by Dr Eusun Han, project number 884364.

Funding: EU Horizon 2020, MSCA-IF (SenseFuture: 884364)

High-resolution RGB, multispectral, and thermal drone imagery from the Iandra field site (2021–2023), supporting crop monitoring, grazing trials, and digital agronomy research.

FULL DESCRIPTION

This dataset contains raw and processed UAV imagery collected at the CSIRO Iandra field site (Greenethorpe, NSW) as part of the SenseFuture: Novel Agronomy for Resilient Farming Systems project. The imagery captures crop and pasture responses to experimental treatments (including grazing, mowing, and plot management) over multiple growing seasons.

The Iandra field site, located at Iandra Castle near Greenethorpe, NSW, is a key CSIRO farming systems research site. It hosts long-term experiments evaluating crop sequences, soil health, and water use efficiency under varying management practices. Trials include wheat–canola rotations and integration of legumes such as fababean to improve nitrogen fixation and sustainability. The site combines small-plot trials with farm-scale demonstrations and provides critical data on productivity, soil fertility, and system resilience in southern NSW.

The dataset includes flights taken with different sensor configurations:

RGB imagery collected using a DJI Phantom 4 Pro at ~30 m altitude, providing high-resolution (centimetre scale) orthomosaics. Multispectral imagery from a Micasense camera, used to generate reflectance-calibrated bands and vegetation indices (e.g. NDVI, NDRE). Thermal imagery from DJI M2EA test flights, used to explore canopy temperature variation.

TEMPORAL COVERAGE

June–September 2021 (pre-grazing, post-grazing, mowing, and multiple growth stages) July–September 2022 (RGB and thermal test flights) 2023 imagery [details to confirm]

SPATIAL COVERAGE

Iandra research trial, near Greenethorpe, NSW, Australia Approx. 34°31′21.698″ S, 148°18′6.484″ E (WGS84) Experimental plots within grazing and cropping trials.

FILE CONTENTS

The collection contains: Raw project files (.p4d) for Pix4DMapper workflows Processed reports (.pdf) describing Pix4D processing outputs and quality checks Stitched datasets (.zip archives, 15–70 GB each) containing orthomosaics, reflectance maps, and metadata Ancillary GIS outputs for integration into QGIS and other geospatial software

See files for more information. Lineage: Flights were conducted at key crop growth stages during 2021–2023. Imagery was processed using Pix4DMapper to generate orthomosaics and vegetation indices, with quality reports included. GIS layers were prepared for integration into QGIS. File sizes range from 100 MB (thermal) to ~70 GB (RGB orthomosaics).