Articles | Volume 14, issue 1
https://doi.org/10.5194/essd-14-295-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-295-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Jan 2022
Data description paper |
| 27 Jan 2022
| 27 Jan 2022
A national extent map of cropland and grassland for Switzerland based on Sentinel-2 data
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Nica Huber
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Dominique Weber
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Christian Ginzler
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Bronwyn Price
Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
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Cited
13 citations as recorded by crossref.
- Reconciling cities with nature: Identifying local Blue-Green Infrastructure interventions for regional biodiversity enhancement G. Donati et al. 10.1016/j.jenvman.2022.115254
- Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review R. Vidican et al. 10.3390/agronomy13123040
- Regional-scale cotton yield forecast via data-driven spatio-temporal prediction (STP) of solar-induced chlorophyll fluorescence (SIF) X. Kang et al. 10.1016/j.rse.2023.113861
- Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network X. Kang et al. 10.1016/j.compag.2022.107260
- The Habitat Map of Switzerland: A Remote Sensing, Composite Approach for a High Spatial and Thematic Resolution Product B. Price et al. 10.3390/rs15030643
- Countrywide classification of permanent grassland habitats at high spatial resolution N. Huber et al. 10.1002/rse2.298
- Automated In-Season Crop-Type Data Layer Mapping Without Ground Truth for the Conterminous United States Based on Multisource Satellite Imagery H. Li et al. 10.1109/TGRS.2024.3361895
- Propagating Sentinel-2 Top-of-Atmosphere Radiometric Uncertainty Into Land Surface Phenology Metrics Using a Monte Carlo Framework L. Graf et al. 10.1109/JSTARS.2023.3297713
- Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau Y. Zeng et al. 10.1038/s41597-024-03198-z
- The 10-m cotton maps in Xinjiang, China during 2018–2021 X. Kang et al. 10.1038/s41597-023-02584-3
- Exploring Switzerland’s Land Cover Change Dynamics Using a National Statistical Survey I. Thomas & G. Giuliani 10.3390/land12071386
- A national extent map of cropland and grassland for Switzerland based on Sentinel-2 data R. Pazúr et al. 10.5194/essd-14-295-2022
- EcoDes-DK15: high-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set J. Assmann et al. 10.5194/essd-14-823-2022
11 citations as recorded by crossref.
- Reconciling cities with nature: Identifying local Blue-Green Infrastructure interventions for regional biodiversity enhancement G. Donati et al. 10.1016/j.jenvman.2022.115254
- Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review R. Vidican et al. 10.3390/agronomy13123040
- Regional-scale cotton yield forecast via data-driven spatio-temporal prediction (STP) of solar-induced chlorophyll fluorescence (SIF) X. Kang et al. 10.1016/j.rse.2023.113861
- Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network X. Kang et al. 10.1016/j.compag.2022.107260
- The Habitat Map of Switzerland: A Remote Sensing, Composite Approach for a High Spatial and Thematic Resolution Product B. Price et al. 10.3390/rs15030643
- Countrywide classification of permanent grassland habitats at high spatial resolution N. Huber et al. 10.1002/rse2.298
- Automated In-Season Crop-Type Data Layer Mapping Without Ground Truth for the Conterminous United States Based on Multisource Satellite Imagery H. Li et al. 10.1109/TGRS.2024.3361895
- Propagating Sentinel-2 Top-of-Atmosphere Radiometric Uncertainty Into Land Surface Phenology Metrics Using a Monte Carlo Framework L. Graf et al. 10.1109/JSTARS.2023.3297713
- Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau Y. Zeng et al. 10.1038/s41597-024-03198-z
- The 10-m cotton maps in Xinjiang, China during 2018–2021 X. Kang et al. 10.1038/s41597-023-02584-3
- Exploring Switzerland’s Land Cover Change Dynamics Using a National Statistical Survey I. Thomas & G. Giuliani 10.3390/land12071386
2 citations as recorded by crossref.
- A national extent map of cropland and grassland for Switzerland based on Sentinel-2 data R. Pazúr et al. 10.5194/essd-14-295-2022
- EcoDes-DK15: high-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set J. Assmann et al. 10.5194/essd-14-823-2022
Latest update: 26 Apr 2024
Short summary
We mapped the distribution of cropland and permanent grassland across Switzerland, where the agricultural land is considerably spatially heterogeneous due to strong variability in topography and climate, thus presenting challenges to mapping. The resulting map has high accuracy in lowlands as well as in mountainous areas. Thus, we believe that the presented mapping approach and resulting map will provide a solid ground for further research in agricultural land cover and landscape structure.
We mapped the distribution of cropland and permanent grassland across Switzerland, where the...
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