Differential Interferometric Synthetic Aperture Radar Research Articles

A review on surface deformation evaluation using multitemporal SAR interferometry techniques

Deformation monitoring is a crucial matter to avoid catastrophic failure due to extraction of resources. Radar data, mainly synthetic apreture radar (SAR) data and their diverse techniques are suitable for deformation monitoring. This paper provides a review of SAR data and their techniques for deformation monitoring. It also provides a brief description of Image acquisition, SAR geometry, SAR development, satellite specifications, and commercial software used for Interferometry and deformation monitoring. In the end, it is concluded that the existing SAR techniques are capable of accurate monitoring of land deformation. It is also concluded that persistant InSAR (PSInSAR) gives better results than differential InSAR (DInSAR).

Modelling groundwater rebound in recently abandoned coalfields using DInSAR

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.

Electrical conductivity and ground displacement in permafrost terrain

Permafrost and ground ice are important features of the landscape that can significantly affect infrastructure in cold regions. Information on thaw susceptibility is important for predicting the behaviour of permafrost as an engineering substrate. We compare apparent conductivity surveys to ground displacement obtained from differential interferometric synthetic aperture radar with the objective of establishing apparent conductivity as an indicator of thaw susceptibility for regional characterization of terrain stability and permafrost conditions along the western coast of Hudson Bay, Nunavut. For field conditions where ground displacement and conductivity are influenced by surficial geology, there is a correlation between high seasonal and inter-annual subsidence and low apparent conductivity, and between high seasonal and inter-annual subsidence and high seasonal conductivity ratio, inferred to be indicative of high ice content and thaw-related displacement. For field conditions with no strong influence of surficial geology, a clear correspondence between subsidence and apparent conductivity does not exist. Nevertheless, the geophysical data are useful in identifying relevant factors for characterization of terrain stability such as saline permafrost and an ice-rich top of permafrost that experience significant seasonal fluctuations in unfrozen water content. When utilizing low-induction number electromagnetic surveys in permafrost terrain, apparent conductivity must be corrected for a depth-dependent temperature profile. For this study, correction factors of 6–13% are required to compensate for temperature variation, or 2.1% per °C at half-depth, but this is not necessarily applicable to other temperature profiles.

TimeFun-InSAR algorithm to investigate physical changes at Bromo volcano by using ALOS/PALSAR data sets

Mt. Bromo is geographically located in eastern of Java Island at 112°57'30'' longitude and 7°56' latitude, with a large area of caldera ~10 Km2. The land over the volcano is a perfect area for farming, one of the important factor affects the level of soil fertility is the most mineral rich soils. Volcanic activities at Mt. Bromo has been recorded in 1775 which characterized by small eruptions with cycles ranging from one to five years. Regarding this evidence, we tried to investigate the surface changes over the Mt. Bromo by using Time-Series InSAR with TimeFun algorithm. TimeFun is an extension of SBAS to allow incorporating various functions such as seasonal oscillations, polynomials, and step functions as generally it estimates DEM errors as well and allows missing observation. The maximum allowed baseline value is defined and used to constrain the interferogram pair by selecting manual after differential InSAR processing in single face working. The proposed analysis is based on 27 SAR data sets acquired by the ALOS/PALSAR sensors during the 2007–2017 time interval. The result shows us deformation occurred up to ~10 cm at summit of Mt. Bromo during the eruption period. Time-series monitoring of surface deformation to infer volume changes, geometries and locations of sources of deformation involved in the future eruption

ADVANCED DIFFERENTIAL INTERFEROMETRIC SAR TECHNIQUE A-DINSAR FOR THE STUDY OF LARGE LANDSLIDES

Large landslides are widespread both in the Alps and in Apennines; the observed movements are generally from extremely slow to slow with some occasional acceleration; the sudden and paroxysmal collapse of the whole mass may have catastrophic consequences. They are also difficult to characterize in their boundaries and state of activity and to monitor with traditional tools. The Advanced Differential interferometric SAR (Synthetic Aperture Radar) technique, A-DInSAR, is a remote sensing technique, which is based on satellite radar imagery for the ground motion measurement. It is based on large stacks of SAR images and enables the measure of small displacement of the ground with a millimetThe aim of this study is to apply the A-DInSAR technique in some large landslide in Alps (Brenvetto, Rosone and Alpe Baranca landslides) in order to study the effectiveness of the technique in their study and monitoring.

Monitoring Land Surface Deformation Associated with Gold Artisanal Mining in the Zaruma City (Ecuador)

Underground mining can produce subsidence phenomena, especially if orebodies are surficial or occur in soft rocks. In some countries, illegal mining is a big problem for environmental, social and economic reasons. However, when unauthorized excavation is conducted underground, it is even more dangerous because it can produce unexpected surficial collapses in areas not adequately monitored. For this reason, it is important to find quick and economic techniques able to give information about the spatial and temporal development of uncontrolled underground activities in order to improve the risk management. In this work, the differential interferometric synthetic aperture radar (DInSAR) technique, implemented in the SUBSOFT software, has been used to study terrain deformation related to illegal artisanal mining in Ecuador. The study area is located in Zaruma (southeast of El Oro province), a remarkable site for Ecuadorian cultural heritage where, at the beginning of the 2017, a local school collapsed, due to sinkhole phenomena that occurred around the historical center. The school, named “Inmaculada Fe y Alegria”, was located in an area where mining activity was forbidden. For this study, the surface deformations that occurred in the Zaruma area from 2015 to 2019 were detected by using the Sentinel-1 data derived from the Europe Space Agency of the Copernicus Program. Deformations of the order of five centimeters were revealed both in correspondence of known exploitation tunnels, but also in areas where the presence of tunnels had not been verified. In conclusion, this study allowed to detect land surface movements related to underground mining activity, confirming that the DInSAR technique can be applied for monitoring mining-related subsidence.

Inversion and Analysis of Mining Subsidence by Integrating DInSAR, Offset Tracking, and PIM Technology

High-intensity underground mining generates considerable surface subsidence in mining areas, including ground cracks and collapse pits on roads and farmland, threatening the safety of buildings. Large-amplitude subsidence (e.g., >2 m) is usually characterized by a large phase gradient in interferograms, leading to severe phase decorrelation and unwrapping errors. Therefore, the subsidence on the surface cannot be well derived simply using conventional differential interferometric synthetic aperture radar (DInSAR) or other geodetic measurements. We propose a new method that combines both DInSAR and subpixel offset-tracking technology to improve mine subsidence monitoring over large areas. We utilize their respective advantages to extract both the spatial boundaries and the amplitude of displacements. Using high-resolution RADARSAT-2 SAR images (5 m) acquired on February 13, 2012, and November 27, 2012, in the Shendong Coalfield located at the border between Shaanxi Province and Inner Mongolia Province, China, we obtain the subcentimetre-level subsidence of the mine boundary by DInSAR and resolve the metre-level mine subsidence centre based on subpixel offset tracking. The whole subsidence field is obtained by combining and analyzing the subcentimetre-level and the metre-level subsidence. We use the probability integral method (PIM) function model to fit the boundary and central mine subsidence to reconstruct the spatial distribution of the mine subsidence. Our results show that the maximum central subsidence reaches ~4.0 m (beyond the monitoring capabilities of DInSAR), which is generally in agreement with the maximum subsidence of ~4.0-5.0 m from field investigation. We also model the boundary and the central subsidence (the final fitting coefficient is 0.978). Our findings indicate that the offset-tracking method can compensate for the deficiency of DInSAR in large-amplitude subsidence extraction, and the inclusion of the PIM technique helps reconstruct the whole subsidence field in mining areas.

The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service

This study is focused on wide-area deformation monitoring initiatives based on the differential interferometric SAR technique (DInSAR). In particular, it addresses the use of advanced DInSAR (A-DInSAR) techniques, which are based on large sets of synthetic aperture radar (SAR) and Copernicus Sentinel-1 images. Such techniques have undergone a dramatic development in the last twenty years: they are now capable to process big sets of SAR images and can be exploited to realize a wide-area A-DInSAR monitoring. The study describes several initiatives to establish wide-area ground motion services (GMS), both at county- and region-level. In the second part of the study, some of the key technical aspects related to wide-area A-DInSAR monitoring are discussed. Finally, the last part of the study is devoted to the European ground motion service (EGMS), which is part of the Copernicus land monitoring service. It represents the most important wide-area A-DInSAR deformation monitoring system ever developed. The study describes its main characteristics and its main products. The end of the production of the first EGMS baseline product is foreseen for the last quarter of 2021.

Effect of digital elevation models on monitoring slope displacements in open-pit mine by differential interferometry synthetic aperture radar

Abstract Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes. Differential interferometric synthetic aperture radar (DInSAR), mounted on an artificial satellite, has the potential to be a cost-effective method for monitoring surface displacements over extensive areas, such as open-pit mines. DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model (DEM). However, since the topography of the ground surface in open-pit mines changes largely due to excavations, measurement errors can occur due to insufficient information on the elevation of mining areas. In this paper, effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry. In addition, validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system (GPS) monitoring conducted for three years at the same limestone quarry. It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters. Comparing the monitoring results of DInSAR and GPS, the root mean square error (RMSE) of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM, considering the excavation processes, is used. It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.

Mining Subsidence Prediction by Combining Support Vector Machine Regression and Interferometric Synthetic Aperture Radar Data

Mining subsidence is time-dependent and highly nonlinear, especially in the Loess Plateau region in Northwestern China. As a consequence, and mainly in building agglomerations, the structures can be damaged severely during or after underground extraction, with risks to human life. In this paper, we propose an approach based on a combination of a differential interferometric synthetic aperture radar (DInSAR) technique and a support vector machine (SVM) regression algorithm optimized by grid search (GS-SVR) to predict mining subsidence in a timely and cost-efficient manner. We consider five Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR) images encompassing the Dafosi coal mine area in Binxian and Changwu counties, Shaanxi Province. The results show that the subsidence predicted by the proposed InSAR and GS-SVR approach is consistent with the Global Positioning System (GPS) measurements. The maximum absolute errors are less than 3.1 cm and the maximum relative errors are less than 14%. The proposed approach combining DInSAR with GS-SVR technology can predict mining subsidence on the Loess Plateau of China with a high level of accuracy. This research may also help to provide disaster warnings.

Modeling-Assisted InSAR Phase-Unwrapping Method for Mapping Mine Subsidence

Compared with traditional measurement technologies, synthetic aperture radar interferometry (InSAR) has unique advantages in monitoring ground subsidence due to underground mining. However, when the subsidence gradient of the subsidence trough exceeds the maximum measurable gradient of InSAR technology, the interference fringes will be too dense, causing phase aliasing. As a result, it is impossible to obtain correct phase-unwrapping result. The main objectives of this letter are two folded. First is to develop an unwrapping strategy to deal with the unwrapping problem caused by large subsidence gradient at the mine subsidence trough. The main idea of this strategy is to estimate most of the subsidence phase by multiple model inversions based on iterative approach. Then, the model phases from multiple models are combined with the final unwrapped residual phase. Another objective of this letter is to evaluate the feasibility of the three common deformation models, i.e., Mogi, probability integral method (PIM), and Okada, in solving the phase-unwrapping problem. Their advantages and disadvantages are outlined. Both the simulated data and real data are used for this experiment. The result shows that the problem of large subsidence gradient in the differential interferometric synthetic aperture radar (DInSAR) results can be solved by multiple model inversion. Among the three models, the use of Okada model seems to provide slightly more accurate result for solving the large-scale subsidence in the mining area than the other two models with the proposed strategy.

Assessment of the Sentinel-1 based ground motion data feasibility for large scale landslide monitoring

In this paper, a systematic procedure to assess the feasibility of Advanced Differential Interferometric SAR (A-DInSAR) technique for landslide monitoring using SAR images acquired by Sentinel-1 sensors is presented. The methodology is named “Assessment of the advanced differentiaL interferometric synthetic aperture radar technique Feasibility for large scale lAndslide monitoring – ALFA” and it is structured in two main phases, which includes pre-processing and post-processing elaborations. The methodology was developed and tested in the Alpine sector of the Piedmont region in Italy, which represents a landslide prone area. In particular, ALFA represents a methodology based on previous algorithms available in the literature to assess the a-prior feasibility assessment and post-processing analysis of A-DInSAR data for landslide, which introduces three novel aspects such as (1) a systematic scheme suitable within regional practices; (2) the use of Sentinel-1 data and the development of (3) an index to take into account of the kind of distribution of the measuring points along the landslide. The approach was applied over an area extended about 5300 km2 affected by 5703 landslides mapped in the database of the Piedmont Region (Landslides information system in Piedmont—SIFRAP). Sentinel-1 images covering the period 2014–2018 were analysed. The results show the potential of the Sentinel-1 data for large-scale landslide monitoring. The developed methodology presents reliable tools that could be useful as feasibility for the use of Sentinel-1 data for landslide monitoring at regional and national scale.

The Impact of SAR Parameter Errors on the Ionospheric Correction Based on the Range-Doppler Model and the Split-Spectrum Method

Interferometric synthetic aperture radar (InSAR) products may be significantly distorted by microwave signals traveling through the ionosphere, especially with long wavelengths. The split-spectrum method (SSM) is used to separate the ionospheric and the nondispersive phase terms with lower and higher spectral sub-band interferogram images. However, the ionospheric path delay phase is very delicate to the synthetic aperture radar (SAR) parameters including orbit vectors, slant range, and target height. In this paper, we get the impact of SAR parameter errors on the ionospheric phase by two steps. The first step is getting the derivates of geolocation with reference to SAR parameters based on the range-Doppler (RD) imaging model and the second step is calculating the derivates of the ionospheric phase delay with respect to geometric positioning. Through the numerical simulation, we demonstrate that the deviation of ionospheric phase has a linear relationship with SAR parameter errors. The experimental results show that the estimation of SAR parameters should be accurate enough since the parameter errors significantly affect the performance of ionospheric correction. The root mean square error (RMSE) between the corrected differential interferometric SAR (DInSAR) phase with SAR parameter errors and the corrected DInSAR phase without parameter errors varies from centimeter to decimeter level with the L-band data acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) over Antofagasta, Chile. Furthermore, the effectiveness of SSM can be improved when SAR parameters are accurately estimated.

Long Term Interferometric Temporal Coherence and DInSAR Phase in Northern Peatlands

Peatlands of northern temperate and cold climates are significant pools of stored carbon. Understanding seasonal dynamics of peatland surface height and volume, often referred to as mire breathing or oscillation, is the key to improve spatial models of material flow and gas exchange. The monitoring of this type of dynamics over large areas is only feasible by remote sensing instruments. The objective of this study is to examine the applicability of Sentinel-1 synthetic aperture radar interferometry (InSAR) to characterize seasonal dynamics of peatland surface height and water table (WT) over open raised bog areas in Endla mire complex in central Estonia, characteristic for northern temperate bogs. Our results show that InSAR temporal coherence, sufficient for differential InSAR (DInSAR), is preserved in the open bog over more than six months of temporal baseline. Moreover, the coherence which is lost in a dry summer, make a recovery in autumn correlate with WT dynamics. The relationship between the coherence from a single master image and the corresponding WT difference is described by the second degree polynomial regression model (Root Mean Squared Error RMSE = 0.041 for coherence magnitude). It is also demonstrated that DInSAR phase is connected to bog surface dynamics and reveals differences between bogs and for ecotopes within a bog. These findings suggest that InSAR long term temporal coherence could be used to describe seasonal bog WT dynamics and differentiate between mire types and ecotopes within a bog. Moreover, DInSAR analysis has the potential to characterize seasonal mire surface oscillation which may be important for assessing the capacity of water storage or restoration success in northern temperate bogs.

The 29 March 2017 Yuzhno-Ozernovskoe Kamchatka Earthquake: Fault Activity in An Extension of the East Kamchatka Fault Zone as Constrained by InSAR Observations

ABSTRACTRecent earthquakes off the northeastern Kamchatka coast reveal that this region is seismically active, although details of the locations and complexity of the fault system are lacking. The northern part of Kamchatka has poor coverage by permanent seismic stations and ground geodetic instruments. Here, we exploit the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique to characterize the fault geometry and kinematics associated with the 29 March 2017 Mw 6.6 Yuzhno-Ozernovskoe earthquake. The aim is to contribute to identifying the active fault branches and to better understanding the complex tectonic regime in this region using the DInSAR technique, which has never before been applied to the analysis of coseismic offsets in Kamchatka.We produced coseismic deformation maps using Advanced Land Observation Satellite-2 ascending and descending and Sentinel-1A descending Synthetic Aperture Radar (SAR) scenes and detected a predominant uplift up to 20 cm and a westward motion of approximately 7 cm near the shoreline. We jointly inverted the three geodetic datasets using elastic half-space fault modeling to retrieve source geometry and fault kinematics. The best-fit solution for the nonlinear inversion suggests a north–west-dipping oblique reverse fault with right-lateral rupture.The model fault geometry is not only generally consistent with the seismic data but also reveals that a hitherto unknown fault was ruptured. The identified fault structure is interpreted as the northern extension of the east Kamchatka fault zone, implying that the region is more complex than previously thought. Important implications arise for the presence of unknown faults at the edges of subduction zones that can generate earthquakes with magnitudes greater than Mw 6.

Long-term ground multi-level deformation fusion and analysis based on a combination of deformation prior fusion model and OTD-InSAR for longwall mining activity

Abstract Caused by the underground longwall mining activities, ground deformation, which includes sudden large-level deformation, slow small-level deformation and the middle-level deformation between them, can lead to serious construction damage and ecological environment degradation. In this paper, we propose a new fusion model that is able to completely retrieve multi-level deformation with measured radar line-of-sight (LOS) deformation from offset-tracking (OT) and differential interferometric synthetic aperture radar (DInSAR) technique (referred to as OTD-InSAR). The results from OTD-InSAR show that small-level deformation on the edge of subsidence basin and large-level deformation in the central portion of subsidence basin are measured with high accuracy. The multi-level deformation fusion model considers the geographic information and SAR data information simultaneously to fuse large-level and small-level deformation and use inverse distance weighting method (IDW) to estimate the middle-level deformation. Due to the insufficient measured data in the actual situation, we present the prediction model to forecast the long period deformation evolution of full workface based on the exponent Knothe model and the fusion results. The 52,303 workface in Daliuta coal mining area in China was selected to verify the effectiveness of the fusion model and prediction model. The comparison between the fusion results and the in-situ measured data shows that the root mean square error (RMSE) is less than 0.23 m. Results of deformation prediction model are found to be very close to fusion results and the RMSE is less than 0.027 m. This research work has brought about a comprehensive analysis of the deformation evolution of the full workface with high precision from the beginning to the end of coal mining for about 18 months. As a result, the monitoring results can support the requirements of mining deformation monitoring in the management of surface disaster.

Identification of the ground movements caused by mining-induced seismicity with the satellite interferometry

Abstract. The assessment of the impact of mining-induced seismicity on the natural environment and infrastructure is often limited to the analysis of terrain surface vibrations. However, similar seismic phenomena, like earthquakes, may also imply dislocations and deformations of the rock mass. Such ground movements may occur in areas which are not directly under the influence of the mining. The study of the displacement field caused by mining-induced seismicity is usually carried out with the use of geodetic methods. Classical geodetic measurements provide discrete information about observed ground movements. As a result, they generally do not provide spatially and temporally relevant estimates of the total range and values of ground movements for specific periods of interest. Moreover, mining-induced seismicity causes a severe threat to buildings. That is why, regarding the complexity of the mechanism of occurrence of mining-induced seismicity and their impact on ground movements, this problem remains a substantial research issue. The presented research aimed to analyse the ground movements caused by mining-induced seismicity. The ground displacements were established based on data from Sentinel-1 satellites applying differential interferometric synthetic aperture radar (DInSAR). The results of the investigation in the copper mining area of the Lower Silesia region of Poland revealed that the observed subsidence caused by mining-induced seismicity usually has a shape of a regular ellipse. The radius of these ground movements does not exceed approximately 2–3 km from the mining-induced tremor's epicenter, and the total subsidence reaches ca. 10–20 cm. More than 50 % of the total subsidence is observed on the surface within a few days after the mining tremor occurrence. Furthermore, the deformations of the surface occur when the energy of mining-induced tremor reaches values of the order of 105 J or higher. The presented research can contribute to better identification and evaluation of the mechanism of the rock mass deformation process caused by mining-induced seismicity. In addition, the use of satellite radar interferometry improves the quality of monitoring of these dynamic phenomena significantly. The data retrieved using this method allow for quasi-continuous monitoring of the local subsidence bowls caused by mining-induced seismicity.

Understanding the dynamic behaviour for the Madrid aquifer (Spain): insights from the integration of A-DInSAR and 3-D groundwater flow and geomechanical models

Abstract. Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques and 3-D groundwater flow and geomechanical models are integrated to improve our knowledge about the Tertiary detritic aquifer of Madrid (TDAM). In particular, the attention is focused on the Manzanares-Jarama well field, located to the northwest of Madrid, which experienced five cycles of extensive groundwater withdrawal followed by natural recovery, to cope with the droughts occurred in summer 1995, 1999, 2002, 2006, and 2009. Piezometric records and A-DInSAR data acquired by ERS-1/2 and ENVISAT satellites during the periods 1992–2000 and 2002–2010, respectively, have been used to calibrate the groundwater flow and the geomechanical models. A time-lag of about one month between the hydraulic head changes and the displacements of the land surface has been detected by a joint wavelet analysis of A-DInSAR and piezometer head time series. Overall, the results show the effectiveness of the proposed integrated approach composed of A-DInSAR and 3-D geomechanical model to characterize the aquifer-system response during and after the groundwater withdrawal.

Could Vegetation Index be Derive from Synthetic Aperture Radar? \u2013 The Linear Relationship between Interferometric Coherence and NDVI

Due to many factors in the physical properties of the ground surface, the corresponding interferometric coherence values change dynamically over time. Among these factors, the roles of the vegetation and its temporal variation have not yet been revealed so far. In this paper, synthetic aperture radar (Sentinel-1) data and optical remote sensing (Landsat TM) images over four whole seasons are employed to reveal the relationship between the interferometric coherence and the normalized difference vegetation index (NDVI) at five sites that have ground deformation due to mining in Henan province, China. The result showed: (1) As for the village area with few vegetation cover, the related coherence values are significantly higher than that in the farm land area with high densities of vegetation in the spring and summer, which indicates that the subsidence by mining in few vegetation cover area is easier to be monitored; (2) Linear regression coefficients ({{bf{R}}}^{{bf{2}}}) between the interfereometric coherence values and the NDVI values is 0.62, which indicate the interferometric coherence values and the NDVI values change reversely in both farm land and village areas over the year. It suggests months between November and March with lower NDVI value are more suitable for deformation detecting. Therefore, the interfereometric coherence values can be used to detect the density of vegetation, while NDVI values can be reference for elucidating when the traditional differential interferometric synthetic aperture radar (DInSAR) could be effectively used.

Multi-scale site evaluation of a relict active layer detachment in a High Arctic landscape

Investigations into the susceptibility of permafrost landscapes response to thermokarst can be performed using various approaches, depending on the scale of investigation. In many cases, point-based field measurements are extrapolated to larger scales and vice versa. The integration of scales often requires some form of ground control in addition to remote sensing surveys, which are at times exclusively conducted. As upscaling from discrete field measurements can provide spatial coverage and landscape-scale significance, downscaling from remote sensing can offer insight into processes and serve as calibration or verification. Here we present a multiple-scale evaluation of an area initially interpreted as a relict active layer detachment slide (before 1950) on Melville Island in the High Arctic, where differential interferometric synthetic aperture radar (DInSAR) showed subsidence between 2013 and 2015. Ground-based, cryostratigraphy measurements were combined with ground-penetrating radar (GPR) to investigate permafrost ice-content. The results indicate greater subsidence within the relict active layer detachment as detected by DInSAR. GPR surveys and permafrost coring indicated the presence of an ice-rich or massive ice layer near the base of the active layer in this area. In addition, cryostratigraphic evidences of thaw unconformity and of massive ice depth helped validate the interpretations of the geomorphology in the active layer detachment. This combination of methods indicated a localized and inherited landform-subsidence association, which brought further insight into the interpretation of DInSAR subsidence data. The framework presented in this study demonstrates the importance of site-specific investigations of thermokarst signal in order to understand the processes behind the remote sensing results.