TerraSAR-X Research Articles

Evaluation of polarimetric capabilities of dual polarized Sentinel-1 and TerraSAR-X data to improve the PSInSAR algorithm using amplitude dispersion index optimization

Polarimetric data is an additional source of information in PSI technique to improve its performance in land subsidence estimation. The combination of polarimetric data and radar interferometry can lead to an increase in coherence and the number of PS pixels. In this paper, we evaluated and compared the dual polarized Sentinel-1A (S1A) and TerraSAR-X (TSX) data to improve the PSInSAR algorithm. The improvement of this research is based on minimizing Amplitude Dispersion Index (ADI) by finding the optimum scattering mechanism to increase the number of PSC and PS pixels. The proposed method was tested using a dataset of 40 dual-pol SAR data (VV/VH) acquired by S1A and 20 dual-pol SAR data (HH/VV) acquired by TSX. The results revealed that using the TSX data, the number of PS pixels increased about 3 times in ESPO method than using the conventional channels, e.g., HH, and VV. This increase in S1A data was about 1.7 times in ESPO method. In addition, we investigated the efficiency of the three polarimetric optimization methods i.e. ESPO, BGSM, and Best for the dual polarized S1A and TSX data. Results showed that the PS density increased about 1.9 times in BGSM and about 1.5 times in Best method in TSX data. However, in S1A data, PS density increased about 1.1 times in BGSM. The Best method was not successful in increasing the PS density using the S1A data. Also, the effectiveness of the method was evaluated in urban and non-urban regions. The experimental results showed that the method was successful in significantly increasing the number of final PS pixels in both regions.

A Novel Vessel Velocity Estimation Method Using Dual-Platform TerraSAR-X and TanDEM-X Full Polarimetric SAR Data in Pursuit Monostatic Mode

In this paper, we demonstrate that the spaceborne dual-platform TerraSAR-X (TSX) and TanDEM-X (TDX) pursuit monostatic mode full polarimetric (full-pol) synthetic aperture radar (SAR) data with a time lag can be used to monitor maritime traffic. For single polarization (single-pol) SAR data, the performance of vessel velocity estimation is mainly determined by 2-D cross correlation of SAR intensity data. As the sea clutter is changing dynamically during the TSX/TDX data acquisition, the correlation between two dual-platform images decreases significantly. We may get unstable or incorrect estimations of vessel velocity, especially under a higher wind condition. For solving this problem, we propose an object-oriented polarimetric likelihood ratio test (PolLRT) method based on the complex Wishart distribution. The proposed method makes PolLRT statistics of the detected target pixels for eliminating the effect of varied sea clutter. Two pairs of full-pol SAR data sets covering the Strait of Gibraltar acquired by dual-platform TSX/TDX in pursuit monostatic mode with a time lag of approximately 10 s are selected for the experiments. The experimental results demonstrate that the proposed PolLRT method has a better performance than that of the classical normalized cross correlation (NCC) method with VV polarization SAR data and the mutual information (MI) method with full-pol SAR data. Specifically, under the lower wind condition, the correct estimation rate of the NCC, the MI, and the proposed PolLRT methods are 85.7%, 57.1%, and 100%, respectively; under the relatively higher wind condition, the correct estimation rate of the above three methods are 48.8%, 23.2%, and 90.1%, respectively.

Retrieval of Internal Solitary Wave Amplitude in Shallow Water by Tandem Spaceborne SAR

The accurate estimation of the upper layer thickness in a two-layer ocean is a crucial step in the retrieval of internal solitary wave (ISW) amplitude from synthetic aperture radar (SAR) data. In this paper, we present a method to derive the upper layer thickness and the consequent ISW amplitude by combining two consecutive SAR images with the extended Korteweg-de Vries (eKdV) equation. An ISW case observed twice by the Chinese C-band SAR GaoFen-3 (GF-3) and the German X-band SAR TerraSAR-X (TS-X) with a temporal interval of approximately 11 min in shallow water to the southeast of Hainan Island in the northwestern South China Sea was used to demonstrate the applicability of the method. Using the in situ measurements of temperature and salinity near the observed ISW, the proposed method yielded an ISW amplitude of −4.52 m, in close proximity to −5.66 ± 1.24 m derived by applying the classic Korteweg–de Vries (KdV) equation based on the continuously stratified theory. Moreover, the climatological dataset of the World Ocean Atlas 2013 (WOA13) was also used with the proposed method in the Hainan case, and the results showed that the method can still provide a reasonable estimate of ISW amplitude in shallow water even when in situ oceanic stratification measurements are absent. The application of our method to derive the ISW amplitude from consecutive SAR images seems highly promising with the increasing emergence of tandem satellites in orbits.

Remotely sensing large- and small-scale ground subsidence: A case study of the Guangdong–Hong Kong–Macao Greater Bay Area of China

As the world's largest city cluster, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is vulnerable to significant subsidence. The widely distributed sediments and rapid urbanization in the GBA result in the concurrence of large- and small-scale subsidence. Mono-sensor synthetic aperture radar (SAR) images usually suffer from the limitation of either low resolution or small coverage, and thus, are not applicable to completely monitoring the GBA. In this study, we used Sentinel-1 (S1), COSMO-SkyMed (CSK) and TerraSAR-X (TSX) images jointly to reveal multi-scale subsidence of the GBA. The overall subsidence ranged from 0 to 112.3 mm/yr derived from the 2015–2017 S1 images. Three regional subsidence bowls (Zhuhai–Zhongshan, Jiangmen, and Guangzhou–Zhongshan) formed in the western alluvial plain. The high correlation between regional subsidence and Quaternary sediments confirms that sediment consolidation is the main cause of subsidence. The land use and numerical modeling results suggest that groundwater extraction and artificial loading are the triggering factors. Two representative local subsidence cases were analyzed using high-resolution images: reclamation settlement at the Hong Kong International Airport (HKIA) and sinkhole subsidence due to the excavation of the Shenzhen Wenbo skyscraper foundation pit. The validation at the HKIA showed that the measurements from the CSK and S1 data both agreed well with the leveling data. However, CSK outperformed S1 in the sense that it increased the point density by a factor of 5, improved the height precision by a factor of 4, and showed fewer false alarms. CSK is therefore more applicable to monitoring the local subsidence of key infrastructures. The cross-heading tracks of TSX and CSK images detected precursory subsidence before the sinkhole collapse from two sides, indicating that the cross-heading tracks benefit the comprehensive monitoring of local subsidence in high-rise and high-density built environments. In summary, the synergistic use of multi-sensor SAR images demonstrates the practicability of the operational surveillance of multi-scale subsidence from regional surveying to the fine monitoring of local areas in the GBA.

Relating X-band SAR Backscattering to Leaf Area Index of Rice in Different Phenological Phases

The objective of this study is to provide complete information on the dynamic relationship between X-band (3.11 cm) backscattering intensity (σ°) and rice crop’s leaf area index (LAI) at all growth phases. Though the relationship between X-band σ° and LAI has been previously explored, details on the relationship at the reproductive phase remain unstudied. LAI at the reproductive phase is important particularly at the heading stage where LAI reaches its maximum as it is closely related to grain yield, and at flowering stage where the total leaf area affects the amount of photosynthates. Therefore, this study examined the relationship of increasing LAI (vegetative to reproductive phase) and decreasing LAI (ripening phase) with TerraSAR-X (TSX) ScanSAR (3.11 cm) σ° at HH polarisation and 45° incidence angle. The results showed a statistically significant (R2 = 0.51, p value < 0.001) non-linear relationship of LAI with σ° at the vegetative to reproductive phase while no significant linear relationship was found at the ripening phase. This study completes the response curve of X-band σ° to LAI by filling in the information on the reproductive phase which more accurately characterises the dynamic relationship between the rice crop’s LAI and X-band’s σ°. This contributes to improved knowledge on the use of X-band data for estimating LAI for the whole crop cycle which is essential for the modelling of crop growth and estimation of yield.

Characterization of pre- and post-failure displacements of the Huangnibazi landslide in Li County with multi-source satellite observations

The Huangnibazi landslide in Li County of southwest China, began to slide rapidly since 8 August 2017. It received little attention before the failure event. The fast motion of the slope posed great threats to the safety of nearby villages and the national highway G317 at the foot of the mountain. In this study, Synthetic Aperture Radar (SAR) datasets collected by C-band Sentinel-1 and X-band TerraSAR-X (TSX), as well as optical images acquired by Sentinel-2 Multi-Spectral Instrument (MSI) over the landslide site were analyzed to characterize the evolution of the slope before and after the failure event. Firstly, the surface change of the sliding area was qualitatively evaluated using the Sentinel-2 true-color images and pseudo-colored TerraSAR-X amplitude images. Next, the slow movement of the slope before the failure event was detected by interferometry using both TerraSAR-X and Sentinel-1 data stacks. The maximum displacement rate estimated was larger than −45 mm/year along the radar line of sight (LOS) direction. Finally, the large post-failure displacements of the landslide were successfully retrieved with meter-level accuracy from TerraSAR-X observations using adaptive amplitude offset tracking method. The maximum displacement decreased from about 30 m in 11 days in August 2017 to 1–2 m in 22 days in January 2018 in both LOS and azimuth directions. According to the recent measurements of surface displacement, the landslide body is becoming stabilized gradually, which suggests that the risk of catastrophic collapse of the slope has been largely reduced.

Using TSX/TDX Pursuit Monostatic SAR Stacks for PS-InSAR Analysis in Urban Areas

Persistent Scatterer Interferometry (PS-InSAR) has become an indispensable tool for monitoring surface motion in urban environments. The interferometric configuration of PS-InSAR tends to mix topographic and deformation components in differential interferometric observations. When the upcoming constellation missions such as, e.g., TanDEM-L or TWIN-L provide new standard operating modes, bi-static stacks for deformation monitoring will be more commonly available in the near future. In this paper, we present an analysis of the applicability of such data sets for urban monitoring, using a stack of pursuit monostatic data obtained during the scientific testing phase of the TanDEM-X (TDX) mission. These stacks are characterized by extremely short temporal baselines between the TerraSAR-X (TSX) and TanDEM-X acquisitions at the same interval. We evaluate the advantages of this acquisition mode for urban deformation monitoring with several of the available acquisition pairs. Our proposed method exploits the special properties of this data using a modified processing chain based on the standard PS-InSAR deformation monitoring procedure. We test our approach with a TSX/TDX mono-static pursuit stack over Guangzhou, using both the proposed method and the standard deformation monitoring procedure, and compare the two results. The performance of topographic and deformation estimation is improved by using the proposed processing method, especially regarding high-rise buildings, given the quantitative statistic on temporal coherence, detectable numbers, as well as the PS point density of persistent scatters points, among which the persistent scatter numbers increased by 107.2% and the detectable height span increased by 78% over the standard processing results.

Integration of SAR Data Into Monitoring of the 2014–2015 Holuhraun Eruption, Iceland: Contribution of the Icelandic Volcanoes Supersite and the FutureVolc Projects

We report how data from satellite and aerial synthetic aperture radar (SAR) observations were integrated into monitoring of the 2014-2015 Holuhraun eruption in the Barðarbunga volcanic system, the largest effusive eruption in Iceland since the 1783-84 Laki eruption. A lava field formed in one of the most remote areas in Iceland, after the propagation of a ~50 km-long dyke beneath the Vatnajokull ice cap, where the Barðarbunga caldera is located. Due to the 6 month duration of the eruption, mainly in wintertime, daily monitoring was particularly challenging. During the eruption, the European volcanological project FutureVolc was ongoing, allowing collaboration of many European experts on volcano monitoring activities. Icelandic volcanoes are also a permanent Supersite within the Geohazard Supersites and Natural Laboratories (GSNL) initiative, with support from the Committee on Earth Observation Satellite (CEOS) in the form of a large collection of SAR images. SAR data were acquired by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) satellites and complemented by aerial SAR images. The large set of SAR satellite data significantly contributed to the daily monitoring during the unrest at Barðarbunga caldera, the Holuhraun eruption and the year following the eruption. Detection of surface changes using both SAR amplitude and phase information was conducted throughout the whole duration of the volcano-tectonic event, and in the following months, to quantify and track the evolution of volcanic processes at Holuhraun and geothermal activity at Barðarbunga volcano. Combination of SAR data with other data sets, e.g. satellite optical images and geodetic Global Positioning System (GPS) measurements, was essential for the evaluation of the volcanic hazard in the whole area. International collaboration within the Futurevolc project formed the basis for successful analyses and interpretation of the large SAR data set. Information was provided at Scientific Advisory Board meetings of the Icelandic Civil Protection and used in decision-making, as well as for supporting field-deployment and air-based surveys.

On the analysis of a time series of X–band TerraSAR–X SAR imagery over oil seepages

ABSTRACTA large time series of 42 dual–polarimetric co–polarized TerraSAR-X (TSX) StripMap Synthetic Aperture Radar (SAR) measurements are exploited to monitor a well-known oil seep area, i.e., the Taylor Energy site in the Gulf of Mexico. A comprehensive scattering analysis is undertaken to assess the impact of SAR imaging parameters (polarization, angle of incidence – AOI, noise floor) and environmental conditions (wind speed – WS, oil properties) on single-polarization SAR–based sea oil seep observation. The main goal of this study is to evaluate the reliability of the scattering–based information derived from the time series of TSX SAR imagery. A two-scale backscattering model is considered to give a physical framework that supports a better understanding of the effects of the above–mentioned factors.Experimental results showed that the high TSX noise floor significantly limits a reliable interpretation of the slick–free sea surface and oil seep backscattering at AOIs larger than 34 and 26, respectively, since they are contaminated by noise. Hence, it is shown that, at larger AOIs, the joint contribution of noisy SAR measurements and low oil backscattering does not result in a larger oil/sea separability. The latter is not remarkably influenced by polarization and WS, under low–to–moderate conditions. Experiments also demonstrate that, when reliable SAR measurements are available, sea oil seep backscattering is affected by the oil’s damping properties more than its concentration in the water column. The time variability of the polluted area is also estimated using the time series of TSX imagery and the obtained results agree with independent analysis undertaken on the same test site.

Monitoring active motion of the Guobu landslide near the Laxiwa Hydropower Station in China by time-series point-like targets offset tracking

Since 2009, the Guobu landslide has been very active, posing a safety threat to the Laxiwa Hydropower Station, located only several hundred meters downstream along the upper Yellow River in China. To investigate the current state of this landslide, we analyzed two stacks of X-band TerraSAR-X (TSX) High-resolution Spotlight (HS) mode images acquired from September 2015 to April 2017 in descending orbits with different look angles. A new time-series point-like target offset tracking (TS-PTOT) method is proposed to retrieve time-series surface displacements at point-like targets (PTs) from SAR image pairs properly combined with large temporal baselines and small spatial baselines. According to an evaluation of the standard deviation of time-series displacements at stable points, the TS-PTOT method increased the measurement precision of offset tracking by about 25% over the results using a single master. Our TSX-HS TS-PTOT results manifested a spatial pattern and magnitude of displacements highly similar to DInSAR result produced with an ALOS-2 PALSAR-2 image pair. The maximum displacement rate at the upper part of the slope during the study period was around 80 cm/yr in the line-of-sight (LOS) direction, which is much lower than the displacement rate measured in 2010. Furthermore, three-dimensional (3D) displacements at those identified homologous PTs were estimated by combining two-dimensional (2D) displacements measured by TS-PTOT from the two SAR data stacks. The 3D deformation pattern of the Guobu landslide properly verified its toppling-sliding deformation mechanism.

TANDEM-X MISSION STATUS, PRODUCTS AND PERSPECTIVES

Abstract. TanDEM-X is an innovative single-pass interferometric radar mission, which is comprised of two formation flying satellites. The TerraSAR-X (TSX) satellite was launched on June 15th 2007, and its almost identically constructed twin satellite TanDEM-X (TDX) was launched on 21st of June 2010. Together they supply high-quality radar data in order to serve two main mission goals: Scientific observation of the Earth and provision of remote sensing data for the commercial market (TerraSAR-X mission), and the generation of a global digital elevation model (DEM) of the Earth’s surface (TanDEM-X mission). Between December 2010 and early 2015, radar data of all land surfaces has been acquired and as of September 2016 the final TanDEM-X DEM dataset has been available. This paper provides a final quality assessment of the TanDEM-X global DEM products with respect to the relative and absolute height accuracy and data coverage both at the global and geocell level. In addition, an overview on current mission status is given and new DEM products, which are currently in the scope of the TanDEM-X mission, are described.

Radargrammetric approaches to the flat relief of the amazon coast using COSMO-SkyMed and TerraSAR-X datasets

The Amazonian coast consists of extensive flood plains and plateaus characterized by a high discharge of water and sediment from the Amazon River. This wide landscape occurs under a tropical climate with heavy rains and high cloud cover, making it unsuitable for conventional mapping based on optical images. Additionally, the flat relief and vegetation structure of the Brazilian Amazon coast define an incoherent to partially coherent behavior for the microwave signal, rendering radargrammetric models more suitable for the three-dimensional mapping of its surface. This study aimed to assess the digital surface models (DSMs) provided by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) Stripmap datasets throughout the radargrammetric models from SARscape and Toutin. The DSMs were generated from SAR (synthetic aperture radar) data with an acquisition geometry that addressed the need for a compromise between the intersection angles and low temporal decorrelation. The radargrammetric SARscape and Toutin’s models were developed from different amounts of stereo ground control points (SGCP). The generated DSMs were evaluated considering a set of 40 independent checkpoints (ICP) measured by GNSS in the field, in their entirety and disaggregated by coastal environment. The vertical accuracy was based on the estimation of the discrepancies, bias and precision (standard deviation and root mean square error – RMSE), and the Taylor and Target diagrams were used for a more comprehensive comparison. In the vertical accuracy analysis using all ICPs measured in situ, the DSM obtained by the SARscape’s model from the CSK SAR data resulted in the lowest RMSE (4.34 m) and mean discrepancy (0.05 m), but Toutin’s model had the lowest standard deviation (2.58 m) of the discrepancies. The Taylor and Target diagrams showed fluctuations in accuracy that alternated the DSMs generated from the two types of SAR data, indicating that TSX produced more stable models and CSK produced better vertical accuracy. The Amazon Coastal Plateau and Fluvial Marine Terrace environments defined three-dimensional representations with lower RMSEs (better than 7.8 and 8.9 m, respectively), regardless of the type of SAR data or the radargrammetric model used. The worst performance, which was for the Fluvial Marine Plain, was influenced by the specific characteristics of this coastal environment, such as the structure of the mangrove vegetation and the shoreline. In general, the high resolution and good ability to revisit the SAR data used, together with the radargrammetric models, allowed for the accurate mapping of the flat relief of the Amazon coastal environments, providing detailed spatial information that can be acquired in severe rainfall conditions in a region of intense morphological dynamics.

Method Combining Probability Integration Model and a Small Baseline Subset for Time Series Monitoring of Mining Subsidence

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence.

Deformation due to geothermal exploitation at Reykjanes, Iceland

Ground deformation in utilized geothermal areas is often attributed either to pressure decrease or temperature decrease in the geothermal reservoir. A new geothermal power plant at Reykjanes began operation in May 2006 and local deformation caused by geothermal utilization was observed shortly thereafter. We use images acquired by the Envisat and TerraSAR-X (TSX) satellites, between 2003 and 2016, as well as available GNSS data, to derive constraints on the cumulative ground displacement at the Reykjanes geothermal area, Iceland, and compare these results to production data acquired from observation wells in this region. We employ interferometric analysis of synthetic aperture satellite radar images (InSAR), using a combined persistent scatterer and small baseline approach, on both ascending and descending Envisat and TSX satellite tracks covering the 2003–2016 period. Time series of range change along line-of-sight (LOS) from the ground to the satellite show the characteristics of on-going ground deflation in the vicinity of the Reykjanes power plant. In the 2005–2008 period, the main area of deformation was 4 km long by 2.5 km wide, aligned along the Reykjanes fissure swarm, but in the period 2009–2016 it is more circular in shape and ~2 km wide. LOS displacement rates have remained relatively steady in time, although slightly faster in the 2005–2008 period than the 2009–2016 period. The average LOS velocities from ascending and descending tracks are decomposed into estimates of near-vertical and near-east displacements. The inferred maximum subsidence since the start of production is ~260 mm. Horizontal displacements show contraction towards the center of deflation of up to ~140 mm. Geodetic modeling is undertaken using sources of simple geometry within an elastic halfspace to determine the optimal sources for the observed contraction throughout 2005–2016. For the earlier period modeled utilizing ENVISAT interferograms (16 June 2005–16 August 2008) the optimal source is a Yang model with a strike of 58° and a source depth of 2.2 km. The calculated volume change associated with the observed contraction is −2.3 × 106 m3. For the latter period, utilizing TSX interferograms (24 September 2009–17 August 2016), the preferred source is a Mogi-type model at a depth of 1.2 km and the modeled volume change is −1 × 106 m3.

TerraSAR-X Time Series Fill a Gap in Spaceborne Snowmelt Monitoring of Small Arctic Catchments—A Case Study on Qikiqtaruk (Herschel Island), Canada

The timing of snowmelt is an important turning point in the seasonal cycle of small Arctic catchments. The TerraSAR-X (TSX) satellite mission is a synthetic aperture radar system (SAR) with high potential to measure the high spatiotemporal variability of snow cover extent (SCE) and fractional snow cover (FSC) on the small catchment scale. We investigate the performance of multi-polarized and multi-pass TSX X-Band SAR data in monitoring SCE and FSC in small Arctic tundra catchments of Qikiqtaruk (Herschel Island) off the Yukon Coast in the Western Canadian Arctic. We applied a threshold based segmentation on ratio images between TSX images with wet snow and a dry snow reference, and tested the performance of two different thresholds. We quantitatively compared TSX- and Landsat 8-derived SCE maps using confusion matrices and analyzed the spatiotemporal dynamics of snowmelt from 2015 to 2017 using TSX, Landsat 8 and in situ time lapse data. Our data showed that the quality of SCE maps from TSX X-Band data is strongly influenced by polarization and to a lesser degree by incidence angle. VH polarized TSX data performed best in deriving SCE when compared to Landsat 8. TSX derived SCE maps from VH polarization detected late lying snow patches that were not detected by Landsat 8. Results of a local assessment of TSX FSC against the in situ data showed that TSX FSC accurately captured the temporal dynamics of different snow melt regimes that were related to topographic characteristics of the studied catchments. Both in situ and TSX FSC showed a longer snowmelt period in a catchment with higher contributions of steep valleys and a shorter snowmelt period in a catchment with higher contributions of upland terrain. Landsat 8 had fundamental data gaps during the snowmelt period in all 3 years due to cloud cover. The results also revealed that by choosing a positive threshold of 1 dB, detection of ice layers due to diurnal temperature variations resulted in a more accurate estimation of snow cover than a negative threshold that detects wet snow alone. We find that TSX X-Band data in VH polarization performs at a comparable quality to Landsat 8 in deriving SCE maps when a positive threshold is used. We conclude that TSX data polarization can be used to accurately monitor snowmelt events at high temporal and spatial resolution, overcoming limitations of Landsat 8, which due to cloud related data gaps generally only indicated the onset and end of snowmelt.

Assessing Single-Polarization and Dual-Polarization TerraSAR-X Data for Surface Water Monitoring

Three synthetic aperture radar (SAR) data classification methodologies were used to assess the ability of single-polarization and dual-polarization TerraSAR-X (TSX) data to classify surface water, including open water, ice, and flooded vegetation. Multi-polarization SAR observations contain more information than single-polarization SAR, but the availability of multi-polarization data is much lower, which limits the temporal monitoring capabilities. The study area is a principally natural landscape centered on a seasonally flooding river, in which four TSX dual-co-polarized images were acquired between the months of April and June 2016. Previous studies have shown that single-polarization SAR is useful for analyzing surface water extent and change using grey-level thresholding. The H-Alpha–Wishart decomposition, adapted to dual-polarization data, and the Kennaugh Element Framework were used to classify areas of water and flooded vegetation. Although grey-level thresholding was able to identify areas of water and non-water, the percentage of seasonal change was limited, indicating an increase in water area from 8% to 10%, which is in disagreement with seasonal trends. The dual-polarization methods show a decrease in water over the season and indicate a decrease in flooded vegetation, which agrees with expected seasonal variations. When comparing the two dual-polarization methods, a clear benefit of the Kennaugh Elements Framework is the ability to classify change in the transition zones of ice to open water, open water to marsh, and flooded vegetation to land, using the differential Kennaugh technique. The H-Alpha–Wishart classifier was not able to classify ice, and misclassified fields and ice as water. Although single-polarization SAR was effective in classifying open water, the findings of this study confirm the advantages of dual-polarization observations, with the Kennaugh Element Framework being the best performing classification framework.

Landslide Monitoring Using Multi-Temporal SAR Interferometry with Advanced Persistent Scatterers Identification Methods and Super High-Spatial Resolution TerraSAR-X Images

Landslides are one of the most common and dangerous threats in the world that generate considerable damage and economic losses. An efficient landslide monitoring tool is the Differential Synthetic Aperture Radar Interferometry (DInSAR) or Persistent Scatter Interferometry (PSI). However, landslides are usually located in mountainous areas and the area of interest can be partially or even heavily vegetated. The inherent temporal decorrelation that dramatically reduces the number of Persistent Scatters (PSs) of the scene limits in practice the application of this technique. Thus, it is crucial to be able to detect as much PSs as possible that can be usually embedded in decorrelated areas. High resolution imagery combined with efficient pixel selection methods can make possible the application of DInSAR techniques in landslide monitoring. In this paper, different strategies to identify PS Candidates (PSCs) have been employed together with 32 super high-spatial resolution (SHR) TerraSAR-X (TSX) images, staring-spotlight mode, to monitor the Canillo landslide (Andorra). The results show that advanced PSI strategies (i.e., the temporal sub-look coherence (TSC) and temporal phase coherence (TPC) methods) are able to obtain much more valid PSs than the classical amplitude dispersion (DA) method. In addition, the TPC method presents the best performance among all three full-resolution strategies employed. The SHR TSX data allows for obtaining much higher densities of PSs compared with a lower-spatial resolution SAR data set (Sentinel-1A in this study). Thanks to the huge amount of valid PSs obtained by the TPC method with SHR TSX images, the complexity of the structure of the Canillo landslide has been highlighted and three different slide units have been identified. The results of this study indicate that the TPC approach together with SHR SAR images can be a powerful tool to characterize displacement rates and extension of complex landslides in challenging areas.

Where We Live—A Summary of the Achievements and Planned Evolution of the Global Urban Footprint

The TerraSAR-X (TSX) mission provides a distinguished collection of high resolution satellite images that shows great promise for a global monitoring of human settlements. Hence, the German Aerospace Center (DLR) has developed the Urban Footprint Processor (UFP) that represents an operational framework for the mapping of built-up areas based on a mass processing and analysis of TSX imagery. The UFP includes functionalities for data management, feature extraction, unsupervised classification, mosaicking, and post-editing. Based on >180.000 TSX StripMap scenes, the UFP was used in 2016 to derive a global map of human presence on Earth in a so far unique spatial resolution of 12 m per grid cell: the Global Urban Footprint (GUF). This work provides a comprehensive summary of the major achievements related to the Global Urban Footprint initiative, with dedicated sections focusing on aspects such as UFP methodology, basic product characteristics (specification, accuracy, global figures on urbanization derived from GUF), the user community, and the already initiated future roadmap of follow-on activities and products. The active community of >250 institutions already working with the GUF data documents the relevance and suitability of the GUF initiative and the underlying high-resolution SAR imagery with respect to the provision of key information on the human presence on earth and the global human settlements properties and patterns, respectively.

Analysis of Orthorectification Accuracy of Pleiades and SPOT6 Images For Mapping Basic of RDTR Coastal Area (Case Study: District of Jenu, Tuban)

The coastal area of Tuban Regency in various spatial plans is planned to be one of the economic growth centers in East Java. The plan requires a detailed Spatial Plan (RDTR) map, especially the Coastal Area with high accuracy. However, the current RDTR map still lacks high accuracy. Therefore, the purpose of this research is to analyze the accuracy of high-resolution satellite image orthorectification, so that it can be used for making RDTR base map. In this research, orthorectification process is done by using satellite image data of Pleiades 1A and SPOT6 with Rational Polynomial Coefficient (RPC) method. As a supporting data are Ground Control Point (GCP) of 11 points and Independent Check Point (ICP) of 12 points and DEM Astrium Terra SAR-X data for satellite image altitude correction so that the image is upright. Based on the processing and data analysis, the accuracy horizontal image of Upright Pleiades 1A is 0.25 meters and the SPOT6 Upright image is 1.8 meters. Based on the horizontal accuracy value, the satellite images of Pleiades 1A and SPOT6 meet the horizontal accuracy standard of the base map scale of 1: 5000 and 1: 10,000 in accordance with Perka BIG No. 15 the year 2014. In addition, this research also conducted the perturbation of TSS of Pleiades 1A satellite image and SPOT6 using Laili algorithm 2015. From the result of image processing and ground truth data can be said that TSS concentration is low (<100 mg / l) according to Permen LH Number 01 of 2010. Thus can be said that marine waters in District of Jenu classified as clean and it does not affect shoreline changes. The result of correlation test of image TSS of Pleiades 1A and SPOT6 with ground truth data is very strong while image data of Pleiades 1A and SPOT6 with aerial photography data have low and very low correlation coefficient.

Staring Spotlight TerraSAR-X SAR Interferometry for Identification and Monitoring of Small-Scale Landslide Deformation

We discuss enhanced processing methods for high resolution Synthetic Aperture Radar(SAR) interferometry (InSAR) to monitor small landslides with difficult spatial characteristics,such as very steep and rugged terrain, strong spatially heterogeneous surface motion,and coherence-compromising factors, including vegetation and seasonal snow cover. The enhancedmethods mitigate phase bias induced by atmospheric effects, as well as topographic phase errorsin coherent regions of layover, and due to inaccurate blending of high resolution discontinuouswith lower resolution background Digital Surface Models (DSM). We demonstrate the proposedmethods using TerraSAR-X (TSX) Staring Spotlight InSAR data for three test sites reflecting diversechallenging landslide-prone mountain terrains in British Columbia, Canada. Comparisons withcorresponding standard processing methods show significant improvements with resultingdisplacement residuals that reveal additional movement hotspots and unprecedented spatial detailfor active landslides/rockfalls at the investigated sites.