Fusion of Sentinel-1 with Official Topographic and Cadastral Geodata for Crop-Type Enriched LULC Mapping Using FOSS and Open Data
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| Title: | Main Title: Fusion of Sentinel-1 with Official Topographic and Cadastral Geodata for Crop-Type Enriched LULC Mapping Using FOSS and Open Data |
| Description: | Abstract: Accurate crop-type maps are urgently needed as input data for various applications, leading to improved planning and more sustainable use of resources. Satellite remote sensing is the optimal tool to provide such data. Images from Synthetic Aperture Radar (SAR) satellite sensors are preferably used as they work regardless of cloud coverage during image acquisition. However, processing of SAR is more complicated and the sensors have development potential. Dealing with such a complexity, current studies should aim to be reproducible, open, and built upon free and open-source software (FOSS). Thereby, the data can be reused to develop and validate new algorithms or improve the ones already in use. This paper presents a case study of crop classification from microwave remote sensing, relying on open data and open software only. We used 70 multitemporal microwave remote sensing images from the Sentinel-1 satellite. A high-resolution, high-precision digital elevation model (DEM) assisted the preprocessing. The multi-data approach (MDA) was used as a framework enabling to demonstrate the benefits of including external cadastral data. It was used to identify the agricultural area prior to the classification and to create land use/land cover (LULC) maps which also include the annually changing crop types that are usually missing in official geodata. All the software used in this study is open-source, such as the Sentinel Application Toolbox (SNAP), Orfeo Toolbox, R, and QGIS. The produced geodata, all input data, and several intermediate data are openly shared in a research database. Validation using an independent validation dataset showed a high overall accuracy of 96.7% with differentiation into 11 different crop-classes. |
| Identifier: | https://doi.org/10.3390/ijgi9020120 (DOI) |
| Related Resources: | Describes Dataset https://www.tr32db.uni-koeln.de/data.php?dataID=1845 (URL) Is Derived From Dataset https://www.tr32db.uni-koeln.de/data.php?dataID=1848 (URL) |
Responsible Party
| Creators: | Christoph Hütt (Author), Guido Waldhoff (Author), Georg Bareth (Author) |
| Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 32: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation |
| Publisher: | Multidisciplinary Digital Publishing Institute |
| Publication Year: | 2020 |
Topic
| TR32 Topic: | Land Use |
| Related Subproject: | Z1 |
| Subjects: | Keywords: Land Cover Mapping, SAR, Satellite Data, Remote Sensing Methods |
| Geogr. Information Topic: | Geoscientific Information |
File Details
| Filename: | ijgi-09-00120-v3.pdf |
| Data Type: | Text - Article |
| File Size: | 23.7 MB |
| Date: | Available: 21.02.2020 |
| Mime Type: | application/pdf |
| Data Format: | |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Free |
| Download Information: | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
| General Access and Use Conditions: | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
| Access Limitations: | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
| Licence: | [Creative Commons] Attribution 4.0 International (CC BY 4.0) |
Geographic
Specific Information - Publication
| Publication Status: | Published |
| Review Status: | Peer reviewed |
| Publication Type: | Article |
| Article Type: | Journal |
| Source: | ISPRS International Journal of Geoinformation |
| Source Website: | https://www.mdpi.com/2220-9964/9/2/120/htm |
| Issue: | 2 |
| Volume: | 9 |
| Number of Pages: | 15 (1 - 15) |
Metadata Details
| Metadata Creator: | Christoph Hütt |
| Metadata Created: | 12.06.2020 |
| Metadata Last Updated: | 12.06.2020 |
| Subproject: | Z1 |
| Funding Phase: | 3 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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Dataset Statistics
| Page Visits: | 931 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 6 |
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