Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria
The monitoring of crops is of vital importance for food and environmental security in a global and European context. The main goal of this study was to assess the crop mapping performance provided by the 100 m spatial resolution of PROBA-V compared to coarser resolution data (e.g., PROBA-V at 300 m)...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-10-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/7/10/13843 |
| _version_ | 1798025787764375552 |
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| author | Eugenia Roumenina Clement Atzberger Vassil Vassilev Petar Dimitrov Ilina Kamenova Martin Banov Lachezar Filchev Georgi Jelev |
| author_facet | Eugenia Roumenina Clement Atzberger Vassil Vassilev Petar Dimitrov Ilina Kamenova Martin Banov Lachezar Filchev Georgi Jelev |
| author_sort | Eugenia Roumenina |
| collection | DOAJ |
| description | The monitoring of crops is of vital importance for food and environmental security in a global and European context. The main goal of this study was to assess the crop mapping performance provided by the 100 m spatial resolution of PROBA-V compared to coarser resolution data (e.g., PROBA-V at 300 m) for a 2250 km2 test site in Bulgaria. The focus was on winter and summer crop mapping with three to five classes. For classification, single- and multi-date spectral data were used as well as NDVI time series. Our results demonstrate that crop identification using 100 m PROBA-V data performed significantly better in all experiments compared to the PROBA-V 300 m data. PROBA-V multispectral imagery, acquired in spring (March) was the most appropriate for winter crop identification, while satellite data acquired in summer (July) was superior for summer crop identification. The classification accuracy from PROBA-V 100 m compared to PROBA-V 300 m was improved by 5.8% to 14.8% depending on crop type. Stacked multi-date satellite images with three to four images gave overall classification accuracies of 74%–77% (PROBA-V 100 m data) and 66%–70% (PROBA-V 300 m data) with four classes (wheat, rapeseed, maize, and sunflower). This demonstrates that three to four image acquisitions, well distributed over the growing season, capture most of the spectral and temporal variability in our test site. Regarding the PROBA-V NDVI time series, useful results were only obtained if crops were grouped into two broader crop type classes (summer and winter crops). Mapping accuracies decreased significantly when mapping more classes. Again, a positive impact of the increased spatial resolution was noted. Together, the findings demonstrate the positive effect of the 100 m resolution PROBA-V data compared to the 300 m for crop mapping. This has important implications for future data provision and strengthens the arguments for a second generation of this mission originally designed solely as a “gap-filler mission”. |
| first_indexed | 2024-04-11T18:25:33Z |
| format | Article |
| id | doaj.art-a6b8fe440df3431a829b7e4bab7394b3 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T18:25:33Z |
| publishDate | 2015-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-a6b8fe440df3431a829b7e4bab7394b32022-12-22T04:09:39ZengMDPI AGRemote Sensing2072-42922015-10-01710138431386210.3390/rs71013843rs71013843Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, BulgariaEugenia Roumenina0Clement Atzberger1Vassil Vassilev2Petar Dimitrov3Ilina Kamenova4Martin Banov5Lachezar Filchev6Georgi Jelev7Space Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaInstitute of Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences, Vienna (BOKU), 1180 Wien, AustriaSpace Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaSpace Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaSpace Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaInstitute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1080 Sofia, BulgariaSpace Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaSpace Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), 1113 Sofia, BulgariaThe monitoring of crops is of vital importance for food and environmental security in a global and European context. The main goal of this study was to assess the crop mapping performance provided by the 100 m spatial resolution of PROBA-V compared to coarser resolution data (e.g., PROBA-V at 300 m) for a 2250 km2 test site in Bulgaria. The focus was on winter and summer crop mapping with three to five classes. For classification, single- and multi-date spectral data were used as well as NDVI time series. Our results demonstrate that crop identification using 100 m PROBA-V data performed significantly better in all experiments compared to the PROBA-V 300 m data. PROBA-V multispectral imagery, acquired in spring (March) was the most appropriate for winter crop identification, while satellite data acquired in summer (July) was superior for summer crop identification. The classification accuracy from PROBA-V 100 m compared to PROBA-V 300 m was improved by 5.8% to 14.8% depending on crop type. Stacked multi-date satellite images with three to four images gave overall classification accuracies of 74%–77% (PROBA-V 100 m data) and 66%–70% (PROBA-V 300 m data) with four classes (wheat, rapeseed, maize, and sunflower). This demonstrates that three to four image acquisitions, well distributed over the growing season, capture most of the spectral and temporal variability in our test site. Regarding the PROBA-V NDVI time series, useful results were only obtained if crops were grouped into two broader crop type classes (summer and winter crops). Mapping accuracies decreased significantly when mapping more classes. Again, a positive impact of the increased spatial resolution was noted. Together, the findings demonstrate the positive effect of the 100 m resolution PROBA-V data compared to the 300 m for crop mapping. This has important implications for future data provision and strengthens the arguments for a second generation of this mission originally designed solely as a “gap-filler mission”.http://www.mdpi.com/2072-4292/7/10/13843PROBA-Vsingle- and multi-date crop identificationNDVI time seriescluster analysisGSD |
| spellingShingle | Eugenia Roumenina Clement Atzberger Vassil Vassilev Petar Dimitrov Ilina Kamenova Martin Banov Lachezar Filchev Georgi Jelev Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria Remote Sensing PROBA-V single- and multi-date crop identification NDVI time series cluster analysis GSD |
| title | Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria |
| title_full | Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria |
| title_fullStr | Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria |
| title_full_unstemmed | Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria |
| title_short | Single- and Multi-Date Crop Identification Using PROBA-V 100 and 300 m S1 Products on Zlatia Test Site, Bulgaria |
| title_sort | single and multi date crop identification using proba v 100 and 300 m s1 products on zlatia test site bulgaria |
| topic | PROBA-V single- and multi-date crop identification NDVI time series cluster analysis GSD |
| url | http://www.mdpi.com/2072-4292/7/10/13843 |
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