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Monitoring structural stability in urban areas and infrastructure networks is emerging as one of the dominant socio-economic issues for population security. The problem is accentuated by the age of the infrastructure because of increasing risks due to material deterioration and loss of load capacity. In this case, SAR satellite data are crucial to identify and assess the deteriorating conditions of civil infrastructures. The large amount of data available from SAR satellite sensors leads to the exploitation and development of new GIS-based procedures for rapid responses and decision making. In recent decades, the DInSAR technique has been used efficiently for the monitoring of structures, providing measurement points located on structures with millimeter precision. Our study has analyzed the behavior of structures in settlements, attempting to discuss the interactions of soil and structures, and examining the behavior of different types of structures, such as roads and buildings. The method used is based on long-term SAR interferometry data and a semi-automatic procedure to measure the displacement (mm/year) of structures, through a GIS-based application performed in the "Implemented MOnitoring DIsplacement" I.MODI platform. The analysis provides extensive information on long-term spatial and temporal continuity of up to 25 years of record, using satellite SAR multi-sensors from ERS, Envisat, and COSMO-SkyMed. The interpretation uses time series spatial analysis, supported by orthophotos, and layers of the DBTR (regional topographic database), Digital Surface model (DSM), and hydrogeological map to show anomalous areas with a high displacement rate and to observe the correlation of settlements in the sediments. With the satellite information and Geographic Information System (GIS), we were able to observe relevant parameters, such as the velocity of advance in the direction of the slope (deformation profiles), the cumulative displacement, and the trend changes in structures. The results illustrate an innovative procedure that allows the management of DInSAR data to facilitate the effective management of structures in which a monitoring protocol was developed at different spatial scales, integrating the information into a GIS. [ABSTRACT FROM AUTHOR]

Sea ice thickness (SIT), which is a crucial and sensitive indicator of climate change in the Antarctic, has a substantial impact on atmosphere-sea-ice-ocean interactions. Despite the slight thinning in SIT and reduction in sea ice volume (SIV) in the Antarctic in the recent decade, challenges remain in quantifying their changes, primarily because of the limited availability of high-quality long-term observational data. Therefore, it is crucial to accurately simulate Antarctic SIT and to assess the SIT simulation capability of state-of-the-art climate models. In this study, we evaluated historical simulations of SIT by 51 climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) using Envisat (ES) and CryoSat-2 (CS2) observations. Results revealed that most models can capture the seasonal cycles in SIV and that the CMIP6 multimodel mean (MMM) can reproduce the increasing and decreasing trends in the SIV anomaly based on ES and CS2 data, although the magnitudes of the trends in the SIV anomaly are underestimated. Additionally, the intermodel spread in simulations of SIT and SIV was found to be reduced (by 43%) from CMIP5 to CMIP6. Nevertheless, based on the CMIP6 MMM, substantial underestimations in SIV of 57.52% and 59.66% were found compared to those derived from ES and CS2 observations, respectively. The most notable underestimation in SIT was located in the sea ice deformation zone surrounding the northwestern Weddell Sea, coastal areas of the Bellingshausen and Amundsen seas, and the eastern Ross Sea. The substantial bias in the simulated SIT might result from deficiencies in simulating critical physical processes such as ocean heat transport, dynamic sea ice processes, and sea ice-ocean interactions. Therefore, increasing the model resolution and improving the representation of sea ice dynamics and the physical processes controlling sea ice-ocean interactions are essential for improving the accuracy of Antarctic sea ice simulation.

The study presents an integrated investigation of a complex landslide based on multitemporal stereo aerial photographic interpretations, existing geotechnical monitoring data, and different PSInSAR datasets. The available information allowed for the quantification of the deformation history, also in periods with no monitoring in the field, making it possible to revise the geometry of the landslide compared to the official landslide mapping. Data from sparse inclinometers are compared with more spatially continuous satellite measurements, showing that the two monitoring techniques are consistent in terms of cumulative deformation trend and in terms of response to prolonged drought and wet periods. Therefore, reliable landslide mass displacements can be monitored using satellite products when ground instrumentations are no longer operating. Understanding the landslide behavior to rainfall conditions offers an important insight into the velocities and cumulative displacements expected during similar stages of enhanced landslide activity. The findings can be helpful to support urban planners in re-evaluating hazard and risk classification and implementing efficient mitigation techniques to reduce landslide damage. [ABSTRACT FROM AUTHOR]

The Central-Eastern part of the High Atlas is dominated by carbonate of Mesozoic age which is affected by the Alpine Orogeny. The deformation manifest in area by different geological structures. The analysis of these later lead to their classification in different category for understanding the geodynamic of the area. This study focuses to map structural lineaments in the CentralEastern High Atlas using two types of Radar data: Synthetic Aperture Radar (SAR)/Sentinel 1B with polarization (VV + VH) and Advanced Synthetic Aperture Radar (ASAR)/Envisat with polarization (VV + HH). This research aims to demonstrate the utility of Radar data for extracting structural lineaments in carbonate deposits. In this work, two techniques of processing data are used: First, the automatic extraction technique, we are employing the Algorithm Line Module of PCI Geomatica program, after the enhancement of images by applying the mean Co-occurrence filter. Second, the manual extraction technique, it was accomplished by applying directional filters with four directions (N00o, N45o, N9o and N135o) in order to highlight linear structures, then trace the detected lineaments. The synthetic maps of structural lineaments are developed by the two techniques. They are validated by using the lithologic maps extracted from Landsat Operational Land Imager (OLI), the previous researches in the study area, shaded relief extracted from ASTER Global Digital Elevation Model (GDEM), and field investigation data. The results present a good correlation between the direction of structural lineaments extracted from the satellite images and the field measurements. Therefore, the directions of lineaments extracted are N-S and E-W, NE-SW and NW-SE, especially the abundance of the direction N-S. This last one is perpendicular with the major faults. The density of structural lineaments in the study area is controlled particularly by the lithological nature and dynamic evolution, where the concentration is high in the Liassic carbonates. The geostatistical and spatial distribution of the structural lineaments led us to conclude that different tectonic factors are responsible for the distribution of lineaments in the surface of the study area. The comparison of two types of radar data shows that Envisat data is more efficient in the manual extraction than Sentinel 1B data. However, Sentinel 1B data is more efficient in the automatic extraction than Envisat data. This work identifies several families of structural lineaments which can be determined the tectonic phases of the Alpine orogeny affected the intracontinental Atlas basin. [ABSTRACT FROM AUTHOR]

The relatively stable conditions of the sea ice cover in the Antarctic, observed for almost 40 years, seem to be changing recently. Therefore, it is essential to provide sea ice thickness (SIT) and volume (SIV) estimates in order to anticipate potential multi-scale changes in the Antarctic sea ice. For that purpose, the main objectives of this work are: (1) to assess a new sea ice freeboard, thickness and volume altimetry dataset over 2003–2020 and (2) to identify first order impacts of the sea ice recent conditions. To produce these series, we use a neuronal network to calibrate Envisat radar freeboards onto CryoSat-2 (CS2). This method addresses the impacts of surface roughness on Low Resolution Mode (LRM) measurements. During the 2011 common flight period, we found a mean deviation between Envisat and CryoSat-2 radar freeboards by about 0.5 cm. Using the Advanced Microwave Scanning Radiometer (AMSR) and the dual-frequency Altimetric Snow Depth (ASD) data, our solutions are compared with the Upward looking sonar (ULS) draft data, some in-situ measurement of the SIMBA campaign, the total freeboards of 6 Operation Ice Bridge (OIB) missions and ICESat-2 total freeboards. Over 2003–2020, the global mean radar freeboard decreased by about −14% per decade and the SIT and SIV by about −10% per decade (considering a snow depth climatology). This is marked by a slight increase through 2015, which is directly followed by a strong decrease in 2016. Thereafter, freeboards generally remained low and even continued to decrease in some regions such as the Weddell sea. Considering the 2013–2020 period, for which the ASD data are available, radar freeboards and SIT decreased by about −40% per decade. The SIV decreased by about −60% per decade. After 2016, the low SIT values contrast with the sea ice extent that has rather increased again, reaching near-average values in winter 2020. The regional analysis underlines that such thinning (from 2016) occurs in all regions except the Amundsen-Bellingshausen sea sector. Meanwhile, we observed a reversal of the main regional trends from 2016, which may be the signature of significant ongoing changes in the Antarctic sea ice. [ABSTRACT FROM AUTHOR]

Monitoring structural stability in urban areas and infrastructure networks is emerging as one of the dominant socio-economic issues for population security. The problem is accentuated by the age of the infrastructure because of increasing risks due to material deterioration and loss of load capacity. In this case, SAR satellite data are crucial to identify and assess the deteriorating conditions of civil infrastructures. The large amount of data available from SAR satellite sensors leads to the exploitation and development of new GIS-based procedures for rapid responses and decision making. In recent decades, the DInSAR technique has been used efficiently for the monitoring of structures, providing measurement points located on structures with millimeter precision. Our study has analyzed the behavior of structures in settlements, attempting to discuss the interactions of soil and structures, and examining the behavior of different types of structures, such as roads and buildings. The method used is based on long-term SAR interferometry data and a semi-automatic procedure to measure the displacement (mm/year) of structures, through a GIS-based application performed in the “Implemented MOnitoring DIsplacement” I.MODI platform. The analysis provides extensive information on long-term spatial and temporal continuity of up to 25 years of record, using satellite SAR multi-sensors from ERS, Envisat, and COSMO-SkyMed. The interpretation uses time series spatial analysis, supported by orthophotos, and layers of the DBTR (regional topographic database), Digital Surface model (DSM), and hydrogeological map to show anomalous areas with a high displacement rate and to observe the correlation of settlements in the sediments. With the satellite information and Geographic Information System (GIS), we were able to observe relevant parameters, such as the velocity of advance in the direction of the slope (deformation profiles), the cumulative displacement, and the trend changes in structures. The results illustrate an innovative procedure that allows the management of DInSAR data to facilitate the effective management of structures in which a monitoring protocol was developed at different spatial scales, integrating the information into a GIS.

The phenomenon of the subsidence of the Earth is called the downward movement of the Earth's surface, which is not easily identifiable and quantifiable due to its slow evolution. The most appropriate method is to use radar data and differential interferometry techniques. Since physical compression and pressure drop are the main causes of subsidence in the places where water is extracted, D-InSAR's integrated zoning and its simultaneous investigation with subsurface factors reflect the anomalous deformation pattern created by subsurface factors. It shows well and demonstrates that the use of D-InSAR has been helpful in subsidence navigation. For this purpose, D InSAR radar data interferometry method was applied to ENVISAT and PALSAR radar satellite data from ASAR and ALOS sensors in 2006-2008, respectively. Ambient drought moderated the effect of phase change caused by atmospheric compounds, and the lack of challenge vegetation minimized the coherence of the phase radar images and made it possible to measure changes in the C and L band radar data annually. The maximum displacement was estimated by the C band of 0.14 m and by the L band of 0.12 m. Finally, we modeled the statistical results of the groundwater of the region and the amount of subsidence estimated by the mentioned radar images by linear regression method. There is groundwater, in relation to ASAR image per meter change in groundwater level we will have 0.025 meter change in ground level elevation and PALSAR (HH) image per meter change in groundwater level, 0.021 meter change in height we will have.

The study presents an integrated investigation of a complex landslide based on multitemporal stereo aerial photographic interpretations, existing geotechnical monitoring data, and different PSInSAR datasets. The available information allowed for the quantification of the deformation history, also in periods with no monitoring in the field, making it possible to revise the geometry of the landslide compared to the official landslide mapping. Data from sparse inclinometers are compared with more spatially continuous satellite measurements, showing that the two monitoring techniques are consistent in terms of cumulative deformation trend and in terms of response to prolonged drought and wet periods. Therefore, reliable landslide mass displacements can be monitored using satellite products when ground instrumentations are no longer operating. Understanding the landslide behavior to rainfall conditions offers an important insight into the velocities and cumulative displacements expected during similar stages of enhanced landslide activity. The findings can be helpful to support urban planners in re-evaluating hazard and risk classification and implementing efficient mitigation techniques to reduce landslide damage.

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The German Research Centre for Geosciences GFZ provides non-tidal atmospheric and oceanic loading (NTAOL) displacements for tracking stations located on the Earth's surface based on ECMWF numerical weather models (NWM) and compatible with GRACE atmosphere and ocean de-aliasing products (AOD1B). We apply both, the dynamic (AOD1B) and the geometric (NTAOL) models, to Precise Orbit Determination (POD) of the altimetry missions ENVISAT, Jason-1, and Jason-2 with Satellite Laser Ranging (SLR) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations. Alternatively to the GFZ displacements, those provided by the International Mass Loading Service (IMLS) based on the MERRA NWM are applied also. The differences in POD are qualified in terms of orbital fits, orbit differences and altimeter cross-over differences. It turns out that the major effect comes from AOD1B, that from NTAOL is considerably smaller, but visible and of benefit for POD. Long-term systematics introduced by the loading models can not be detected. Geographicaly correlated systematics important for altimetry show up, however well below the millimeter. The effect of loading on altimeter cross-over results is even smaller and close to the point where sensitivity is lost. [ABSTRACT FROM AUTHOR]

The relatively stable conditions of the sea ice cover in the Antarctic, observed for almost 40 years, seem to be changing recently. Therefore, it is essential to provide sea ice thickness (SIT) and volume (SIV) estimates in order to anticipate potential multi-scale changes in the Antarctic sea ice. For that purpose, the main objectives of this work are: (1) to assess a new sea ice freeboard, thickness and volume altimetry dataset over 2003–2020 and (2) to identify first order impacts of the sea ice recent conditions. To produce these series, we use a neuronal network to calibrate Envisat radar freeboards onto CryoSat-2 (CS2). This method addresses the impacts of surface roughness on Low Resolution Mode (LRM) measurements. During the 2011 common flight period, we found a mean deviation between Envisat and CryoSat-2 radar freeboards by about 0.5 cm. Using the Advanced Microwave Scanning Radiometer (AMSR) and the dual-frequency Altimetric Snow Depth (ASD) data, our solutions are compared with the Upward looking sonar (ULS) draft data, some in-situ measurement of the SIMBA campaign, the total freeboards of 6 Operation Ice Bridge (OIB) missions and ICESat-2 total freeboards. Over 2003–2020, the global mean radar freeboard decreased by about −14% per decade and the SIT and SIV by about −10% per decade (considering a snow depth climatology). This is marked by a slight increase through 2015, which is directly followed by a strong decrease in 2016. Thereafter, freeboards generally remained low and even continued to decrease in some regions such as the Weddell sea. Considering the 2013–2020 period, for which the ASD data are available, radar freeboards and SIT decreased by about −40% per decade. The SIV decreased by about −60% per decade. After 2016, the low SIT values contrast with the sea ice extent that has rather increased again, reaching near-average values in winter 2020. The regional analysis underlines that such thinning (from 2016) occurs in all regions except the Amundsen-Bellingshausen sea sector. Meanwhile, we observed a reversal of the main regional trends from 2016, which may be the signature of significant ongoing changes in the Antarctic sea ice.

The focus of this study is the monitoring and analysis of the most recent crustal deformation phenomena in Southern Pakistan. For subsidence evaluation, the longer temporal monitoring is recommended; therefore, the time period chosen for this measurement is between two separate 2005 to 2008 and 2014 to 2018 time series analysis. Remote sensing, synthetic aperture radar interferometry techniques (InSAR) technique is employed for the understanding of localized phenomena of crustal deformation in spatio-temporal coverage. Thatta and Jamshoro districts of the Southern Pakistan region are selected as areas of interest (AOI). These districts are notable for the subsidence phenomena in Pakistan. ENVISAT and central sub swath of Sentinal-1A satellites and InSAR datasets are utilized for quantification of subsidence rate of the area of interest because of the accuracy of their sensors up to millimeters. These satellite missions have widespread spatial coverage, continuous temporal sampling, and free data accessibility due to open data policy of European Space Agency. These two different satellite datasets for different periods of acquisitions provided the comparison of the subsidence rate between temporal periods of these two satellite imageries for area of interest. The long-term data monitoring enables to understand temporal-spatial characteristic to the AOI and understanding of the localized trend. Computation of localized subsidence pattern from ENIVSAT and central sub swath IW2 of Sentinel-1A had been carried out from period Jan 2005 to Dec 2009 with 32 acquisitions and from April 2014 to Nov 2018 with 49 imagery acquisitions, respectively, for ascending orbit. For this Line of Sight (LOS) displacement measurement, InSAR time-series analysis is utilized with the application of the small baseline subset (SBAS) interferogram technique. SBAS time series analysis emerged as strong algorithm with capability to reduce temporal decorrelation for deformation investigation within last couple of years. A total of 53 interferograms from ENVISAT and 141 interferograms from Sentinel-1A are formed. Relative temporal baseline positions are of ± 300 m for ENVISAT and ± 150 m for Sentinel-1A with respect to master acquisition. Subsidence of average 4 mm per year is measured along the cross section line from ENVISAT in the area of interest with total subsidence of 24 mm over a period of 6 years. During the Sential-1A acquisition period, the subsidence rate is the same but the area of subsidence is smaller in size as compared with the previous period of monitoring with ENVISAT. Maximum subsidence noted for the period from May 2005 to Aug 2006. It was the same period when over pumping of water was carried out in the area of interest. The larger deformation zone is due to the intense extraction of subsurface freshwater, because the subsidence correlated with the data of tube wells provided by the country water management agency. The data showed the increase in numbers of tube wells installed in the locality over the first phase study time period with extraction of water up to 7000 ha per year (Development Statistics of Sindh 2001-2016) with depletion of groundwater table up to 122 m from the surface. [ABSTRACT FROM AUTHOR]

Envisat has been identified as a candidate target for active debris removal. The research on its rotation state is of great significance. The specular glint times in optical observation data can be used in fitting the rotation state of Envisat by the epoch method. Using well-observed variations in synodic frequencies, and minimizing the goodness-of-fit indicator by a grid-search, complete spin state solutions can be derived. By this method, Envisat's spin axis longitude α and latitude δ in the orbital coordinate system can be calculated. The latitude δ oscillates widely with time between - 55 ° and - 85 ° with a mean value of δ mean = - 67.08 °. Its distribution has peaks in two areas around - 60 ° and - 80 ° , which is similar to the results through laser ranging measurements from a single pass. In addition, the precession fit of the spin axis longitude α shows that the spin axis may not precess regularly around the negative normal of the orbital plane. Besides, Envisat's sidereal period from 2013 to 2015 increases exponentially with the expression: P sid (sec) = 121.1 · exp (4.462 × 10 - 4 · t) , where t is measured in days from the beginning of 2013, RMS of the fit residuals = 1.8586 s. [ABSTRACT FROM AUTHOR]

Quantifying the mass balance of the Antarctic Ice Sheet (AIS), and the resulting sea level rise, requires an understanding of inter-annual variability and associated causal mechanisms. Very few studies have been exploring the influence of climate anomalies on the AIS and only a vague estimate of its impact is available. Changes to the ice sheet are quantified using observations from space-borne altimetry and gravimetry missions. We use data from Envisat (2002 to 2010) and Gravity Recovery And Climate Experiment (GRACE) (2002 to 2016) missions to estimate monthly elevation changes and mass changes, respectively. Similar estimates of the changes are made using weather variables (surface mass balance (SMB) and temperature) from a regional climate model (RACMO2.3p2) as inputs to a firn compaction (FC) model. Elevation changes estimated from different techniques are in good agreement with each other across the AIS especially in West Antarctica, Antarctic Peninsula, and along the coasts of East Antarctica. Inter-annual height change patterns are then extracted using for the first time an empirical mode decomposition followed by a principal component analysis to investigate for influences of climate anomalies on the AIS. Investigating the inter-annual signals in these regions revealed a sub-4-year periodic signal in the height change patterns. El Niño Southern Oscillation (ENSO) is a climate anomaly that alters, among other parameters, moisture transport, sea surface temperature, precipitation, in and around the AIS at similar frequency by alternating between warm and cold conditions. This periodic behavior in the height change patterns is altered in the Antarctic Pacific (AP) sector, possibly by the influence of multiple climate drivers, like the Amundsen Sea Low (ASL) and the Southern Annular Mode (SAM). Height change anomaly also appears to traverse eastwards from Coats Land to Pine Island Glacier (PIG) regions passing through Dronning Maud Land (DML) and Wilkes Land (WL) in 6 to 8 years. This is indicative of climate anomaly traversal due to the Antarctic Circumpolar Wave (ACW). Altogether, inter-annual variability in the SMB of the AIS is found to be modulated by multiple competing climate anomalies.

Arctic sea ice variations are sensitive to Arctic environmental changes and global changes. Freeboard and thickness are two important parameters in sea ice change research. Satellite altimetry can provide long-time and large-scale sea ice monitoring. We estimated the Arctic sea ice freeboard and its variations for the period from 2002 to 2012 from Envisat satellite altimetry data. To remove geoid undulations, we reprocessed the Envisat data using a newly developed mean sea surface (MSS) model, named DTU18. Residuals in the static geoid were removed by using the moving average technique. We then determined the local sea surface height and sea ice freeboard from the Envisat elevation profiles. We validated our freeboard estimates using two radar freeboard products from the European Space Agency (ESA) Climate Change Initiative (CCI) and the Alfred Wegener Institute (AWI), as well as the Operation IceBridge (OIB) sea ice freeboard product. The overall differences between our estimates and the CCI and AWI data were 0.11 ± 0.14 m and 0.12 ± 0.14 m, respectively. Our estimates show good agreement with the three products for areas of freeboard larger than 0.2 m and smaller than 0.3 m. For areas of freeboard larger than 0.3 m, our estimates correlate better with OIB freeboard than with CCI and AWI. The variations in the Arctic sea ice thickness are discussed. The ice freeboard reached its minimum in 2008 during the research period. Sharp decreases were found in the winters of 2005 and 2007.

This article focuses on the precision and bias of laser altimetry data [Ice, Cloud, and Land Elevation Satellite (ICESat)] and radar altimetry data (Envisat) L2 products during the contemporary period from 2003 to 2008 in the Amundsen Sea Embayment (ASE) in West Antarctica (an ice loss region) and the Lambert-Amery System (LAS) in East Antarctica (an ice gain region). We used the crossover method to obtain the elevation differences between ICESat tracks, Envisat tracks, and between ICESat and Envisat tracks. The crossover points were generated and the difference of each crossover pair was calculated as raw data. The standard deviations were then computed from the raw data in a grid cell for both ICESat and Envisat. The precision of both satellites varied as a function of the surface slope in the abovementioned two regions, from 6.6 to 16.6 cm for the ICESat data and from 0.11 to 0.35 m for the Envisat data. The crossover points from ICESat-Envisat showed a mean bias of 0.55 ± 4.00 m for the ASE and 0.45 ± 0.99 m for the LAS, in accordance with the penetration depth of the radar altimetry. The relationship between the precision of the satellite measurements with the slope of the ice sheet and the ice velocity in the study area showed that the regions with gentle slopes and low velocity obtained a better precision of altimetry data. [ABSTRACT FROM AUTHOR]

A new approach for assessing the quality of Synthetic Aperture Radar (SAR) wave spectra is presented here. The algorithm addresses two specific issues, related to the 180° directional ambiguity in the propagation direction inherent to SAR measurements, and the removal of noise. In spite of several and progressive advances in the mapping and retrieval of SAR wave spectra, these issues are persistent in the existing official databases and hinder the use of these data for practical uses. This new algorithm is based on a recently developed database of long-term global wave spectral characteristics, which allows estimating the occurrence probability of every individual wave system found in the observed spectra, and that of its ambiguous pair. In addition, assuring the spatial consistency of the wave systems along track, helps obtaining more robust results. In this sense, wave spectra within a track are processed in several steps, so that wave systems with more likelihood of being correct are processed first, and consequently used to evaluate the more challenging components. Accordingly, a specific quality label is assigned to every wave system depending on the certainty achieved. An Envisat track over a challenging area with multiple crossing swells is used to illustrate the performance of the algorithm. [ABSTRACT FROM AUTHOR]

This document describes in detail the structure of the level 0 data of the ENVISAT satellite and, in addition, presents the de-encapsulation and decompression algorithms of the raw ASAR data, specifically the IM operation mode files. These algorithms were developed in order to facilitate and optimize the task of retrieving the source data. As a result, a raw-data-based image of a region in the Falcon state of Venezuela was obtained after applying the aforementioned algorithms to the level 0 files downloaded by the ESA Simple Online Catalogue's. [ABSTRACT FROM AUTHOR]

In preparation for the operations of the ALTIUS mission, research is carried out to assess the accuracy of the SGP4 orbital propagator in predicting stellar occultation events. The quantification of the accuracy and its consequent improvement will enable reliable measurement planning and, therefore, maximize the number of measurements. To this end, predictions are made for the timing of occultations for the GOMOS instrument on-board the ENVISAT, which are then compared to actual occultation occurrences. It is found that the error is substantial but follows a trend that can be interpolated. This enables devising a method for highly accurate predictions given a sufficient number of data points. Statistically significant results for the accuracy of the propagator and a calibration method are presented. Recommendations for a measurement planning procedure of ALTIUS are formulated. [ABSTRACT FROM AUTHOR]

In the absence of systematic structural monitoring to support adequate maintenance standards, many existing infrastructures may reach unacceptable quality levels during their life cycle, resulting in significant damage and even potential failure. The metropolitan area of the Gulf of Salerno (Italy), served by a complex multimodal transport network connecting the port area to the roads and railways surrounding the urban area, represents an important industrial and commercial hub at the local and international scale. This particular scenario, developed in a complex morphological and geological context, has led to the interference and overlapping of the transport network (highway, railway, main and secondary roads) that run through the piedmont area north of the port. Given the relevance of the area, our research aims to highlight the capabilities of the persistent scatterer interferometry (PSI) technique, belonging to the group of differential interferometric synthetic aperture radar (SAR), to extract space–temporal series of displacements on ground points or artifacts with millimeter accuracy useful to understand ongoing deformation processes. By using archived data from the European Space Agency missions, i.e., ERS1/2 (European remote-sensing satellite) and ENVISAT (environmental satellite), and the most recent data from COSMO-SkyMed constellations, it was possible to collect a 28-year dataset that was used to spatially analyze displacement patterns at a site-specific scale to check the stability of viaducts and embankments, and on a larger scale to understand the activity of the surrounding slopes. Despite the different resolution and subsequently the ground density, the analysis of the different datasets showed a spatiotemporal consistency in the displacement patterns that concerned two subareas showing significant annual velocity trends, one northeast of the city and the second in the port area. The analysis presented in this paper highlights how a complex geologic area, combining slope movements and various fault systems, could be a major concern for the stability of the overlying infrastructure and also the role that a PSI analysis can play in remotely monitoring their behavior over long periods of time.

Changes in subsurface water resources might alter the surrounding ground by generating subsidence or uplift, depending on geological and hydrogeological site characteristics. Improved understanding of the relationships between surface water storage and ground deformation is important for design and maintenance of hydraulic facilities and ground stability. Here, we construct one of the longest series of Interferometric Synthetic Aperture Radar (InSAR) to date, over twenty-five years, to study the relationships between water level changes and ground surface deformation in the surroundings of Lake Mead, United States, and at the site of the Hoover Dam. We use the Small Baseline Subset (SBAS) and Permanent scatterer interferometry (PSI) techniques over 177 SAR data, encompassing different SAR sensors including ERS1/2, Envisat, ALOS (PALSAR), and Sentinel-1(S1). We perform a cross-sensor examination of the relationship between water level changes and ground displacement. We found a negative relationship between water level change and ground deformation around the reservoir that was consistent across all sensors. The negative relationship was evident from the long-term changes in water level and deformation occurring from 1995 to 2014, and also from the intra-annual oscillations of the later period, 2014 to 2019, both around the reservoir and at the dam. These results suggest an elastic response of the ground surface to changes in water storage in the reservoir, both at the dam site and around the reservoir. Our study illustrates how InSAR-derived ground deformations can be consistent in time across sensors, showing the potential of detecting longer time-series of ground deformation.

The Ocean and Land Colour Instrument (OLCI) on-board Sentinel-3 (2016–present) was designed with similar mechanical and optical characteristics to the Envisat Medium Resolution Imaging Spectrometer (MERIS) (2002–2012) to ensure continuity with a number of land and marine biophysical products. The Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) is an indicator of canopy chlorophyll content and is intended to continue the legacy of the Envisat MERIS Terrestrial Chlorophyll Index (MTCI). Despite spectral similarities, validation and verification of consistency is essential to inform the user community about the product’s accuracy, uncertainty, and fitness for purpose. This paper aims to: (i) describe the theoretical basis of the Sentinel-3 OTCI and (ii) evaluate the spatiotemporal consistency between the Sentinel-3 OTCI and the Envisat MTCI. Two approaches were used to conduct the evaluation. Firstly, agreement between the Sentinel-3 OTCI and the Envisat MTCI archive was assessed over the Committee for Earth Observation Satellites (CEOS) Land Product Validation (LPV) core validation sites, enabling the temporal consistency of the two products to be investigated. Secondly, intercomparison of monthly Level-3 Sentinel-3 OTCI and Envisat MTCI composites was carried out to evaluate the spatial distribution of differences across the globe. In both cases, the agreement was quantified with statistical metrics (R2, NRMSD, bias) using an Envisat MTCI climatology based on the MERIS archive as the reference. Our results demonstrate strong agreement between the products. Specifically, high 1:1 correspondence (R2 >0.88), low global mean percentage difference (−1.86 to 0.61), low absolute bias (

Inland water storage change is a fundamental part of the hydrologic cycle, which reflects the impact of climate change and anthropogenic activities on water resources. In this study, we used multisatellite data (from satellite altimetry, remote sensing, and the Gravity Recovery and Climate Experiment (GRACE)) to investigate water storage changes in the Aral Sea and its endorheic basin. The water storage depletion rate in the Aral Sea from calibrated hypsometric curves (CHCs) created by satellite altimetry and image data agrees with the GRACE-derived result using the Slepian space domain inverse method (SSDIM). Compared with the combined filtering method (CFM) and mascon solutions, the SSDIM was shown to be an effective method of reducing the GRACE leakage error and restoring the signal attenuation in the Aral Sea. Moreover, we used the WaterGAP global hydrology model (WGHM) to qualitatively analyze the variations in the water storage components. The results show that the groundwater in the Aral Sea affects the change in the interannual water storage, especially during the extreme dry and humid periods. However, from the long-term water storage trend, the decrease in the surface storage dominates the shrinking of the Aral Sea. In addition, more details of the water storage change pattern in the endorheic basin were revealed by the enhanced GRACE solution. Our findings accentuate the severe water storage states of the Aral Sea endorheic basin under the impact of climate change and human interventions.

Rice is the most important food crop in Asia, and the timely mapping and monitoring of paddy rice fields subsequently emerged as an important task in the context of food security and modelling of greenhouse gas emissions. Rice growth has a distinct influence on Synthetic Aperture Radar (SAR) backscatter images, and time-series analysis of C-band images has been successfully employed to map rice fields. The poor data availability on regional scales is a major drawback of this method. We devised an approach to classify paddy rice with the use of all available Envisat ASAR WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) data for our study area, the Mekong Delta in Vietnam. We used regression-based incidence angle normalization and temporal averaging to combine acquisitions from multiple tracks and years. A crop phenology-based classifier has been applied to this time series to detect single-, double- and triple-cropped rice areas (one to three harvests per year), as well as dates and lengths of growing seasons. Our classification has an overall accuracy of 85.3% and a kappa coefficient of 0.74 compared to a reference dataset and correlates highly with official rice area statistics at the provincial level (R² of 0.98). SAR-based time-series analysis allows accurate mapping and monitoring of rice areas even under adverse atmospheric conditions.

In this study deformation processes in northern Zona Metropolitana del Valle de Mexico (ZMVM) are evaluated by means of advanced multi-temporal interferometry. ERS and ENVISAT time series, covering approximately an 11-year period (between 1999 and 2010), were produced showing mainly linear subsidence behaviour for almost the entire area under study, but increasing rates that reach up to 285 mm/yr. Important non-linear deformation was identified in certain areas, presumably suggesting interaction between subsidence and other processes. Thus, a methodology for identification of probable fracturing zones based on discrimination and modelling of the non-linear (quadratic function) component is presented. This component was mapped and temporal subsidence evolution profiles were constructed across areas where notable acceleration (maximum of 8 mm/yr2) or deceleration (maximum of −9 mm/yr2) is found. This methodology enables location of potential soil fractures that could impact relevant infrastructure such as the Tunel Emisor Oriente (TEO) (along the structure rates exceed 200 mm/yr). Additionally, subsidence behaviour during wet and dry seasons is tackled in partially urbanized areas. This paper provides useful information for geological risk assessment in the area.

Associating a radar scatterer to a physical object is crucial for the correct interpretation of interferometric synthetic aperture radar measurements. Yet, especially for medium-resolution imagery, this is notoriously difficult and dependent on the accurate 3-D positioning of the scatterers. Here, we investigate the 3-D positioning capabilities of ENVISAT medium-resolution data. We find that the data are perturbed by range-and-epoch-dependent timing errors and calibration offsets. Calibration offsets are estimated to be about 1.58 m in azimuth and 2.84 m in range and should be added to ASAR products to improve geometric calibration. The timing errors involve a bistatic offset, atmospheric path delay, solid earth tides, and local oscillator drift. This way, we achieve an unbiased positioning capability in 2-D, while in 3-D, a scatterer was located at a distance of 28 cm from the true location. 3-D precision is now expressed as an error ellipsoid in local coordinates. Using the Bhattacharyya metric, we associate radar scatterers to real-world objects. Interpreting deformation of individual infrastructure is shown to be feasible for this type of medium-resolution data. [ABSTRACT FROM AUTHOR]

The Carpathian bend is amongst the tectonically most active areas in Europe where intraplate subduction triggers sub-crustal earthquakes releasing significant amount of seismic energy in a well-defined seismic zone. To constrain the deep processes by exploiting their linkage to the surface processes an accurate knowledge of surface deformations is required. Detection of small-magnitude tectonic processes with high reliability is a challenge in which the recent space geodetic techniques may bright a breakthrough. In this study we used the archive ENVISAT data set of the European Space Agency to investigate the feasibility limit of detecting crustal deformations in the region of the south Carpathian bend, where past geodetic observations failed to unravel the tectonic processes with high details. Despite the inherent limitations of radar interferometry our results show that coherent velocity field can be estimated with a magnitude of few mm/year. The vertical displacement field suggests subsidence in the Brasov basin which is in agreement with former studies, however radar interferometry can provide a more detailed picture. [ABSTRACT FROM AUTHOR]

Abstract The study of urban subsidence with multi-temporal SAR interferometry is nowadays a well-consolidated approach. Thanks to this powerful technique, it is possible to detect and to measure ground deformation velocity and time series of displacement with high accuracy. This work focuses the analysis on the subsidence phenomenon that is threating the city of Guzman (Jalisco state, Mexico) by means of multi-temporal SAR interferometry applied to a stack of COSMO-SkyMed data, from 2011 to 2015, and a stack of Sentinel-1 TOPSAR mode images, from 2016 to 2018. The work is intended to carry on the study performed with ENVISAT images covering the time span between 2003 and 2010, allowing the continuous monitoring of the deformation process. [ABSTRACT FROM AUTHOR]

Knowledge of backscatter change is important to accurately retrieve elevation change time series from satellite radar altimetry over continental ice sheets. Previously, backscatter coefficients generated in two cases, namely with and without accounting for backscatter gradient (BG), are used. However, the difference between backscatter time series obtained separately in these two cases and its impact on retrieving elevation change are not well known. Here we first compare the mean profiles of the Ku and Ka band backscatter over the Greenland ice sheet (GrIS), with results illustrating that the Ku-band backscatter is 3 ∼ 5 dB larger than that of the Ka band. We then conduct statistic analysis about time series of backscatter formed separately in the above two cases for both Ku and Ka bands over two regions in the GrIS. It is found that the standard deviation of backscatter time series becomes slightly smaller after removing the BG effect, which suggests that the method for the BG correction is effective. Furthermore, the impact on elevation change from backscatter change due to the BG effect is separately assessed for both Ku and Ka bands over the GrIS. We conclude that Ka band altimetry would benefit from a BG induced backscatter analysis (∼10% over region 2). This study may provide a reference to form backscatter time series towards refining elevation change time series from satellite radar altimetry over ice sheets using repeat-track analysis. [ABSTRACT FROM AUTHOR]

The Satellite Laser Ranging (SLR) technology is used to accurately determine the position of space objects equipped with so-called retro-reflectors or retro-reflector arrays (RRA). This type of measurement allows to measure the range to the spacecraft with high precision, which leads to determination of very accurate orbits for these targets. Non-active spacecraft, which are not attitude controlled any longer, tend to start to spin or tumble under influence of the external and internal torques and forces. If the return signal is measured for a non-spherical non-active rotating object, the signal in the range residuals with respect to the reference orbit is more complex. For rotating objects the return signal shows an oscillating pattern or patterns caused by the RRA moving around the satellite’s centre of mass. This behaviour is projected onto the radial component measured by the SLR. In our work, we demonstrate how the SLR ranging technique from one sensor to a satellite equipped with a RRA can be used to precisely determine its spin motion during one passage. Multiple SLR measurements of one target over time allow to accurately monitor spin motion changes which can be further used for attitude predictions. We show our solutions of the spin motion determined for the non-active ESA satellite Envisat obtained from measurements acquired during years 2013–2015 by the Zimmerwald SLR station, Switzerland. All the necessary parameters are defined for our own so-called point-like model which describes the motion of a point in space around the satellite centre of mass. [ABSTRACT FROM AUTHOR]

Radar altimetry was initially designed to measure the marine geoid. Thanks to the improvement in the orbit determination from the meter to the centimeter level, this technique has been providing accurate measurements of the sea surface topography over the open ocean since the launch of Topex/Poseidon in 1992. In spite of a decrease in the performance over land and coastal areas, it is now commonly used over these surfaces. This study presents a semi-automatic method that allows us to discriminate between acquisitions performed at high tides and low tides. The performances of four radar altimetry missions (ERS-2, ENVISAT, SARAL, and CryoSat-2) were analyzed for the retrieval of sea surface height and, for the very first time, of the intertidal zone topography in a coastal lagoon. The study area is the Arcachon Bay located in the Bay of Biscay. The sea level variability of the Arcachon Bay is characterized by a standard deviation of 1.05 m for the records used in this study (2001-2017). Sea surface heights are very well retrieved for SARAL (R~0.99 and RMSE < 0.23 m) and CryoSat-2 (R > 0.93 and RMSE < 0.42 m) missions but also for ENVISAT (R > 0.82 but with a higher RMSE >0.92 m). For the topography of the intertidal zone, very good estimates were also obtained using SARAL (R~0.71) and CryoSat-2 (R~0.79) with RMSE lower than 0.44 m for both missions. [ABSTRACT FROM AUTHOR]

The rotational state of Envisat is re-estimated using the specular glint times in optical observation data obtained from 2013 to 2015. The model is simplified to a uniaxial symmetric model with the first order variation of its angular momentum subject to a gravity-gradient torque causing precession around the normal of the orbital plane. The sense of Envisat’s rotation can be derived from observational data, and is found to be opposite to the sense of its orbital motion. The rotational period is estimated to be ( 120.674 ± 0.068 ) · exp ( 4.5095 ± 0.0096 ) × 10 - 4 · t s , where t is measured in days from the beginning of 2013. The standard deviation is 0.760 s, making this the best fit obtained for Envisat in the literature to date. The results demonstrate that the angle between the angular momentum vector and the negative normal of the orbital plane librates around a mean value of 8.53 ° ± 0.42 ° with an amplitude from about 0.7 ° (in 2013) to 0.5 ° (in 2015), with the libration period equal to the precession period of the angular momentum, from about 4.8 days (in 2013) to 3.4 days (in 2015). The ratio of the minimum to maximum principal moments of inertia is estimated to be 0.0818 ± 0.0011 , and the initial longitude of the angular momentum in the orbital coordinate system is 40.5 ° ± 9.3 ° . The direction of the rotation axis derived from our results at September 23, 2013, UTC 20:57 is similar to the results obtained from satellite laser ranging data but about 20 ° closer to the negative normal of the orbital plane. [ABSTRACT FROM AUTHOR]

Knowledge of interannual mass variations of the Antarctic ice sheet (AIS) associated with its surface mass change is important for correctly interpreting the long-term mass trend and evaluating the fidelity of surface mass balance from regional climate models. Here, we revisit the interannual anomalies of mass change from Gravity Recovery and Climate Experiment and elevation change from ENVISAT over the AIS during 2003-2009, with the objective of obtaining higher resolution interannual mass anomalies based on ENVISAT data. High positive correlations (>0.6) between the two interannual anomalies are primarily found over the west AIS and coastal regions in the east AIS, occupying more than 40% of the AIS. By combining the two interannual anomalies, we are able to estimate the density of snow/ice changing interannually over regions in the AIS. Especially over the Amundsen Sea sector with significant interannual signals, the temporal variability of the density of snow/ice associated with interannual anomalies is shown for the first time, which agrees with the events of excess snow accumulation and the accelerated ice discharge occurring there. Furthermore, we demonstrate the feasibility of obtaining higher resolution interannual mass anomalies over the west AIS, based on the density-corrected ENVISAT data. Negative correlations, which were also found in a previous study, are likely related to errors in the relatively weak interannual signals. [ABSTRACT FROM AUTHOR]

Satellite altimetry has been widely used for inland water monitoring and modeling in the present decade. In this paper, the availability, data quality, and quantity of a number of spaceborne radar altimetry missions (including Topex/Poseidon (TP), ERS-2, Envisat, Jason-1/−2/−3, CryoSat-2, Saral, and Sentinel-3) are investigated. This is, to the best of our knowledge, the first paper to investigate the influences of onboard trackers, satellite flying directions, and land contamination on Level-1 waveforms and Level-2 measurements over large mountainous lakes. The analyses were conducted over eight Tibetan lakes, which are of varying sizes from ca. 93 to 1046 km2 and are sampled by multiple altimeters. From the results presented in this paper, it is demonstrated that the previous generation of altimeters, such as TP, Jason-1, ERS-2, and Envisat, shows a higher percentage of data unavailability and lower valid observation rates. Investigations of Level-1 waveforms show onboard tracker failing in locking on the lake surface, resulting in data loss or invalid measurements. In addition, the onboard tracking systems are sometimes unstable, resulting in larger along-track standard deviations (SD) (SD > 15 cm). In contrast, the recent generation of altimeters, i.e., Jason-3 and Sentinel-3 with open-loop tracking mode, significantly increases the data availability (> 90% passes and > 60% individual observations) and delivers higher precision measurements (SD around 10 cm). Moreover, the waveform leading edge is very consistent, indicating more stable onboard tracking. Higher quality Jason-3 and Sentinel-3 data allow monitoring of sub- and quasi-monthly lake variations, which are not revealed by e.g., TP and ERS-2 data due to poorer signal-to-noise ratios. Exceptionally, Saral Ka-band altimeter, operated in closed-loop tracking mode, is less affected by flying directions and land contamination (topography and landscapes), delivering high quality measurements (SD around 7 cm for 40 Hz). This study provides a comprehensive comparison of multiple altimeters in monitoring lakes in mountainous areas, and demonstrates the substantial improvements achieved in the past decades. However, care has to be taken when merging data from old generation altimetry missions over mountainous lakes. The lessons learned from these Tibetan lakes can be taken across to other mountain lakes. • Comprehensive assessment of multiple altimeters performance over Tibetan lakes. • Investigation of influences of onboard trackers on Level-1 waveforms and Level-2 measurements. • Onboard tracking failure is largely responsible for erroneous measurements contained in the GDR. • Distinctive improvements (∼ 100% data availability & < 10 cm precision) achieved during 1992–2021. [ABSTRACT FROM AUTHOR]

From January 2009 to April 2012 a satellite survey of the central and southeastern parts of the Baltic Sea was carried out by the Space Radar Laboratory at the Space Research Institute of Russian Academy of Sciences (RAS). The main attention was focused on the detection of oil pollution as well as biogenic and anthropogenic surfactant films. The basic data are high resolution radar images obtained by advanced synthetic aperture radar (ASAR) on board of the Envisat satellite of the European Space Agency. Remotely sensed data in visual and infrared (IR) bands acquired by sensors MERIS Envisat, MODIS-Terra and -Aqua, and AVHRR NOAA nearly simultaneously with the ASAR images, were processed and analysed in order to facilitate the discrimination between different types of surface pollutants, to understand a comprehensive features of meteorological and hydrodynamic processes in the sea area of investigation, and to reveal factors determining pollutants spread and drift. The regions of the most intense oil pollution are outlined.