88438fae-9fe5-4f55-9f4d-1a73778bf62c English Dataset German Aerospace Center (DLR) geoservice@dlr.de 2025-07-01T07:24:43 ISO 19115-1:2014/19139 564339 ETRS89 / UTM Zone 32N (EPSG:25832) HedgeRows - Bavaria, 2019-2021 2025-07-01T09:00:00 https://geoservice.dlr.de/catalogue/srv/metadata/88438fae-9fe5-4f55-9f4d-1a73778bf62c Hedgerows play an important role in maintaining biodiversity, carbon sequestration, soil stability and the ecological integrity of agricultural landscapes. In this dataset, hedgerows are mapped for the whole of Bavaria. Orthophotos with a spatial resolution of 20 cm, taken in the period from 2019 to 2021, were used in a deep learning approach. Hedgerow polygons of the Bavarian in-situ biotope mapping from 5 districts (Miltenberg, Hassberge, Dillingen a.d. Donau, Freyung-Grafenau, Weilheim-Schongau) as well as other manually digitized polygons were used for training and testing as input into a DeepLabV3 Convolutional Neural Network (CNN). The CNN has a Resnet50 backbone and was optimized with the Dice loss as a cost function. The generated hedgerow probability tiles were post-processed by merging and averaging the overlapping tile boundaries, shape simplification and filtering. For more details, see Huber Garcia et al. (2025). The dataset has been created within the project FPCUP (https://www.copernicus-user-uptake.eu/) in close cooperation with Bayerisches Landesamt für Umwelt (LfU). The hedgerow dataset can form a data basis for informed decision making and for scientific applications in the field of sustainable agriculture and ecology. German Aerospace Center (DLR) ursula.gessner@dlr.de German Aerospace Center (DLR) Verena.HuberGarcia@dlr.de German Aerospace Center (DLR) geoservice@dlr.de https://geoservice.dlr.de/catalogue/srv/api/records/88438fae-9fe5-4f55-9f4d-1a73778bf62c/attachments/hedgerows_ql.jpg large_thumbnail https://geoservice.dlr.de/catalogue/srv/api/records/88438fae-9fe5-4f55-9f4d-1a73778bf62c/attachments/hedgerows_ql_s.jpg thumbnail Land cover GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.local.theme.inspire-theme Regional Spatial scope 2024-05-23 geonetwork.thesaurus.external.place.SpatialScope.en DLR EOC opendata Hedges Hedgerows Habitats Linear Woody Vegetation High-Diversity Landscape Features Biotopes Orthophotos CNN DeepLabV3 Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use. There are no limitations on public access to spatial data sets and services. Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by/4.0/ Terms of use: License, https://creativecommons.org/licenses/by/4.0/ {"id": "cc-by-4.0", "name": "Creative-Commons - Attribution 4.0 International (CC BY 4.0)", "url": "http://dcat-ap.de/def/licenses/cc-by/4.0", "quelle": "Copyright DLR (year of production)"} English farming 8.96 12.85 47.26 50.56 2019-04-01T00:00:00 2021-10-01T00:00:00 Geopackage https://geoservice.dlr.de/eoc/land/wms? OGC:WMS HEDGEROWS_BY_2019_2021 EOC Land Map Service https://download.geoservice.dlr.de/HEDGEROWS/files WWW:LINK-1.0-http--link HTTP Download https://geoservice.dlr.de/web/datasets/hedgerows_by EOC Geoservice Dataset EOC Geoservice Dataset DOI: 10.1016/j.rsase.2025.101451 WWW:LINK-1.0-http--link Scientific publication Scientific publication Conformity_001 INSPIRE Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification. true RGB orthophotos with a spatial resolution of 20 cm were used as earth observation data, which were taken between April 2019 and September 2021 by the Bavarian State Office for Digitization, Highspeed Internet and Surveying. Hedgerow data from the federal biotope mapping of the Bavarian Environmental Agency as well as manually digitalized hedgerow shapes are used for training, validation and testing. Processing: Orthophotos and hedgerow shapes were used in a CNN model to predict hedgerow objects. For details of preprocessing see Huber Garcia et al. (2025). Quality Assurance: A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively base on 3732 image tiles in the districts Freyung-Grafenau, Miltenberg, Hassberge, Dillingen and Weilheim-Schongau. The accuracy assessment is described in detail in Huber Garcia et al. (2025)