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We have recently investigated the use of SAR interferometry for the mapping of Snow Water Equivalent (SWE) temporal variations using Sentinel-1 data [1]. Maps of temporal changes of SWE, measured with a sub-centimetre accuracy and updated every six days have been obtained over a study area in Finland. This methodology relies on the shift in the interferometric phase caused by the refraction of the microwave signal penetrating the snow layer. In this work, we investigate phase inconsistencies [2] of a sets of three interferograms obtained from three Sentinel-1 images acquired along the same orbit at different acquisition times to study the snow melt. We find that while phase inconsistencies are not expected to be present in case of examining surfaces covered with frozen snow, the scattering mechanism of microwave in the snow layer during the melting phase affects both the interferometric phase and coherence. This work was supported, in part, by the Academy of Finland project no. 325806. References:[1] V. Conde, G. Nico, P. Mateus, J. Catalão, A. Kontu, M. Gritsevich, On the estimation of temporal changes of snow water equivalent by spaceborne SAR interferometry: a new application for the Sentinel-1 mission, J. Hydrol. Hydromech., 67, 2019, 1, 93–100. DOI: 10.2478/johh-2018-0003[2] F. De Zan, M. Zonno, P. López-Dekker, Phase inconsistencies and multiple scattering in SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 53(12), 6608-6616, 2015

Synthetic Aperture Radar (SAR) interferometry is currently providing displacement measurements over large areas and recently also maps of water vapor in atmosphere. However, the interferometric phase can also capture tiny contributions due to soil moisture. In this work the results obtained in a 1-year experiment with in-situ measurements of soil moisture in agricultural area, in the flat land around the Tagus river, Lisbon, Portugal, are presented. We analyze two interferometric models for the estimation of soil moisture from SAR images. Sentinel-1 SAR images in the C-band are used due to their regular acquisition plan and the short revisiting time. We present examples of soil maps from Sentinel-1 data, characterized by a high spatial resolution and short updating time and comments on their use in precision farming.

In this work we present a methodology for the mapping of Snow Water Equivalent (SWE) temporal variations based on the Synthetic Aperture Radar (SAR) Interferometry technique and Sentinel-1 data. The shift in the interferometric phase caused by the refraction of the microwave signal penetrating the snow layer is isolated and exploited to generate maps of temporal variation of SWE from coherent SAR interferograms. The main advantage of the proposed methodology with respect to those based on the inversion of microwave SAR backscattering models is its simplicity and the reduced number of required in-situ SWE measurements. The maps, updated up to every 6 days, can attain a spatial resolution up to 20 m with sub-centimetre ΔSWE measurement accuracy in any weather and sun illumination condition. We present results obtained using the proposed methodology over a study area in Finland. These results are compared with in-situ measurements of ΔSWE, showing a reasonable match with a mean accuracy of about 6 mm.

In this work we study the problem of mapping soil moisture by means of Synthetic Aperture Radar (SAR) images. A test site has been set in Companhia das Lezirias, close to Lisbon, Portugal. The main advantage of using SAR images is their capability to map soil moisture at a very high spatial resolution. This opens interesting perspectives for agricultural applications, where soil moisture can abruptly change across field boundaries depending on the agricultural practices. The study area is characterized by flat topography, large agricultural areas and sparse vegetation. Five sensors have been deployed in a test area to measure soil moisture with a sampling time of one hour for a period of seven months. In-situ measurements are compared with the results obtained by processing 33 C-band Sentinel-1 images using the SAR interferometry technique. The aim of the study is to analyze the relation between the interferometric phase and time varying soil moisture. The main advantage of SAR interferometry with respect to the use of radar cross-section is that the information about soil moisture can be recovered using a reduced number of in-situ measurements. In particular, we combine three interferograms obtained from three SAR images, acquired over the same area at different times, to derive maps of bi-coherence and phase triplet. This last quantity allows to disentangle the phase contribution due to soil moisture from those related to microwave propagation in atmosphere and terrain displacements. Results are compared to those obtained using the interferometric phase and coherence to emphasize the importance to split the effects due to propagation (e.g. atmosphere) from those related to volume scattering.

Big Data Era in Sky and Earth Observation (BIG-SKY-EARTH, http://www.bigskyearth.eu) is COST Action that aims at setting the ground for a long-term networking between astronomy and remote sensing research communities in the area of Big Data utilization. The purpose of BIG-SKY-EARTH is to emphasize similarities between these disciplines and boost the communication within and between the emerging field of astroinformatics and its older Earth Observation counterpart geoinformatics, in close collaboration with computer scientists. The Action is now entering its final year and the results are visible on several scales. There are many examples of concrete "industrial cross-pollination" stories where BIG-SKY-EARTH facilitated exchange of methods and knowledge between network participants. For example, remote sensing and astronomy big data repositories for meteorological nowcasting, thermosolar energy production forecasting, astronomy big data analytics libraries for wind farm predictive maintenance visualization, astronomy and remote sensing C-based stack for scalable numerical analysis used in advanced manufacturing analytics, GPU analytics for remote sensing and industrial analytics, or developing astronomy platform on the top of commercial remote sensing airship to enable transfer the same technology to a high-resolution remote sensing platform. Some of those collaborations expanded into research papers or even project proposals for H2020 based on partnerships between academia and industry, including developing new types of astronomy and remote sensing research based on innovative airship technologies. The Action has also organized three training schools so far: "Big Data Processing" (Oberpfaffenhofen, Germany), "Big Data Visualization" (Preston, UK), "Big Data GPU Analytics" (San Sebastián, Spain). On the level of the entire networking, the Action is also working on the book "Big Data in AstroGeoInformatics" and accompanying code and algorithm repository. Altogether, the established level of activity and interests for further collaboration suggest that this networking will actively continue also after the official end of COST funding. This presentation will also show two examples of research activities that the presenter started thanks to BIG-SKY-EARTH. The first example focuses on the Precipitable Water Vapor (PWV) estimated from Sentinel-1 images using the SAR interferometry technique. Large databases of high resolution Sentinel-1 PWV maps will need to be analyzed before their assimilation in Numerical Weather Models and use for the estimation of geophysical parameters. This research started during an STSM visit at the Finnish Geospatial Research Institute led to the first tools for the analysis of PWV time series in terms of terrain topography and landcover and the visualization of atmosphere thermodynamic quantities [1]. The second example is on the mapping of the Snow Water Equivalent (SWE) using Sentinel-1 SAR images[2-4]. References: [1]G.Nico,A.Gil,M.Quartulli,P.Mateus,J.Catalao,Merging InSAR and GNSS meteorology:how can we mine InSAR and GNSS databases to extract and visualize information on atmosphere processes?,Proc.of Big Data from Space(BIDS),375-378,2017 [2]V.Conde,G.Nico,P.Mateus,J.Catalao,A.Kontu,M.Gritsevich,Snow Water Equivalent Retrieval Using Synthetic Aperture Radar(SAR) Interferometry,Proc. 8th EARSeL workshop on Land Ice and Snow,2017 [3]V.Conde,G.Nico,J.Catalao,A.Kontu,M.Gritsevich,Wide-area mapping of snow water equivalent by Sentinel-1&2 data,Geophysical Research Abstracts Vol.19, EGU2017-9580-1,2017 [4]V.Conde,G.Nico,P.Mateus,J.Catalão,A.Kontu,M.Gritsevich,On the estimation of temporal changes of snow water equivalent by spaceborne SAR interferometry: a new application for the Sentinel-1 mission,Journal of Hydrology and Hydromechanics,DOI:10.2478/johh-2018-0003,2017

In this work, we exploit the integration of an advanced synthetic aperture radar (SAR) interferometry technique and the application of the finite-element method for the assessment and the interpretation of a localized subsidence phenomenon that took place within a specific area of Lisbon, Portugal. SAR images over the Lisbon city, covering different time intervals in the period of 1995-2010, were acquired and processed by means of the persistent scatterers (PSs) technique. Results clearly reveals a localized subsidence, limited to an area 2 km × 1.5 km wide, which has been confirmed by the leveling performed in 1976, 1996, and 2010. A physical interpretation of the observed ground deformations is provided based on the results of a finite-element model using stratigraphic data, in situ piezometric measurements, and geotechnical properties of the involved soils. The ground subsidence is interpreted as the consequence of a consolidation process affecting the central fine-grained soil layer, which in turn has been driven by water withdrawal from the existing aquifers. The change of the hydraulic boundary conditions was generated by the excavation works for the construction of underground lines and also by the reduction of rainfall water infiltration as an effect of the increase in ground surface impermeable areas due to urbanization. The consequent consolidation process of the compressible fine-grained soil layer is supposed to provide a reasonable explanation of the observed time series of ground displacement in the examined area.