Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring
The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | http://www.mdpi.com/2220-9964/7/10/405 |
| _version_ | 1811286785997668352 |
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| author | Urška Kanjir Nataša Đurić Tatjana Veljanovski |
| author_facet | Urška Kanjir Nataša Đurić Tatjana Veljanovski |
| author_sort | Urška Kanjir |
| collection | DOAJ |
| description | The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase. |
| first_indexed | 2024-04-13T03:07:05Z |
| format | Article |
| id | doaj.art-fddeff2537e441d2af79e63f288b596f |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-04-13T03:07:05Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-fddeff2537e441d2af79e63f288b596f2022-12-22T03:05:14ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-10-0171040510.3390/ijgi7100405ijgi7100405Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy MonitoringUrška Kanjir0Nataša Đurić1Tatjana Veljanovski2Research Centre of the Slovenian Academy of Sciences and Arts, Novi trg 2, 1000 Ljubljana, SloveniaSlovenian Centre of Excellence for Space Science and Technologies SPACE-SI, Aškerčeva cesta 12, 1000 Ljubljana, SloveniaResearch Centre of the Slovenian Academy of Sciences and Arts, Novi trg 2, 1000 Ljubljana, SloveniaThe European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase.http://www.mdpi.com/2220-9964/7/10/405crop monitoringtime series analysisNDVI object-based temporal profileschange detectionpermanent meadowsarable fieldsGEOBIA |
| spellingShingle | Urška Kanjir Nataša Đurić Tatjana Veljanovski Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring ISPRS International Journal of Geo-Information crop monitoring time series analysis NDVI object-based temporal profiles change detection permanent meadows arable fields GEOBIA |
| title | Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring |
| title_full | Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring |
| title_fullStr | Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring |
| title_full_unstemmed | Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring |
| title_short | Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring |
| title_sort | sentinel 2 based temporal detection of agricultural land use anomalies in support of common agricultural policy monitoring |
| topic | crop monitoring time series analysis NDVI object-based temporal profiles change detection permanent meadows arable fields GEOBIA |
| url | http://www.mdpi.com/2220-9964/7/10/405 |
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