Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology
In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/10/12/2049 |
| _version_ | 1828883351852810240 |
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| author | Pierre-Louis Frison Bénédicte Fruneau Syrine Kmiha Kamel Soudani Eric Dufrêne Thuy Le Toan Thierry Koleck Ludovic Villard Eric Mougin Jean-Paul Rudant |
| author_facet | Pierre-Louis Frison Bénédicte Fruneau Syrine Kmiha Kamel Soudani Eric Dufrêne Thuy Le Toan Thierry Koleck Ludovic Villard Eric Mougin Jean-Paul Rudant |
| author_sort | Pierre-Louis Frison |
| collection | DOAJ |
| description | In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering coefficients, <i>σ</i><sup>0</sup> and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as <i>in situ</i> precipitation and air temperature. The high temporal frequency of Sentinel-1 acquisitions (i.e., twelve days, or six, if both Sentinel-1A and B are combined over Europe) and the dual polarization configuration (VV and VH over most land surfaces) made a significant contribution. In particular, the radar backscattering coefficient ratio of VV to VH polarization, <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>σ</mi> <mrow> <mi>V</mi> <mi>V</mi> </mrow> <mn>0</mn> </msubsup> <mo>/</mo> <msubsup> <mi>σ</mi> <mrow> <mi>V</mi> <mi>H</mi> </mrow> <mn>0</mn> </msubsup> </mrow> </semantics> </math> </inline-formula>, showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (<i>r</i> = 0.77) over stands of deciduous trees. These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than optical data. These observations will be quantitatively analyzed with the use of electromagnetic models in the near future. |
| first_indexed | 2024-12-13T10:46:55Z |
| format | Article |
| id | doaj.art-d88d0f66f71043a8bac6d66cdc238b66 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:46:55Z |
| publishDate | 2018-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d88d0f66f71043a8bac6d66cdc238b662022-12-21T23:50:06ZengMDPI AGRemote Sensing2072-42922018-12-011012204910.3390/rs10122049rs10122049Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest PhenologyPierre-Louis Frison0Bénédicte Fruneau1Syrine Kmiha2Kamel Soudani3Eric Dufrêne4Thuy Le Toan5Thierry Koleck6Ludovic Villard7Eric Mougin8Jean-Paul Rudant9LaSTIG/MATIS, Université Paris-Est, IGN, 5 Bd Descartes, Champs sur Marne, 77455 Marne la Vallée CEDEX 2, FranceLaSTIG/MATIS, Université Paris-Est, IGN, 5 Bd Descartes, Champs sur Marne, 77455 Marne la Vallée CEDEX 2, FranceLaSTIG/MATIS, Université Paris-Est, IGN, 5 Bd Descartes, Champs sur Marne, 77455 Marne la Vallée CEDEX 2, FranceEcologie Systématique Evolution, University of Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, F-91400 Orsay, FranceEcologie Systématique Evolution, University of Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, F-91400 Orsay, FranceCESBIO, UMR 5126, CNRS/CNES/UPS/IRD, 18 av. Edouard Belin, bpi 2801, 31401 Toulouse CEDEX 9, FranceCESBIO, UMR 5126, CNRS/CNES/UPS/IRD, 18 av. Edouard Belin, bpi 2801, 31401 Toulouse CEDEX 9, FranceCESBIO, UMR 5126, CNRS/CNES/UPS/IRD, 18 av. Edouard Belin, bpi 2801, 31401 Toulouse CEDEX 9, FranceObservatoire Midi-Pyrénées—Géosciences Environnement Toulouse, UMR 5563, CNRS/IRD/UPS, 14 av. E. Belin, 31400 Toulouse, FranceLaSTIG/MATIS, Université Paris-Est, IGN, 5 Bd Descartes, Champs sur Marne, 77455 Marne la Vallée CEDEX 2, FranceIn this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering coefficients, <i>σ</i><sup>0</sup> and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as <i>in situ</i> precipitation and air temperature. The high temporal frequency of Sentinel-1 acquisitions (i.e., twelve days, or six, if both Sentinel-1A and B are combined over Europe) and the dual polarization configuration (VV and VH over most land surfaces) made a significant contribution. In particular, the radar backscattering coefficient ratio of VV to VH polarization, <inline-formula> <math display="inline"> <semantics> <mrow> <msubsup> <mi>σ</mi> <mrow> <mi>V</mi> <mi>V</mi> </mrow> <mn>0</mn> </msubsup> <mo>/</mo> <msubsup> <mi>σ</mi> <mrow> <mi>V</mi> <mi>H</mi> </mrow> <mn>0</mn> </msubsup> </mrow> </semantics> </math> </inline-formula>, showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (<i>r</i> = 0.77) over stands of deciduous trees. These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than optical data. These observations will be quantitatively analyzed with the use of electromagnetic models in the near future.https://www.mdpi.com/2072-4292/10/12/2049seasonal monitoringtemperate mixed forestSARSentinel-1radar backscattering coefficientinterferometric coherence |
| spellingShingle | Pierre-Louis Frison Bénédicte Fruneau Syrine Kmiha Kamel Soudani Eric Dufrêne Thuy Le Toan Thierry Koleck Ludovic Villard Eric Mougin Jean-Paul Rudant Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology Remote Sensing seasonal monitoring temperate mixed forest SAR Sentinel-1 radar backscattering coefficient interferometric coherence |
| title | Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology |
| title_full | Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology |
| title_fullStr | Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology |
| title_full_unstemmed | Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology |
| title_short | Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology |
| title_sort | potential of sentinel 1 data for monitoring temperate mixed forest phenology |
| topic | seasonal monitoring temperate mixed forest SAR Sentinel-1 radar backscattering coefficient interferometric coherence |
| url | https://www.mdpi.com/2072-4292/10/12/2049 |
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