Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe
The difficulty of calculating the daily water budget of irrigated fields is often due to the uncertainty surrounding irrigation amounts and timing. The automated detection of irrigation events has the potential to greatly simplify this process, and the combination of high-resolution SAR (Sentinel-1)...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/5/1449 |
| _version_ | 1797614439167426560 |
|---|---|
| author | Michel Le Page Thang Nguyen Mehrez Zribi Aaron Boone Jacopo Dari Sara Modanesi Luca Zappa Nadia Ouaadi Lionel Jarlan |
| author_facet | Michel Le Page Thang Nguyen Mehrez Zribi Aaron Boone Jacopo Dari Sara Modanesi Luca Zappa Nadia Ouaadi Lionel Jarlan |
| author_sort | Michel Le Page |
| collection | DOAJ |
| description | The difficulty of calculating the daily water budget of irrigated fields is often due to the uncertainty surrounding irrigation amounts and timing. The automated detection of irrigation events has the potential to greatly simplify this process, and the combination of high-resolution SAR (Sentinel-1) and optical satellite observations (Sentinel-2) makes the detection of irrigation events feasible through the use of a surface soil moisture (SSM) product. The motivation behind this study is to utilize a large irrigation dataset (collected during the ESA Irrigation + project over five sites in three countries over three years) to analyze the performance of an established algorithm and to test potential improvements. The study’s main findings are (1) the scores decrease with SSM observation frequency; (2) scores decrease as irrigation frequency increases, which was supported by better scores in France (more sprinkler irrigation) than in Germany (more localized irrigation); (3) replacing the original SSM model with the force-restore model resulted in an improvement of about 6% in the F-score and narrowed the error on cumulative seasonal irrigation; (4) the Sentinel-1 configuration (incidence angle, trajectory) did not show a significant impact on the retrieval of irrigation, which supposes that the SSM is not affected by these changes. Other aspects did not allow a definitive conclusion on the irrigation retrieval algorithm: (1) the lower scores obtained with small NDVI compared to large NDVI were counter-intuitive but may have been due to the larger number of irrigation events during high vegetation periods; (2) merging different runs and interpolating all SSM data for one run produced comparable F-scores, but the estimated cumulative sum of irrigation was around −20% lower compared to the reference dataset in the best cases. |
| first_indexed | 2024-03-11T07:11:22Z |
| format | Article |
| id | doaj.art-5b8caaff3d0b419a87702a5c6a1a29ba |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T07:11:22Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5b8caaff3d0b419a87702a5c6a1a29ba2023-11-17T08:33:15ZengMDPI AGRemote Sensing2072-42922023-03-01155144910.3390/rs15051449Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in EuropeMichel Le Page0Thang Nguyen1Mehrez Zribi2Aaron Boone3Jacopo Dari4Sara Modanesi5Luca Zappa6Nadia Ouaadi7Lionel Jarlan8CESBIO, Université de Toulouse, CNRS/UPS/IRD/CNES/INRAE, 18 Avenue Edouard Belin, Bpi 2801, 31401 Toulouse, FranceCESBIO, Université de Toulouse, CNRS/UPS/IRD/CNES/INRAE, 18 Avenue Edouard Belin, Bpi 2801, 31401 Toulouse, FranceCESBIO, Université de Toulouse, CNRS/UPS/IRD/CNES/INRAE, 18 Avenue Edouard Belin, Bpi 2801, 31401 Toulouse, FranceCNRM-Météo-France/CNRS, Université de Toulouse, 42 ave G. Coriolis, 31075 Toulouse, FranceDepartment of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 93, 06125 Perugia, ItalyResearch Institute for Geo-Hydrological Protection, National Research Council, Via Madonna Alta 126, 06128 Perugia, ItalyClimate and Environmental Remote Sensing (CLIMERS) Research Group, Department of Geodesy and Geoinformation, TU Wien, 1040 Vienna, AustriaCESBIO, Université de Toulouse, CNRS/UPS/IRD/CNES/INRAE, 18 Avenue Edouard Belin, Bpi 2801, 31401 Toulouse, FranceCESBIO, Université de Toulouse, CNRS/UPS/IRD/CNES/INRAE, 18 Avenue Edouard Belin, Bpi 2801, 31401 Toulouse, FranceThe difficulty of calculating the daily water budget of irrigated fields is often due to the uncertainty surrounding irrigation amounts and timing. The automated detection of irrigation events has the potential to greatly simplify this process, and the combination of high-resolution SAR (Sentinel-1) and optical satellite observations (Sentinel-2) makes the detection of irrigation events feasible through the use of a surface soil moisture (SSM) product. The motivation behind this study is to utilize a large irrigation dataset (collected during the ESA Irrigation + project over five sites in three countries over three years) to analyze the performance of an established algorithm and to test potential improvements. The study’s main findings are (1) the scores decrease with SSM observation frequency; (2) scores decrease as irrigation frequency increases, which was supported by better scores in France (more sprinkler irrigation) than in Germany (more localized irrigation); (3) replacing the original SSM model with the force-restore model resulted in an improvement of about 6% in the F-score and narrowed the error on cumulative seasonal irrigation; (4) the Sentinel-1 configuration (incidence angle, trajectory) did not show a significant impact on the retrieval of irrigation, which supposes that the SSM is not affected by these changes. Other aspects did not allow a definitive conclusion on the irrigation retrieval algorithm: (1) the lower scores obtained with small NDVI compared to large NDVI were counter-intuitive but may have been due to the larger number of irrigation events during high vegetation periods; (2) merging different runs and interpolating all SSM data for one run produced comparable F-scores, but the estimated cumulative sum of irrigation was around −20% lower compared to the reference dataset in the best cases.https://www.mdpi.com/2072-4292/15/5/1449Europeirrigation timingFAO-56force-restoresurface soil moisture |
| spellingShingle | Michel Le Page Thang Nguyen Mehrez Zribi Aaron Boone Jacopo Dari Sara Modanesi Luca Zappa Nadia Ouaadi Lionel Jarlan Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe Remote Sensing Europe irrigation timing FAO-56 force-restore surface soil moisture |
| title | Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe |
| title_full | Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe |
| title_fullStr | Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe |
| title_full_unstemmed | Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe |
| title_short | Irrigation Timing Retrieval at the Plot Scale Using Surface Soil Moisture Derived from Sentinel Time Series in Europe |
| title_sort | irrigation timing retrieval at the plot scale using surface soil moisture derived from sentinel time series in europe |
| topic | Europe irrigation timing FAO-56 force-restore surface soil moisture |
| url | https://www.mdpi.com/2072-4292/15/5/1449 |
| work_keys_str_mv | AT michellepage irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT thangnguyen irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT mehrezzribi irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT aaronboone irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT jacopodari irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT saramodanesi irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT lucazappa irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT nadiaouaadi irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope AT lioneljarlan irrigationtimingretrievalattheplotscaleusingsurfacesoilmoisturederivedfromsentineltimeseriesineurope |