Development Of Algorithms For The Estimation Of Hydrological Parameters Combining Cosmo-Skymed And Sentinel Time Series With In Situ Measurements

2020 ◽  
Author(s):  
Deodato Tapete ◽  
Francesca Cigna ◽  
Simonetta Paloscia ◽  
Emanuele Santi ◽  
Simone Pettinato ◽  
...  
Keyword(s):  
Time Series ◽  
In Situ Measurements ◽  
Hydrological Parameters

scholarly journals Sentinel-1 SAR Interferometry for Surface Deformation Monitoring in Low-Land Permafrost Areas

2018 ◽  
Vol 10 (9) ◽  
pp. 1360 ◽  
Author(s):  
Tazio Strozzi ◽  
Sofia Antonova ◽  
Frank Günther ◽  
Eva Mätzler ◽  
Gonçalo Vieira ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Displacement ◽  
Deformation Monitoring ◽  
In Situ Measurements ◽  
River Delta ◽  
Sar Interferometry ◽  
The Arctic ◽  
Lena River ◽  
Lena River Delta

Low-land permafrost areas are subject to intense freeze-thaw cycles and characterized by remarkable surface displacement. We used Sentinel-1 SAR interferometry (InSAR) in order to analyse the summer surface displacement over four spots in the Arctic and Antarctica since 2015. Choosing floodplain or outcrop areas as the reference for the InSAR relative deformation measurements, we found maximum subsidence of about 3 to 10 cm during the thawing season with generally high spatial variability. Sentinel-1 time-series of interferograms with 6–12 day time intervals highlight that subsidence is often occurring rather quickly within roughly one month in early summer. Intercomparison of summer subsidence from Sentinel-1 in 2017 with TerraSAR-X in 2013 over part of the Lena River Delta (Russia) shows a high spatial agreement between both SAR systems. A comparison with in-situ measurements for the summer of 2014 over the Lena River Delta indicates a pronounced downward movement of several centimetres in both cases but does not reveal a spatial correspondence between InSAR and local in-situ measurements. For the reconstruction of longer time-series of deformation, yearly Sentinel-1 interferograms from the end of the summer were considered. However, in order to infer an effective subsidence of the surface through melting of excess ice layers over multi-annual scales with Sentinel-1, a longer observation time period is necessary.

Landslide dynamics inferred from in-situ measurements and time series of terrestrial imagery: the Cliets rockslide (Savoie, French Alps)

2020 ◽  
Author(s):  
Mathilde Desrues ◽  
Jean-Philippe Malet ◽  
Ombeline Brenguier ◽  
Aurore Carrier ◽  
Lionel Lorier
Keyword(s):  
Time Series ◽  
Mechanical Behavior ◽  
Optical Sensors ◽  
In Situ Measurements ◽  
Displacement Fields ◽  
Total Station ◽  
French Alps ◽  
Geophysical Surveys ◽  
Landslide Dynamics

<p>Several geodetic methods can be combined to better understand landslide dynamics and behavior. The obtained deformation/displacement fields can be analyzed to inverse the geometry of the moving mass and the mechanical behavior of the slope (kinematic regime, rheological properties of the media), and sometimes anticipate the time of failure. Among them, dense in-situ measurements (total station measurements, extensometer data and GNSS surveys) allow reaching accuracy close to the centimeter. These techniques can be combined to dense time series of passive terrestrial imagery in order to obtain distributed information. Actually, more and more passive optical sensors are used to provide both qualitative information (detection of surface change) and quantitative information using either a single camera (quantification of displacement by correlation techniques) or stereo-views (creation of Digital Surface Models, DSM).</p><p> </p><p>In this study, we analyze a unique dataset of the Cliets rockslide event that occurred on 9 February 2019. The pre-failure and failure stages were documented using the above mentioned methods. The performance of the methods are evaluated in terms of their possible contribution to a monitoring survey.</p><p> </p><p><span>The Cliets landslide is located in the French Alps (Savoie) and is affecting the high traffic road of Gorges de l’Arly. Located upstream of a tunnel, the unstable slope was instrumented by the SAGE Society during the crisis in the period July–February 2019. About 8000 m</span><sup><span>3</span></sup><span> collapsed closing the tunnel access for one year. Topographic measurements of a series of 41 benchmarks by automated total station were used to determined the time of rupture and the landslide mechanical behavior (tertiary creep vs stable regime). Additionally, a fixed CANON EOS 2000D with a lens with a focal length of 24 mm, was installed in front of the landslide. Images were acquired hourly and the time series was processed using the TSM processing toolbox (Desrues et al., 2019). Displacement fields were generated over time and compared to the topographic measurements. Photogrammetric surveys were carried out to generate several DSMs before and after the crisis. It allowed to estimate the volume of the collapsed masses. Finally, geophysical surveys were included in the study to determine the thickness of the potential unstable layer. </span></p><p>The results allow highlighting (1) different kind of behaviors which are identified and explained by a simple physical models, (2) the volumes of the displaced masses, and (3) the absence of a direct relation of the failure with the meterological forcing factors.</p><p> </p><p><span><strong>Acknowledgments</strong></span><span>: These works are part of a CIFRE / ANRT agreement between IPGS/CNRS UMR7516 and the SAGE Society.</span></p>

Towards the removal of model bias from ESA CCI SM by using an L-band scaling reference

2021 ◽  
Author(s):  
Rémi Madelon ◽  
Nemesio Rodriguez-Fernandez ◽  
Robin Van Der Shalie ◽  
Yann Kerr ◽  
Tracy Scalon ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Climate Models ◽  
In Situ Measurements ◽  
Time Data ◽  
Data Set ◽  
Spatial Coverage ◽  
L Band ◽  
Better Than

<p>Merging data from different instruments is required to construct long time data records of soil moisture (SM). This is the goal of projects such as the ESA Climate Change Initiative (CCI) for SM (Gruber et al., 2019), which uses both active and passive microwave sensors. Currently, the GLDAS v2.1 model is used as reference to re-scale active and passive time series by matching their Cumulative Density Function (CDF) to that of the model. Removing the dependency on models is important, in particular for data assimilation applications into hydrological or climate models, and it has been proposed (Van der Schalie et al., 2018) to use L-band data from one of the two instruments specifically designed to measure SM, ESA Soil Moisture and Ocean Salinity (SMOS) and NASA Soil Moisture Active Passive (SMAP) satellites, as reference to re-scale other time series.<br>To investigate this approach, AMSR-2 SM time series obtained from C1-, C2- and X-band observations using LPRM (Land Parameter Retrieval Model) were re-scaled by CDF-matching (Brocca et al., 2011) using different SMAP and SMOS official (SMAP L2 V005, SMOS L3 V300, SMOS NRT V100&V200) and research (SMOS IC V103) SM products as well as the SMAP and SMOS LPRM v6 SM data used by the ESA CCI. The time series re-scaled using L-band remote sensing data were compared to those re-scaled using GLDAS and were evaluated against in situ measurements at several hundred sites retrieved from the International Soil Moisture Network (Dorigo et al., 2011). The results were analyzed as a function of the land cover class and the Koppen-Geiger climate classification.<br>Overall, AMSR-2 time series re-scaled using SMAP L2, SMAP LPRM and SMOS IC data sets as reference gave the best correlations with respect to in situ measurements, similar to those obtained by the time series re-scaled using GLDAS and slightly better than those of the original AMSR-2 time series. These results imply that different SMAP and SMOS products could actually be used to replace GLDAS as reference for the re-scaling of other sensors time series within the ESA CCI. However, one must bear in mind that this study is limited to the re-scaling of AMSR-2 data at a few hundred sites.<br>For a more detailed assessment of the L-band data set to be used for a global re-scaling, it is necessary to investigate other effects such as the spatial coverage or the time series length. SMAP spatial coverage is better than that of SMOS in regions affected by radio frequency interference. In contrast, the length of SMAP time series can be too short to capture the long term SM variability for climate applications in some regions. The CDF of SMOS time series computed from the date of SMAP launch is significantly different to those of the full length SMOS time series in some regions of the Globe. Possible ways of using a coherent SMAP/SMOS L-band data set will be discussed.</p>

Modeling of the Russell glacier's basal conditions at seasonal time scale using the satellite observations of surface ice speed

2021 ◽  
Author(s):  
Anna Derkacheva ◽  
Fabien Gillet-Chaulet ◽  
Jeremie Mouginot
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Flow Model ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Surface Velocity ◽  
Ice Flow ◽  
Surface Ice ◽  
The Impact

<p>Greenland’s future response to climate change will be determined partly by various phenomena controlling ice flow. For the land-terminating sectors, the water lubricating the glacier's base is considered as a major control on the ice motion. For instance, the seasonal modulations of water input induced by summer melt can cause glacier speed-up up to +200-300% compared to the winter mean. Thus, a comprehensive understanding of variations in the basal conditions, which are at the origin of the glacier flow fluctuations, plays a key role for the climate projections.</p><p>While the in-situ measurements stay a local and hard approach to investigate the basal conditions, ice flow modeling offers the possibility to invert for them over the large area based on observations of surface glacier speed and topography. During the last decade, the number of available satellite observations has increased significantly, allowing for far more frequent measurements of the glacier speed and precise reconstruction of the seasonal fluctuations. Here, we investigate the possibility of applying this satellite-derived time-series of surface ice velocity to reconstruct the annual behavior of the basal conditions with 2 weeks temporal resolution using an ice flow model.</p><p>The area of this study is Russell glacier located on the southwest coast of Greenland. A time series of surface velocity dataset was created by merging measurements from Sentinel-1&2 and Landsat-8, covering an area up to 100 km inland with 150 m/pix spatial resolution and 2-weeks temporal resolution (Derkacheva et al. 2020). The 3D Full-Stokes ice flow model Elmer/Ice is used to invert for the effective basal friction coefficient for each time step.  Usage of a friction law that has been derived for hard beds (Gagliardini et al., 2007) allows to constrain the variation of the basal effective pressure. Overall, the results from the model inversions give access to the evolution of the basal ice speed, friction, effective and water pressure, floatation fraction throughout a complete year. The results are compared with in-situ measurements in terms of absolute values and show a good agreement. The impact of the flow model setup, regularization, assumptions for the ice rheology, and the impact of noise in the speed data are also examined and compared with in-situ measurements.</p>

scholarly journals Observing The Mediterranean Sea from space: 21 years of Pathfinder-AVHRR Sea Surface Temperatures (1985 to 2005). Re-analysis and validation

2006 ◽  
Vol 3 (4) ◽  
pp. 1191-1223 ◽  
Author(s):  
S. Marullo ◽  
B. Buongiorno Nardelli ◽  
M. Guarracino ◽  
R. Santoleri
Keyword(s):  
Time Series ◽  
Mediterranean Basin ◽  
In Situ Measurements ◽  
Sea Surface ◽  
Regular Grid ◽  
Daily Series ◽  
Avhrr Data ◽  
The Mediterranean ◽  
The Mediterranean Basin

Abstract. The time series of satellite infrared AVHRR data from 1985 to 2005 has been used to produce a daily series of optimally interpolated SST maps over the regular grid of the operational MFSTEP OGCM model of the Mediterranean basin. A complete validation of this OISST (Optimally Interpolated Sea Surface Temperature) product with in situ measurements has been performed in order to exclude any possibility of spurious trends due to instrumental calibration errors/shifts or algorithms malfunctioning related to local geophysical factors. The validation showed that satellite OISST is able to reproduce in situ measurements with a mean bias of less than 0.1°C and RMSE of about 0.5°C and that errors do not drift with time or with the percent interpolation error.

scholarly journals Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

Sensors ◽  
2008 ◽  
Vol 8 (4) ◽  
pp. 2833-2853 ◽  
Author(s):  
Fabio Fontana ◽  
Christian Rixen ◽  
Tobias Jonas ◽  
Gabriel Aberegg ◽  
Stefan Wunderle
Keyword(s):  
Time Series ◽  
In Situ Measurements ◽  
Alpine Grassland ◽  
Modis Ndvi ◽  
Ndvi Time Series

Quantifying groundwater exploitation induced subsidence in the Rafsanjan plain, southeastern Iran, using InSAR time-series and in situ measurements

2017 ◽  
Vol 218 ◽  
pp. 134-151 ◽  
Author(s):  
Mahdi Motagh ◽  
Roghayeh Shamshiri ◽  
Mahmud Haghshenas Haghighi ◽  
Hans-Ulrich Wetzel ◽  
Bahman Akbari ◽  
...  
Keyword(s):  
Time Series ◽  
In Situ Measurements ◽  
Groundwater Exploitation ◽  
Rafsanjan Plain

scholarly journals Observing the Mediterranean Sea from space: 21 years of Pathfinder-AVHRR sea surface temperatures (1985 to 2005): re-analysis and validation

Ocean Science ◽  
2007 ◽  
Vol 3 (2) ◽  
pp. 299-310 ◽  
Author(s):  
S. Marullo ◽  
B. Buongiorno Nardelli ◽  
M. Guarracino ◽  
R. Santoleri
Keyword(s):  
Time Series ◽  
Mediterranean Basin ◽  
In Situ Measurements ◽  
Sea Surface ◽  
Regular Grid ◽  
Daily Series ◽  
Avhrr Data ◽  
The Mediterranean ◽  
The Mediterranean Basin

Abstract. The time series of satellite infrared AVHRR data from 1985 to 2005 has been used to produce a daily series of optimally interpolated SST maps over the regular grid of the operational MFSTEP OGCM model of the Mediterranean basin. A complete validation of this OISST (Optimally Interpolated Sea Surface Temperature) product with in situ measurements has been performed in order to exclude any possibility of spurious trends due to instrumental calibration errors/shifts or algorithms malfunctioning related to local geophysical factors. The validation showed that satellite OISST is able to reproduce in situ measurements with a mean bias of less than 0.1 K and RMSE of about 0.5 K and that errors do not drift with time or with the percent interpolation error.

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