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Permafrost thaw in Arctic regions is increasing methane (CH4) emissions to the atmosphere but quantification of such emissions is difficult given the large and remote areas impacted. Hence, Earth Observation (EO) data are critical for assessing both permafrost thaw, associated ecosystem change, and increased CH4 emissions. Often extrapolation from field measurements using EO is the approach employed. However, there are key challenges to consider – that landscape CH4 emissions result from a complex local-scale mixture of micro-topographies and vegetation types that support widely differing CH4 emissions and the difficulty in detecting the initial stages of permafrost degradation before vegetation transitions have occurred. This study considers the use of a combination of ultra-high resolution unoccupied aerial vehicle (UAV) data, together with Sentinel-1 and -2 data to extrapolate field measurements of CH4 emissions from a set of vegetation types which capture the local variation in vegetation on degrading palsa wetlands. We show that the ultra-high resolution UAV data can map spatial variation in vegetation relevant to variation in CH4 emissions and extrapolate these across the wider landscape. We further show how Sentinel-1 and Sentinel-2 can be used. By way of a soft classification, and simple correction of misclassification bias of a hard classification, the output vegetation mapping and subsequent extrapolation of CH4 emissions matched closely that generated using the UAV data. InSAR assessment of subsidence together with the vegetation classification suggested that high subsidence rates of palsa wetland can be used to quantify areas at risk of increased CH4 emissions. We estimate that a transition of an area currently experiencing subsidence to fen type vegetation are estimated to increase emissions from 116 kg CH4 season−1 from the 50 ha study area, to emissions as high as 6500 to 13000 kg CH4 season−1. The key outcome from this study is that a fusion of EO data types provides the ability to estimate CH4 emissions from large geographies covered by a fine mixture of vegetation types and vulnerable to transitioning to CH4 emitters in the near future. This points to an opportunity to measure and monitor CH4 from the Arctic over space and time with confidence.

The cessation of dewatering following coalfield abandonment results in the rise of minewater, which can create significant changes in the local and regional hydrogeological regime. Monitoring such change is challenging but essential to avoiding detrimental consequences such as groundwater contamination and surface flooding. Inverse modelling methods using satellite radar interferometry (InSAR) have proven capable for retrospectively mapping minewater level changes, however, there is a need for the capability to remotely monitor changes as they occur. In this study, ground deformation measurements obtained from InSAR are used to develop a method to remotely monitor the spatio-temporal rise of minewater, which could be implemented in near real-time. The approach is demonstrated over the Horlivka mining agglomeration, Ukraine, where there is no other feasible approach possible due to a lack of safe ground access. The results were blindly validated against in-situ measurements before being used to forecast the time until minewater will reach the natural water table and Earth's surface. The findings reveal that, as a result of military conflict in Donbas, an environmental catastrophe could occur where potentially radioactive minewater is forecast to reach the natural water table between May and August of 2024.

The Humbly Grove Field has, for the UK, a unique development history. It was discovered as an oilfield in May 1980 and produced as an oilfield until 2000 along with small satellite fields Herriard (developed) and Hester9s Copse (not developed). Peak production of 2219 bopd was achieved during July 1986 but, by October 1988, the rate had fallen to around 1000 bopd, a rate that was more or less maintained until October 1995 after which the production fell rapidly. At this point the decision was taken to reconfigure the field as a gas storage facility. Significant renewed pressure depletion occurred between 2000 and 2005, following which first cushion and then storage gas was injected into two reservoirs: the Middle Jurassic, Great Oolite Group and the uppermost Triassic, Rhaetian Westbury Formation. Gas storage operations commenced in 2005 and the reservoirs have undergone cyclical gas injection and gas withdrawal since that date. The cyclical injection of gas and re-pressuring of the Great Oolite reservoir causes mobile oil to be swept towards dedicated oil production wells. This operates effectively as an enhanced oil recovery scheme. The co-produced liquid hydrocarbons provide a valuable secondary income stream for the field.

Catastrophic failure of a tailings dam at an iron ore mine complex in Brumadinho, Brazil, on 25th January 2019 released 11.7 million m3 of tailings downstream. Although reportedly monitored using an array of geotechnical techniques, the collapse occurred without any apparent warning. It claimed more than 200 lives and caused considerable environmental damage. Here we present the Intermittent Small Baseline Subset (ISBAS) technique on satellite-based interferometric synthetic aperture radar (InSAR) data to assess the course of events. We find that parts of the dam wall and tailings were experiencing deformation not consistent with consolidation settlement preceding the collapse. Furthermore, we show that the timing of the dam collapse would have been foreseeable based on this observed precursory deformation. We conclude that satellite-based monitoring techniques may help mitigate similar catastrophes in the future. Ground deformation and a sudden acceleration of movement in the final two months preceded the catastrophic collapse of the Brumadinho Tailings Dam in Brazil, according to advanced analyses of InSAR remote sensing data.

This paper describes a novel methodology where Machine Learning Algorithms (MLAs) have been integrated to assess the landslide risk for slow moving mass movements, processes whose intermittent activity makes challenging any risk analysis worldwide. MLAs has been trained on datasets including Interferometric Synthetic Aperture Radar (InSAR) and additional remote sensing datasets such as aerial stereo photographs and LiDAR and tested in the Termini-Nerano landslides system (southern Apennines, Italy). The availability of such a wealth of materials allows also an unprecedented spatio-temporal reconstruction of the volume and the kinematic of the landslides system through which we could generate and validate the hazard map. Our analysis identifies fifteen slow-moving phenomena, traceable since 1955, whose total area amounts to 4.1 × 105 m2 and volume to ~1.4 × 106 m3. InSAR results prove that seven out of the fifteen slow-moving landslides are currently active and characterized by seasonal velocity patterns. These new insights on the dynamic of the landslides system have been selected as the main independent variables to train three MLAs (Artificial Neural Network, Generalized Boosting Model and Maximum Entropy) and derive the landslide hazard for the area. Finally, official population and buildings census data have been used to assess the landslide risk whose highest values are located in the crown area, south of Termini village, and nearby Nerano. This new methodology provides a different landslide risk scenario compared to the existing official documents for the study area and overall new insights on how to develop landslide risk management strategies worldwide based on a better understanding of slope processes thanks to the latest satellite technologies available.

Greater awareness of the serious human rights abuses associated with the extraction and trade of cobalt in the Democratic Republic of the Congo (DRC) has applied increasing pressure for businesses to move towards more responsible and sustainable mineral sourcing. Artisanal and small-scale mining (ASM) activities in rural and remote locations may provide heightened opportunities to conceal the alleged human rights violations associated with mining, such as: hazardous working conditions, health impacts, child labour, child trafficking, and debt bondage. In this study, we investigate the feasibility of the Intermittent Small Baseline Subset (ISBAS) interferometric synthetic aperture radar (InSAR) method, teamed with high temporal frequency Sentinel-1 imagery, for monitoring ASM activity in rural locations of the &ldquo, Copperbelt&rdquo, the DRC. The results show that the ISBAS descriptive variables (mean, standard deviation, minimum, and maximum) were significantly different (p-value = &le, 0.05) between mining and non-mining areas. Additionally, a significant difference was found for the ISBAS descriptive variables mean, standard deviation, and minimum between the different mine types (industrial, surface, and tunnels). As expected, a high level of subsidence (i.e., negative ISBAS pixel value) was a clear indicator of mine activity. Trial activity thresholds were set for the descriptive variables mean (-2.43 mm/yr) and minimum (-5.36 mm/yr) to explore an ISBAS approach to active mine identification. The study concluded that the ISBAS method has great potential as a monitoring tool for ASM, with the ability to separate mining and non-mining areas based on surface motion values, and further distinguish the different mine types (industrial, surface, and tunnel). Ground data collection and further development of ISBAS analysis needs to be made to fully understand the value of an ISBAS-based ASM monitoring system. In particular, surrounding the impact of seasonality relative to longer-term trends in ASM activity.

Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make a significant cost-effective contribution to the progressive abandonment strategy of recently closed coalfields. Applications of DInSAR over coalfields have observed heave in coal measures rocks and temporal correlations between the rise of mine water and deformation time-series. The cessation of systematic dewatering can have a variety of detrimental impacts and knowledge of the time-scales (i.e. the rate of rebound) and structure of the mine system are crucial to the remediation strategy. Although mine plans and borehole measurements provide vital information in this regard, mine plans are often incomplete or inaccurate, whereas monitoring boreholes are spatially sparse. Consequently, groundwater can flow in unanticipated directions via goaf, mine shafts and roadways, making it difficult to determine where the impacts of rebound are likely to occur. In this study, ground deformation data obtained using ISBAS DInSAR on ENVISAT (2002–2009) and Sentinel-1 (2015–2019) data are used to develop a simple method to model groundwater rebound in abandoned coalfields. A forward analytical model based upon the principle of effective stress and mine water ponds is first implemented to estimate surface heave in response to changes in groundwater levels measured in monitoring boreholes. The forward model is then calibrated and validated using the ground deformation data. The DInSAR data were subsequently inverted to map the change in groundwater levels in greater detail across the coalfield and forecast surface discharges in order to support mitigation strategies.

80% of peatlands in Indonesia and Malaysia (15% of Earth's soil carbon) are now drained for production of pulp wood and palm oil. Associated increased peat decomposition and large-scale forest fires are now significant contributors to global greenhouse gas emissions. However, carbon losses from these processes and the impact of peatland drainage remain poorly quantified across SE Asia because of the challenging scale and inaccessibility of dense tropical peatland forests.Space-based platforms offer the opportunity for regular and efficient pan-regional monitoring and overcome inaccessibility of tropical peatland environments. A development in satellite interferometric synthetic aperture radar (InSAR) in monitoring surface motion has the potential to solve this problem. A new ‘intermittent small baseline subset’ (ISBAS) modelling technique provides excellent coverage across almost all land surfaces irrespective of ground cover, enabling long-term measurement of peatland surface motion across whole catchments, regions and countries. Importantly, the ISBAS technique is able to determine surface deformation under tropical forest canopy using C-band InSAR, enabling continuous monitoring of surface motion ranging from 0.1–40cm/yr at spatial scales ≥90x90m.This project aims to determine whether rate of subsidence of the peat surface measured by ISBAS-InSAR is a proxy for rate of carbon loss in tropical peatlands in SE Asia. ISBAS-InSAR time series and field measurements of subsidence will be used to monitor and characterise seasonal tropical peat surface oscillations over time and field radar experiments will investigate C-band radar signal attenuation with the peat surface at different moisture contents.

Rapid population growth in South-East Asia has placed immense pressure upon lowland regions both to supply food and employment and space for residential, commercial and infrastructure development. This pressure has led to sites on tropical peatland previously considered unsuitable for development to be revisited. One such site, the KLIA2 terminal and runway, Kuala Lumpur International Airport which opened in May 2014 at a cost of 3.6 billion MYR has been beset by well documented subsidence problems. Coverage of the tropics by the Sentinel-1 satellite constellation presents an opportunity to monitor the ongoing subsidence at KLIA 2, identify potential knowledge gaps and help inform more sustainable infrastructure development in tropical peatland regions. Our results show that the ISBAS InSAR method produces reproducible ground deformation maps which can clearly identify the patterns of deformation across both urban infrastructure and adjacent rural plantations and tropical peat swamp. This is particularly well defined around the terminal building at KLIA-2 where different ground preparation and foundation design have resulted in stable terminal buildings and subsidence of surrounding pavement. Deformation is greatest in the runway area where alternate bands of uplift and subsidence presumably accompany the greatest loads associated with landing aircraft. In contrast, areas where peat replacement was the primary form of ground preparation, ground motion is stable, however this comes at high economic and environmental cost.

Retrieving ground motion information for non-urban and semi-vegetated areas using differential Interferometric Synthetic Aperture Radar (InSAR) and Small Baseline Subset (SBAS) approaches with C-band satellite radar imagery is challenging due to temporal decorrelation. By exploiting six stacks of medium resolution ERS-1/2 SAR images acquired between 1992 and 2000 over four regions of interest in the UK, this paper demonstrates the performance of the recently developed processing method Intermittent SBAS (ISBAS). This approach builds upon the conventional low-resolution SBAS method and, by relaxing the approach to selecting image pixels to process and accounting for the intermittent nature of non-urban targets, is capable to extend the coverage of motion results across the full range of land cover types, even those typically unfavourable for InSAR. On average, the new ISBAS implementation provides 4 to 26 times more coverage than SBAS for the processed regions, with the spatial coverage of ground motion solutions increasing from only 4–12% land pixels with SBAS, to 39–99% with ISBAS. Despite relying only on temporal subsets of the networks of small baseline interferograms, intermittently coherent pixels show velocity standard errors of 0.8–1.4 mm/year on average, hence retain sub-millimetre to millimetre precision. The empirical relationships between intermittent coherence and standard errors in the estimated ground motion velocity are computed for each of the six datasets, and confirm that errors are controlled by the number of independent observations used for each image pixel to extract the ISBAS solution. In particular, velocity standard errors e vel for the intermittently coherent pixels are inversely proportional to the square root of the number of best coherence interferograms used, n i , and can be modelled as e vel = 11 / n i mm/year on average for the six datasets. The established empirical relationship also allows informed decisions on the ISBAS threshold for n i to be made. This is achieved by setting the maximum acceptable error in the velocity estimate e MAX , and then computing the corresponding minimum n i to accept an intermittently coherent pixel that will guarantee the desired precision. In the present era of ‘big SAR data’ and their derived ‘big InSAR data’, we discuss perspectives on the use of huge datasets of thousands or even millions of ground deformation time series – such as those produced using ISBAS, with a particular focus on the veracity of big data and the need for a quality assessment check-point in the ‘big InSAR data’ cycle.

The advent of new satellite and data processing techniques have meant that routine, operational and reliable surveys of land motion on a regional and national scale are now possible. In this paper, we apply a novel satellite remote sensing technique, the Intermittent Small Baseline Subset method, to data from a new satellite mission, Sentinel-1, and demonstrate that a wide area map of ground deformation can be generated that supports the regulation of a range of energy-related activities. The area for the demonstration is mainland Scotland (∼75,000 km2) and the land motion map required the processing of some 627 images acquired from March 2015 to April 2017. The results show that land motion is encountered almost everywhere across Scotland, dominated by subsidence over peatland areas. However, many other phenomena are also encountered including landslides and deformation associated with mining and civil engineering activities. Considering specifically Petroleum Exploration and Development Licence areas offered under the 14th Onshore Licensing Round in the UK, examples of the types of land motion are shown, including an example related to soil restoration by a wind farm. It is demonstrated that, in Scotland at least, almost all licence areas contain deformation of one form or another and, furthermore, the causes of that subsidence are dynamic and likely to be changing from year-to-year. Therefore, maps like this are likely to be of enormous use in a regulatory framework to scope out pre-existing problems in a licence area and to ensure that the correct monitoring framework is put in place once activities begin. They can also provide evidence of good practice and give assurance against litigation by third parties.

In this paper, TLS error sources are discussed and the types and magnitudes of these errors are observed. Furthermore, a procedure for eliminating laser scanner outliers and reducing noise is introduced. For this purpose, two TLS instruments have been examined: Leica Scanstation P20 and P40. The results of the tests reveal the average noise level (mean errors) between two scans can be improved by using a surface model rather than direct point to point differencing, with improvements from 2.8 mm to 1.7 mm and from 0.7 mm to 0.2 mm for P20 and P40 respectively. In addition, the best fit local planes technique can remove outliers without reducing point density. Therefore, the maximum errors decreased from 50 mm (due to outliers) to 11 mm and from 13 mm (due to outliers) to 1 mm for P20 and P40 respectively.

A large scale study of landslide processes was undertaken by coupling conventional geomorphological field surveys with aerial photographs along with an advanced Interferometric Synthetic Aperture Radar (InSAR) analysis of ground instability in north-western Sicily. COSMO-SkyMed satellite images for the period between 2008 and 2011 were processed using the Intermittent Small BAseline Subset (ISBAS) technique, recently developed at the Department of Civil Engineering of the University of Nottingham. The use of ISBAS allowed the derivation of ground surface displacements across non-urbanized areas, thus overcoming one of the main limitations of conventional interferometric techniques. ISBAS provides ground motion information not only for urban but also for rural, woodland, grassland and agricultural terrains, which cover > 60% of north-western Sicily, thereby improving by 40 times in some cases, the slope instability investigation capabilities of InSAR methods. ISBAS ground motion data enabled the updating of the landslide inventory for the areas of Piana degli Albanesi and Marineo (over 130 km2), which encompass a number of active, dormant and inactive landslides according to the pre-existing landslide inventory maps produced through aerial photo-interpretation and local field checks. An average of ∼ 7000 ISBAS pixels km− 2 allowed the detection of small displacements in regions difficult to access. In particular, 226 landslides – mainly slides, flows and creep and four badlands were identified, comprising a total area of 25.3 km2. When compared to the previous landslide inventory maps, 84 phenomena were confirmed, 67 new events were detected and 79 previously mapped events were re-assessed, modifying their typology, boundary and/or state of activity. Because the InSAR method used here is designed to measure slow rates of velocity and therefore may not detect fast-moving, events such as falls and topples, the results for Piana degli Albanesi and Marineo demonstrate the validity of this method to support land management, underlying the time and cost benefits of a combined approach using traditional monitoring procedures and satellite InSAR methods especially if slow-moving slope movements prevail.

Peatland surface motion is a key property of peatland that relates to condition. However, field‐based techniques to measure surface motion are not cost‐effective over large areas and long time periods. An alternative method that can quantify peatland surface motion over large areas is interferometric synthetic aperture radar. Although field validation of the accuracy of this method is difficult, the value of InSAR as a means of quantifying peat condition can be tested. To achieve this the characteristics of InSAR time series measured over an18‐month period at 22 peatland sites in the Flow Country northern Scotland were compared to site condition assessment based on plant functional type and site management history. Sites in good condition dominated by Sphagnum display long‐term stability or growth and a seasonal cycle with maximum uplift and subsidence in Aug‐Nov and April‐June respectively. Drier and partially drained sites dominated by shrubs display long‐term subsidence with maximum uplift and subsidence in July‐Oct and Feb‐June respectively. Heavily degraded sites with large bare peat extent display subsidence with no distinct seasonal oscillations. Seasonal oscillation in surface motion at sites with a dominant non‐vascular plant community is interpreted as resulting from changes in seasonal evaporative demand. On sites with extensive vascular plants cover and falling water table, surface oscillations are interpreted as representing sustained drawdown during the growing season and subsequent recharge in late winter. This study highlights the potential to use InSAR to characterize peatland condition and provide a new view of the surface dynamics of peatland landscapes.

The launch of Copernicus, the largest Earth Observation program to date, is significant due to the regular, reliable and freely accessible data to support space-based geodetic monitoring of physical phenomena that can result in natural hazards. In this study, wide area interferometric synthetic aperture radar (InSAR) capability is demonstrated by processing 436 Copernicus Sentinel-1 C-Band SAR images (May 2015–May 2017) using the Intermittent Small Baseline Subset (ISBAS) method to produce a wide-area-map (WAM) covering the Netherlands and extending into neighbouring areas of Belgium and Germany. Ground deformation velocities from six interferometric stacks, containing over 19 million measurements, were mosaicked together to produce a seamless ISBAS-WAM over some 53,000 km2 achieving a ground coverage of 94%. The retrieval of low-resolution measurements over soft surfaces (i.e. agricultural fields, forests, semi-natural areas and wetlands) afforded by the ISBAS technique was crucial due the dominance of non-urban land cover. Across the WAM, the spatial distribution of deformations concurs with independent sources of data, such as previous persistent scatterer interferometry (PSI) deformation maps, models of subsidence and settlement susceptibility, and quantitatively with GPS measurements over the Groningen gas field. A statistical analysis of the velocities reveals that intermittently coherent measurements in rural areas can provide reliable, additional deformation information with a very high degree of confidence (5σ), much of which is spatially correlated to known deformation features associated with compressible soils, infrastructure, peat oxidation, oil and gas production, salt mining and underground and opencast mining.Remotely derived deformation products, with near complete spatial coverage, provide a powerful tool for mitigation and remediation against adverse geological conditions to help in the protection of assets, property and life. The ISBAS-WAM demonstrates that routine generation of such products on a continental scale is now theoretically achievable, given the recent establishment of the Copernicus programme and the development of state-of-the-art InSAR methods such as ISBAS.

This work assesses the feasibility of national ground deformation monitoring of Great Britain using synthetic aperture radar (SAR) imagery acquired by Copernicus’ Sentinel-1 constellation and interferometric SAR (InSAR) analyses. As of December 2016, the assessment reveals that, since May 2015, more than 250 interferometric wide (IW) swath products have been acquired on average every month by the constellation at regular revisit cycles for the entirety of Great Britain. A simulation of radar distortions (layover, foreshortening, and shadow) confirms that topographic constraints have a limited effect on SAR visibility of the landmass and, despite the predominance of rural land cover types, there is potential for over 22,000,000 intermittent small baseline subset (ISBAS) monitoring targets for each acquisition geometry (ascending and descending) using a set of IW image frames covering the entire landmass. Finally, InSAR results derived through ISBAS processing of the Doncaster area with an increasing amount of Sentinel-1 IW scenes reveal a consistent decrease of standard deviation of InSAR velocities from 6 mm/year to ≤2 mm/year. Such results can be integrated with geological and geohazard susceptibility data and provide key information to inform the government, other institutions and the public on the stability of the landmass.

The high resolution TerraSAR-X dataset was employed with DInSAR and persistent scatterer interferometry (PSI) technique for subsidence monitoring in a mountainous area. For DInSAR technique, the generally used SRTM and relief-DEM, which was derived from aerial topographic map, were used to evaluate the influence of external DEM. The results show that SRTM could not fully compensate the complex topography of the research area. The corner reflectors installed during the acquisition of SAR dataset were used to estimate the accuracy of geocoding. The terrain corrected geocoding results based on relief-DEM were much better than using SRTM, with the root mean square error (RMSE) being 6.35 m in X direction and 11.65 m in Y direction (both in UTM projection), around one pixel of the multilooked intensity image to be geocoded. For PSI technique, the results from time-series analysis of multi-baseline differential interferograms were integrated to restrict only persistent scatterer candidates near the boundary of subsiding area for regression analysis. The results demonstrate that PSI can refine the boundary of subsidence, which could then be used to derive some angular parameters to help people to learn the law of subsidence caused by repeated excavation in this area.

Interferometric Synthetic Aperture Radar (InSAR) and Differential Interferometric Synthetic Aperture Radar (DInSAR) have shown numerous applications for subsidence monitoring. In the past 10 years, the Persistent Scatterer InSAR (PSI) and Small BAseline Subset (SBAS) approaches were developed to overcome the problem of decorrelation and atmospheric effects, which are common in interferograms. However, DInSAR or PSI applications in rural areas, especially in mountainous regions, can be extremely challenging. In this study we have employed a combined technique, i.e., SBAS-DInSAR, to a mountainous area that is severely affected by mining activities. In addition, L-band (ALOS) and C-band (ENVISAT) data sets, 21 TerraSAR-X images provided by German Aerospace Center (DLR) with a high resolution have been used. In order to evaluate the ability of TerraSAR-X for mining monitoring, we present a case study of TerraSAR-X SAR images for Subsidence Hazard Boundary (SHB) extraction. The resulting data analysis gives an initial evaluation of InSAR applications within a mountainous region where fast movements and big phase gradients are common. Moreover, the experiment of four-dimension (4-D) Tomography SAR (TomoSAR) for structure monitoring inside the mining area indicates a potential near all-wave monitoring, which is an extension of conventional InSAR.

For centuries the promontory of Capo Colonna in Calabria region, southern Italy, experienced land subsidence and coastline retreat to an extent that the archaeological ruins of the ancient Greek sanctuary are currently under threat of cliff failure, toppling and irreversible loss. Gas extraction in nearby wells is a further anthropogenic element to account for at the regional scale. Exploiting an unprecedented satellite Synthetic Aperture Radar (SAR) time series including ERS-1/2, ENVISAT, TerraSAR-X, COSMO-SkyMed and Sentinel-1A data stacks acquired between 1992 and 2016, this paper presents the first and most complete Interferometric SAR (InSAR) baseline assessment of land subsidence and coastal processes affecting Capo Colonna. We analyse the regional displacement trends, the correlation between vertical displacements with gas extraction volumes, the impact on stability of the archaeological heritage, and the coastal geohazard susceptibility. In the last 25 years, the land has subsided uninterruptedly, with highest annual line-of-sight deformation rates ranging between -15 and -20 mm/year in 2011-2014. The installation of 40 pairs of corner reflectors along the northern coastline and within the archaeological park resulted in an improved imaging capability and higher density of measurement points. This proved to be beneficial for the ground stability assessment of recent archaeological excavations, in an area where field surveying in November 2015 highlighted new events of cliff failure. The conceptual model developed suggests that combining InSAR results, geomorphological assessments and inventorying of wave-storms will contribute to unveil the complexity of coastal geohazards in Capo Colonna.

The differential interferometric synthetic aperture radar (DInSAR) remote sensing technique has proven to be invaluable in the remote monitoring of earth surface movements associated with the extraction and geostorage (subsurface injection) of natural resources (water, oil, gas). However, a significant limitation of this technique is the low density and uneven coverage that may be achieved over vegetated rural environments. The Intermittent Small Baseline Subset (ISBAS) method, an amended version of the established SBAS algorithm, has been designed to improve coverage over rural, vegetated, land cover classes by allowing for the intermittent coherence that is predominant in such areas. In this paper we perform a validation of the ISBAS method over an area of gas production and geostorage in North Holland, the Netherlands. Forty-two ERS-2 (SAR) C-band images (1995–2000) and 63 ENVISAT (ASAR) C-band images (2003–2010) were processed using the ISBAS technique and the derived measurements enabled the identification of subsidence patterns in rural and urban areas alike. The dominant feature was an area of subsidence to the west of Alkmaar, attributed to natural gas production from the Bergermeer reservoir, where subsidence rates in the region of 3 mm/year were measured. Displacements derived using linear and non-linear surface deformation models were validated with respect to the first order system of levelling benchmarks which form the Amsterdam Ordnance Datum (NAP). It was established that ISBAS products were accurate to within 1.52 mm/year and 1.12 mm/year for the ERS and ENVISAT data sets respectively. Errors achieved were comparable to results using persistent scatterers interferometry (PSI) during a validation activity carried out in the European Space Agency Terrafirma project. These results confirm the capability of the ISBAS method to provide a more regular sampling of land motion measurements over gas fields that may be critically used in future to infer the properties of buried, fluid-filled, porous rock.

A ZWD correction method is also presented and results are shown, which improve upon those without the correction. The ZWD estimates are produced using an undifferenced global navigation satellite system GNSS processing technique known as PPP. This, coupled with the chosen PSI method, provides a low noise solution when compared to similar experiments involving the integration of GNSS and interferometric synthetic aperture radar InSAR data. The results show that there is good temporal and spatial correlation between the PPP ZWD estimates and the PSI-derived atmospheric phase contributions. Noticeable improvements in the PSI solution when comparing before and after processing runs to precise levelling observations are shown.

This paper illustrates the capabilities of the Advanced Land Observing Satellite (ALOS) Phased Array Type L-band Synthetic Aperture Radar (PALSAR) instrument in the identification of macro-and meso-scale land deformation caused by the Wenchuan Earthquake of 12 May 2008. The specific location analysed is an area near the south west termination of the rupture zone where fault slip and surface deformations were relatively low and topography is relatively high. A full geometric processing of the interferometric synthetic aperature radar (InSAR) data is performed, including the removal of the stereoscopic effect, and the terrain effect fully compensated by identification and removal of layover and shadow areas. This allows for the full characterization of the main earthquake deformation.

This work presents a Differential SAR Interferometry (DInSAR) analysis of slow-moving landslides in Costa della Gaveta (southern Italy) exploiting the improved spatial density of radar targets provided by the novel Intermittent SBAS (ISBAS) algorithm. Several landslides occurred in this area over the past decade, producing a ground displacement of several centimeters and causing unsafe road and rail traffic conditions. In the 2.4 km2 study area, ISBAS analysis of TerraSAR-X data acquired in 2010–2011 has shown the presence of sixteen phenomena with a southeastern main direction of motion. The DInSAR results agree with both the magnitude and the deformation mechanisms that were mapped during field observations and reported in the geotechnical literature.

In this paper, the capability of the integer ambiguity method to find the absolute position of InSAR data is demonstrated. A radargrammetric model is used for the space triangulation. The method is demonstrated using ERS data of the Thames region and the results are compared to GPS measurements and a digital elevation model. The GPS stations, not visible in the image, are located on the InSAR data using a simple range-Doppler algorithm and an analysis of their positions is undertaken. The results are consistent with other methods but with the advantage that the radargrammetric model is very simple. The results also highlight the problems of integrating GPS data with InSAR data in urban areas where a GPS station may not be representative of the dominant scatterers within a resolution cell, and they suggest methods that might be applied in future to reduce this problem. The model should help the integration of InSAR data with other geometric survey data. Resume Dans cet article on montre l'aptitude de la methode des leves de l'ambiguite par fonction entiere a fournir de maniere absolue la position des donnees interferometriques des radars a synthese d'ouverture (InSAR). On a effectue une triangulation spatiale en utilisant un modele radargrammetrique. On a valide cette methode en utilisant des donnees d'ERS situees dans la region de la Tamise et en comparant les resultats aux determinations GPS et a un MNE. En utilisant un simple algorithme de telemetrie Doppler on a pu localiser sur les donnees InSAR, les stations GPS qui ne sont pas visibles sur l'image, puis on a analyse ces positions. Les resultats sont comparables avec ceux des autres methodes, mais la modelisation radargrammetrique presente l'avantage d'une grande simplicite. Les resultats mettent aussi en evidence les problemes d'integration des donnees GPS dans les donnees InSAR en region urbaine, car les stations GPS ne sont pas necessairement representatives des reflecteurs-radar dominants dans les enregistrements. Aussi a-t-on suggere des methodes propres a reduire ces problemes et que l'on pourrait appliquer a l'avenir. Ce modele pourrait egalement faciliter l'integration des donnees InSAR avec d'autres donnees provenant de leves geometriques. Zusammenfassung In diesem Beitrag wird die Fahigkeit der Integer Ambiguitaten Methode vorgestellt, die das Problem der Bestimmung der absoluten Lage von InSAR Daten lost. Die raumliche Triangulierung erfolgt durch ein radargrammetrisches Modell. Am Beispiel von ERS Daten der Themseregion wird die Methode vorgestellt und die Ergebnisse mit GPS Messungen und DHM Daten verglichen. Da die GPS Stationen im Bild nicht sichtbar sind, werden sie uber einen einfachen Entfernungs-Doppler Algorithmus in den InSAR Daten lokalisiert und die ermittelten Lagekoordinaten analysiert. Das sehr einfache radargrammetrische Modell bietet Ergebnisse, die vergleichbar mit anderen Methoden sind. Die Ergebnisse zeigen aber auch die Probleme bei der Integration von GPS und InSAR Daten in urbanen Gebieten auf. Eine GPS Station ist moglicherweise nicht fur die dominanten Streustellen in einer Auflosungszelle reprasentativ. Es werden Verfahren vorgeschlagen, die dieses Problem in Zukunft reduzieren konnen. Das vorgestellte Modell sollte die Integration von InSAR Daten mit anderen vermessungstechnisch erfassten Geometriedaten unterstutzen. Resumen Este articulo demuestra el potencial del metodo de ambiguedades enteras para determinar la posicion absoluta de datos InSAR. En la investigacion se usa un modelo radargrametrico para la triangulacion espacial. El metodo se comprueba con imagenes ERS de la region del Tamesis comparando los resultados con mediciones realizadas con GPS y con un MDE. Las estaciones GPS, que no se aprecian en la imagen, se localizan en la imagen InSAR usando un algoritmo range-doppler simple y a continuacion se hace un analisis de sus posiciones. Los resultados son consistentes con otros metodos pero con la ventaja de la simplicidad del modelo radargrametrico utilizado. Ademas, los resultados ilustran los problemas de integracion de los datos GPS e InSAR en areas urbanas donde una estacion GPS puede no ser suficientemente representativa de los dispersores dominantes en una celda de resolucion, por lo que se sugieren algunos metodos que podrian aplicarse en el futuro para reducir este problema. El modelo deberia ayudar a integrar los datos InSAR con otros datos geometricos de campo.

Interferometric SAR (InSAR) has established itself as a useful technique for precise cloud-independent topographic surveying and for the monitoring of topographic change at sub-centimetric accuracies. Despite this, measurements of the phase are still only available modulo 2π and this leads to an ambiguity problem that is usually not explicitly resolved. This paper presents a generalised method for the precise determination of the phase ambiguity that is independent of datum and projection biases. The method is based on those applied to Global Navigation Satellite Systems (GNSS) signals and shows that the far-field approximation is insufficient for precise positioning. Geometric similarities between InSAR and radargrammetry are highlighted. The solution presented allows the geolocation of a target to an accuracy limited only by the accuracy of the transmit–receive time of the sensor. Resume Il est etabli que l'interferometrie radar (InSAR) est une technique utile pour les releves topographiques precis meme en presence de nuages et pour le suivi des variations de la topographie avec des precisions sub-centimetriques. Neanmoins les mesures de phase ne peuvent etre faites que modulo 2π, ce qui conduit a un probleme d'ambiguite qui n'est generalement pas resolu de maniere explicite. On presente dans cet article une methode generale de determination precise de l'ambiguite de phase qui soit independante des biais du systeme de projection. Cette methode decoule de celles utilisees pour les signaux GNSS et montre que les approximations faites habituellement sont insuffisantes pour des localisations precises. On met en evidence les analogies geometriques entre radargrammetrie et l'InSAR. La solution obtenue permet finalement de localiser une cible avec une precision qui n'est limitee que par la precision du temps de reception-transmission du capteur. Zusammenfassung Interferometrisches SAR (InSAR) hat sich als nutzliche Technik zur prazisen, wolkenfreien topographischen Vermessung und fur die Erfassung von topographischen Veranderungen im Millimeter Bereich etabliert. Dennoch sind bisher Phasenmessungen nur mit Modulo 2π moglich, was zu einem Mehrdeutigkeitsproblem fuhrt, das meist nicht explizit aufgelost wird. Dieser Beitrag stellt eine generalisierte Methode fur die prazise Bestimmung der Phasenmehrdeutigkeit vor, die unabhangig von systematischen Fehlern bei Datum und Projektion ist. Diese Methode ist ahnlich derjenigen, die auf GNSS Signale angewandt werden, und zeigt, dass die Fernfeld-Naherung unzureichend fur eine genaue Positionierung ist. Die geometrischen Ahnlichkeiten zwischen InSAR und Radargrammetrie werden hervorgehoben. Die vorgeschlagene Losung erlaubt die Geopositionierung eines Zielobjektes mit einer Genauigkeit, die nur von der Genauigkeit der Sende-Empfangszeit des Sensors abhangt.

In the context of recent advances in InSAR processing techniques to retrieve higher persistent scatterer and coherent target densities over unfavourable land cover classes, this study tests the Intermittent Small Baseline Subset (ISBAS) approach to update the landslide inventory around the town of Piana degli Albanesi (Italy), an area where only 2% of the land appears suitable to generate radar scatterers based on a pre-survey feasibility assessment. ISBAS processing of 38 ascending mode and 36 descending mode COSMO-SkyMed StripMap HIMAGE SAR scenes at 3m resolution allows identification of ~726,000 and ~893,000 coherent and intermittently coherent pixels for the ascending and descending data stacks respectively. Observed improvements in the number of ISBAS solutions for the ascending mode are greater than 40 times compared to the conventional SBAS approach, not only for urban and rocky terrains, but also rural and vegetated land covers. Line of sight ground motion rates range between -6.4 and +5.5 mm/yr in 2008-2011, although the majority of the processed area shows general stability, with average rates of -0.6 mm/yr in the ascending and -0.1 mm/yr in the descending mode results. Interpretation of the ISBAS deformation rates, integrated with targeted field surveys and aerial photo-interpretation, provides a new and more complete picture of landslide distribution, state of activity and intensity in the test area, and allows depiction of very slow and extremely slow landslide processes even in areas difficult to access, with unprecedented coverage of results. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.