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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Bibliographic Details
Main Authors: Pierre-Louis Frison, Bénédicte Fruneau, Syrine Kmiha, Kamel Soudani, Eric Dufrêne, Thuy Le Toan, Thierry Koleck, Ludovic Villard, Eric Mougin, Jean-Paul Rudant
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/10/12/2049
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Summary: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>&#963;</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>&#963;</mi> <mrow> <mi>V</mi> <mi>V</mi> </mrow> <mn>0</mn> </msubsup> <mo>/</mo> <msubsup> <mi>&#963;</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.
ISSN:2072-4292