Potential of Sentinel-1 Data for Monitoring Temperate Mixed Forest Phenology

Remote Sensing

Thuy Le Toan¹  Thierry Koleck¹  Ludovic Villard¹  Kamel Soudani²  Eric Dufrêne²  Pierre-Louis Frison³  Jean-Paul Rudant³  Bénédicte Fruneau³  Syrine Kmiha³  Eric Mougin⁴ 

[1] CESBIO, UMR 5126, CNRS/CNES/UPS/IRD, 18 av. Edouard Belin, bpi 2801, 31401 Toulouse CEDEX 9, France;Ecologie Systématique Evolution, University of Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, F-91400 Orsay, France;LaSTIG/MATIS, Université Paris-Est, IGN, 5 Bd Descartes, Champs sur Marne, 77455 Marne la Vallée CEDEX 2, France;Observatoire Midi-Pyrénées—Géosciences Environnement Toulouse, UMR 5563, CNRS/IRD/UPS, 14 av. E. Belin, 31400 Toulouse, France;

关键词: seasonal monitoring;    temperate mixed forest;    SAR;    Sentinel-1;    radar backscattering coefficient;    interferometric coherence;   

DOI  :  10.3390/rs10122049

来源: DOAJ

【 摘 要 】

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, σ⁰ and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as in situ 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, ${\sigma }_{VV}^0/{\sigma }_{VH}^0$ , showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (r = 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.

【 授权许可】

Unknown