scholarly journals Potential of Synthetic Aperture Radar Sentinel-1 time series for the monitoring of phenological cycles in a deciduous forest

2021 ◽  
Author(s):  
Kamel Soudani ◽  
Nicolas Delpierre ◽  
Daniel Berveiller ◽  
Gabriel Hmimina ◽  
Gaëlle Vincent ◽  
...  

AbstractAnnual time-series of the two satellites C-band SAR (Synthetic Aperture Radar) Sentinel-1 A and B data over five years were used to characterize the phenological cycle of a temperate deciduous forest. Six phenological markers of the start, middle and end of budburst and leaf expansion stage in spring and the leaf senescence in autumn were extracted from time-series of the ratio (VV/VH) of backscattering at co-polarization VV (vertical-vertical) and at cross polarization VH (vertical-horizontal). These markers were compared to field phenological observations, and to phenological dates derived from various proxies (Normalized Difference Vegetation Index NDVI time-series from Sentinel-2 A and B images, in situ NDVI measurements, Leaf Area Index LAI and litterfall temporal dynamics). We observe a decrease in the backscattering coefficient (σ0) at VH cross polarization during the leaf development and expansion phase in spring and an increase during the senescence phase, contrary to what is usually observed on various types of crops. In vertical polarization, σ0VV shows very little variation throughout the year. S-1 time series of VV/VH ratio provides a good description of the seasonal vegetation cycle allowing the estimation of spring and autumn phenological markers. Estimates provided by VV/VH of budburst dates differ by approximately 8 days on average from phenological observations. During senescence phase, estimates are positively shifted (later) and deviate by about 20 days from phenological observations of leaf senescence while the differences are of the order of 2 to 4 days between the phenological observations and estimates based on in situ NDVI and LAI time-series, respectively. A deviation of about 7 days, comparable to that observed during budburst, is obtained between the estimates of senescence from S-1 and those determined from the in situ monitoring of litterfall. While in spring, leaf emergence and expansion described by LAI or NDVI explains the increase of VV/VH (or the decrease of σ0VH), during senescence, S-1 VV/VH is decorrelated from LAI or NDVI and is better explained by litterfall temporal dynamics. This behavior resulted in a hysteresis phenomenon observed on the relationships between VV/VH and NDVI or LAI. For the same LAI or NDVI, the response of VV/VH is different depending on the phenological phase considered. This study shows the high potential offered by Sentinel-1 SAR C-band time series for the detection of forest phenology for the first time, thus overcoming the limitations caused by cloud cover in optical remote sensing of vegetation phenology.HighlightsWe study S-1 C-band dual polarized data potential to predict forest phenologySeasonal phenological transitions were accurately described by S-1 time-seriesBudburst and senescence dates from S-1 differ from direct observations by one weekTime-series of S-1 VV/VH, NDVI, LAI and litterfall were also comparedRelationships VV/VH vs NDVI and LAI show a hysteresis according to the season

2014 ◽  
Vol 41 (17) ◽  
pp. 6123-6130 ◽  
Author(s):  
Sergey V. Samsonov ◽  
Alexander P. Trishchenko ◽  
Kristy Tiampo ◽  
Pablo J. González ◽  
Yu Zhang ◽  
...  

Author(s):  
Roberta Bonì ◽  
Claudia Meisina ◽  
Linda Poggio ◽  
Alessandro Fontana ◽  
Giulia Tessari ◽  
...  

Abstract. In this work, an innovative methodology to generate the automatic ground motion areas mapping is presented. The methodology is based on the analysis of the Synthetic Aperture Radar (SAR)-based displacement time series. The procedure includes two modules developed using the ModelBuilder tool (ArcGis). These modules allow to identify the ground motion areas (GMA) using only one dataset and the persistent GMA (PGMA) considering the different monitored periods and datasets. These areas represent clusters of targets characterized by the same displacement time series trend. The procedure was tested using different sensors such as ERS-1/2, ENVISAT, COSMO-SkyMed and Sentinel-1 covering the periods, 1992–2000, 2003–2010, 2012–2016 and 2014–2017, respectively, over an area of about 500 km2 in the Venetian-Friulian coastal Plain (NE Italy). The resulting mapping allows to detect priority areas where to address further in situ investigations such as to verify the presence of localized buried landforms.


2020 ◽  
Vol 12 (23) ◽  
pp. 3970
Author(s):  
Antonio Sánchez-Román ◽  
Ananda Pascual ◽  
Marie-Isabelle Pujol ◽  
Guillaume Taburet ◽  
Marta Marcos ◽  
...  

The quality of the Data Unification and Altimeter Combination System (DUACS) Sentinel-3A altimeter data in the coastal area of the European seas is investigated through a comparison with in situ tide gauge measurements. The comparison was also conducted using altimetry data from Jason-3 for inter-comparison purposes. We found that Sentinel-3A improved the root mean square differences (RMSD) by 13% with respect to the Jason-3 mission. In addition, the variance in the differences between the two datasets was reduced by 25%. To explain the improved capture of Sea Level Anomaly by Sentinel-3A in the coastal band, the impact of the measurement noise on the synthetic aperture radar altimeter, the distance to the coast, and Long Wave Error correction applied on altimetry data were checked. The results confirmed that the synthetic aperture radar altimeter instrument onboard the Sentinel-3A mission better solves the signal in the coastal band. Moreover, the Long Wave Error processing contributes to reduce the errors in altimetry, enhancing the consistency between the altimeter and in situ datasets.


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