Temporal Baseline Research Articles

Source parameters of the 2017Mw 6.2 Yukon earthquake doublet inferred from coseismic GPS and ALOS-2 deformation measurements

We investigated an M_w ∼ 6.2 earthquake doublet on the border of the USA and Canada using ALOS2 Light-of-Sight displacements and GPS measurements. We selected three L-band ALOS-2 interfergorams with temporal baselines of one yr to extract coseismic deformation maps, in which master and slave images were both acquired in July. A subpixel-based alignment and another range spectral splitting techniques under the GAMMA InSAR software framework were applied to improve the interferometric coherence and reduce the effects of phase anomalies in two of the three interferometric pairs due to either ionospheric delay or a potential focusing issues in the generation of the ALOS2 SLC data. The updated interferograms convincingly reveal deformation fringe patterns produced by the two earthquakes. We conducted a nonlinear geophysical inversion to estimate the geometric parameters of the earthquakes with the InSAR and GPS measurements. The best-fitting model shows that a thrust faulting on a reverse fault and left-lateral strike-slip faulting on a nearly vertical fault with the centroid depths of 9.3±0.6 and 8.4±0.7 km, respectively, are most likely responsible for the earthquake doublet. The eastern Denali fault (EDF) and Duke River fault are major active faults in the region and the earthquake doublet could be due to reactivation of the part of the two faults system.

OPTIMUM CONDITIONS FOR DIFFERENTIAL SAR INTERFEROMETRY TECHNIQUE TO ESTIMATE HIMALAYAN GLACIER VELOCITY

Abstract. Differential SAR Interferometry (DInSAR) is the process of differencing two Interferograms for measuring surface movement with an accuracy of millimeter range. The DInSAR process can be applied to observe glacier movement, earthquake deformations, volcanic activities and rate of subsidence or uplift caused due to the extraction of groundwater or coal. By using single pass interferometry technique we can also generate accurate DEM. In this paper, we are presenting the movement of a Chhota Shigri glacier with the help two pass DInSAR technique and mainly we concentrated on the optimum conditions for estimating glacier movement using DInSAR. We got good coherence and Interferogram fringes for L-band sensor with less temporal baseline. Therefore, we generated glacier velocity using ALOS-2 data with 14 days temporal baseline. Initially, we generated Interferogram (defo-pair) by taking 10th March 2015 image as a master and 24th March 2015 image as a slave. But this generated Interferogram also having topographic information and atmospheric errors with the displacement component. Therefore, we used SRTM DEM for removing topographic information from the Interferogram. Because we are using L-band data, results may not be affected by troposphere. Maximum glacier velocity we observed in the accumulation zone as 7.285 cm/day in the month of March and while it’s moving towards ablation zone the glacier velocity is decreasing.

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.

A Motion Compensation Strategy for Airborne Repeat-Pass SAR Data

Generating accurate repeat-pass interferometric airborne synthetic aperture radar (SAR) products demands the precise compensation of the 3-D motion of the aircraft. This requires to estimate and correct small residual motion errors (RMEs) within the accuracy limits of the sensor navigation subsystem, e.g., using residual motion compensation (MoCo) algorithms. Because of their data-driven nature, the performance of these algorithms severely degrades for heavily decorrelated interferograms. This letter proposes a generic RME estimation and compensation strategy optimally estimating RME in a stack of SAR acquisitions, where some interferometric pairs are strongly affected by decorrelation. The algorithm works even if the whole scene decorrelates, as long as the coherence magnitude is reasonably high over short temporal and spatial baselines. The approach entails correcting the navigation data of each slave image of a one-to-many interferometric network with a cumulative correction. The summation is over the results of a precursory application of a general data-driven residual MoCo algorithm (e.g., multisquint) to interferometric pairs for which the impact of interferometric decorrelation is marginal (i.e., small temporal and/or spatial baselines). Compared to other RME correction strategies, the main appeal of the proposed approach lies in the simplicity of its implementation. The overall methodology is tested on a zero-baseline time series acquired at L-band by the German Aerospace Center’s airborne system F-SAR.

Monitoring of the 2015 Villarrica Volcano Eruption by Means of DLR’s Experimental TET-1 Satellite

Villarrica Volcano is one of the most active volcanoes in the South Andes Volcanic Zone. This article presents the results of a monitoring of the time before and after the 3 March 2015 eruption by analyzing nine satellite images acquired by the Technology Experiment Carrier-1 (TET-1), a small experimental German Aerospace Center (DLR) satellite. An atmospheric correction of the TET-1 data is presented, based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GDEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor data with the shortest temporal baseline to the TET-1 acquisitions. Next, the temperature, area coverage, and radiant power of the detected thermal hotspots were derived at subpixel level and compared with observations derived from MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Thermal anomalies were detected nine days before the eruption. After the decrease of the radiant power following the 3 March 2015 eruption, a stronger increase of the radiant power was observed on 25 April 2015. In addition, we show that the eruption-related ash coverage of the glacier at Villarrica Volcano could clearly be detected in TET-1 imagery. Landsat-8 imagery was analyzed for comparison. The information extracted from the TET-1 thermal data is thought be used in future to support and complement ground-based observations of active volcanoes.

Extraction of digital elevation model from Chinese GF-3 C-band synthetic aperture radar data with a step-wise method focusing on facilitating phase unwrapping

GaoFen-3 (GF-3) is the first fully polarimetric C-band synthetic aperture radar (SAR) satellite in China. Interferometric observation is an important capability of GF-3. However, the long temporal baseline is a great challenge for repeat-pass interferometric synthetic aperture radar (InSAR) processing, especially over mountainous areas. Phase noise and complex topography make phase unwrapping difficult. This paper proposes a step-wise approach for high-resolution InSAR data processing focusing on facilitating phase unwrapping. First, the coarse GF-3 digital elevation model (DEM) is reconstructed by InSAR processing with multilooking of large looks, which is used to suppress phase noise. Second, the coarse GF-3 DEM is used to remove the terrain phase from the InSAR phase with multilooking of small looks, which can reduce phase gradient and improve the accuracy of phase unwrapping. After several iterations, the GF-3 DEM is finally inversed with multilooking of 2 looks, which is of high resolution and high accuracy. The performance of GF-3 C-band InSAR data on the extraction of DEM is examined over a deciduous forested area with the proposed method. The root-mean-square error of the extracted GF-3 DEM is 3.78 m in comparison with the LiDAR DEM.

Analyzing the Effect of Temporal Baseline on the Geolocation Accuracy of Next Generation Synthetic Aperture Radar Data

Bu çalışmada, 2007 yılından günümüze dek yörüngeye oturtulan ve yeni nesil yapay açıklı radar (SAR) uyduları olarak betimlenen misyonların lideri konumundaki TerraSAR-X (TSX) uydusundan elde edilen dijital yüzey modelleri (DYM) üzerinde zamansal baz uzunluğunun etki analizi gerçekleştirilmiştir. Uyduların aynı bölge üzerinden iki farklı geçişi arasındaki zamansal baz uzunluğu, DYM kalitesi üzerinde doğrudan etkili bir interferometrik parametredir. Çalışmada, bu parametrenin TSX’den üretilen DYM kalitesindeki etkisinin saptanması için aralarında TSX’in en kısa tekrar geçiş süresi olan 1 periyot (11 gün) bulunan bir interferometrik SAR (InSAR) görüntü çifti ile 17 periyot (187 gün) bulunan ikinci bir çiftin karşılaştırmalı doğruluk analizi gerçekleştirilmiştir. Analizlerde, zamansal baz uzunluğu etkisinin direkt olarak kanıtlanabilmesi için sonucu etkiyebilecek diğer tüm parametrelerin eşdeğer olduğu görüntü çiftleri kullanılmıştır. Uygulamalar, Berlin, Almanya üzerinde 20 km’lik bir alanı kapsayan 15 alçalış yönünde alınmış yüksek çözünürlüklü spotlight (HS) mod TSX görüntüsü ile gerçekleştirilmiştir. DYM’ler 2 m grid aralığında üretilmiş olup kalite göstergesi olan mutlak düşey doğruluklar radargrametri tekniği ile elde edilmiş ve yine 2 m çözünürlüklü bir referans DYM ile model bazlı kıyaslama yöntemi ile analiz edilmiştir. Analizler yerleşim alanı ve orman alanı sınıfları için ayrı ayrı yapılmıştır. Elde edilen sonuçlar, zamansal baz uzunluğunun DYM kalitesi üzerinde beklenenden daha büyük bir etki yarattığını ve 1 periyotluk minimum zamansal baz uzunluğunda elde edilen DYM’lerin 17 periyotluk süre sonunda elde edilene göre hem yerleşim hem de ormanlık alanda yaklaşık %20 daha başarılı olduğu gerçeğini ortaya koymuştur. 

A New InSAR Phase Demodulation Technique Developed for a Typical Example of a Complex, Multi-Lobed Landslide Displacement Field, Fels Glacier Slide, Alaska

Landslides can have complex, spatially strongly inhomogeneous surface displacement fields with discontinuities from multiple active lobes that are deforming while failing on nested slip surfaces at different depths. For synthetic aperture radar interferometry (InSAR), particularly at lower resolutions, these characteristics can cause significant aliasing of the wrapped phase. In combination with steep terrain and seasonal snow cover, causing layover and temporal decorrelation, respectively, traditional phase unwrapping can become unfeasible, even after topographic phase contributions have been removed with an external high-resolution digital surface model (DSM). We present a novel method: warp demodulation that reduces the complexity of the phase unwrapping problem for noisy and/or aliased, low-resolution interferograms of discontinuous landslide displacement. The key input to our warp demodulation method is a single (or several) reference interferogram(s) from a high-resolution sensor mode such as TerraSAR-X Staring Spotlight with short temporal baseline and good coherence to allow localization of phase discontinuities and accurate unwrapping. The task of constructing suitable phase surfaces to approximate individual to-be-demodulated interferograms from the reference interferogram is made difficult by strong and spatially inhomogeneous temporal, seasonal, and interannual variations of the landslide with individual lobes accelerating or decelerating at different rates. This prevents using simple global scaling of the reference. Instead, our method uses an irregular grid of small patches straddling strong spatial gradients and phase discontinuities in the reference to find optimum local scaling factors that minimize the residual phase gradients across the discontinuities after demodulation. Next, for each to-be-demodulated interferogram, from these measurements we interpolate a spatially smooth global scaling function, which is then used to scale the (discontinuous) reference. Demodulation with the scaled reference leads to a residual phase that is also spatially smooth, allowing it to be unwrapped robustly after low-pass filtering. A key assumption of warp demodulation is that the locations of the phase discontinuities can be mapped in the reference and that they are stationary in time at the scale of the image resolution. We carry out extensive tests with simulated data to establish the accuracy, robustness, and limitations of the new method with respect to relevant parameters, such as decorrelation noise and aliasing along phase discontinuities. A realistic parameterization of the method is demonstrated for the example of the Fels Glacier Slide in Alaska using a recent late-summer high-resolution staring spotlight interferometric image pair from TerraSAR-X to demodulate. We show warp demodulation results for also recent but early-summer, partially incoherent interferograms of the same sensor, as well as for older and coarser aliased interferograms from RADARSAT-2, ALOS-1, and ERS.

Mapping and Characterizing Thermal Dilation of Civil Infrastructures with Multi-Temporal X-Band Synthetic Aperture Radar Interferometry

Temperature variation plays a significant role in the long-term structural behaviour of civil infrastructures, but very few quantitative studies have measured and analysed the infrastructures’ global thermal dilation because of their large sizes and geometric complexities. The modern Differential Synthetic Aperture Radar Interferometry (DInSAR) technique has great potential in applications of their thermal dilation mapping and characterization due to the techniques’ unique capabilities for use in large areas, with high-resolution, and at low-costs for deformation measurements. However, the practical application of DInSAR in thermal dilation estimation is limited by difficulty in the precise separation from the residual topographic phase and the trend deformation phase. Moreover, due to a lack of thermal dilation characteristics analyses in previous studies, the thermal dilation mechanisms are still unclear to users, which restricts the accurate understanding of the thermal dilation evolution process. Given the above challenges, an advanced multi-temporal DInSAR approach is proposed in this study, and the effectiveness of this approach was presented using three cases studies concerning different infrastructure types. In this method, the coherent, incoherent, and semantic information of structures were combined in order to refine the detection of point-like targets (PTs). Interferometric subsets with small temporal baselines and temperature differences were used for high-resolution topography estimation. A pre-analysis was adopted to determine the transmission direction, spatial pattern, and temporal variation of the thermal dilation. Then, both the traditional least squares estimation and our robust coherence-weighted least squares regression analysis were performed between the time series displacements and the corresponding temperatures to quantitatively estimate the thermal dilation model. The results were verified in terms of the estimated linear thermal dilation coefficient, which indicates the greater reliability of our method. Furthermore, the thermal dilation characteristics of different civil infrastructure types were analysed, which facilitates a greater understanding of the thermal dilation evolution process of civil infrastructures.

Multi-temporal, multi-frequency, and multi-polarization coherence and SAR backscatter analysis of wetlands

Despite recent research into the Interferometric Synthetic Aperture Radar (InSAR) technique for wetland mapping worldwide, its capability has not yet been thoroughly investigated for Canadian wetland ecosystems. Accordingly, this study statistically analysed interferometric coherence and SAR backscatter variation in a study area located on the Avalon Peninsula, Newfoundland and Labrador, Canada, consisting of various wetland classes, including bog, fen, marsh, swamp, and shallow-water. Specifically, multi-temporal L-band ALOS PALSAR-1, C-band RADARSAT-2, and X-band TerraSAR-X data were used to investigate the effect of SAR frequency and polarization, as well as temporal baselines on the coherence degree in the various wetland classes. SAR backscatter and coherence maps were also used as input features into an object-based Random Forest classification scheme to examine the contribution of these features to the overall classification accuracy. Our findings suggested that the temporal baseline was the most influential factor for coherence maintenance in herbaceous wetlands, especially for shorter wavelengths. In general, coherence was the highest in L-band and intermediate/low for both X- and C-band, depending on the wetland classes and temporal baseline. The Wilcoxon rank sum test at the 5% significance level found significant difference (P-value < 0.05) between the mean values of HH/HV coherence at the peak of growing season. The test also suggested that L-band intensity and X-band coherence observations were advantageous to discriminate complex wetland classes. Notably, an overall classification accuracy of 74.33% was attained for land cover classification by synergistic use of both SAR backscatter and interferometric coherence. Thus, the results of this study confirmed the potential of incorporating SAR and InSAR features for mapping Canadian wetlands and those elsewhere in the world with similar ecological characteristics.

Ground subsidence observation of solid waste landfill park using multi-temporal radar interferometry

ABSTRACTLand subsidence on landfill parks needs to be consistently and periodically measured because the landfill areas tend to subside unexpectedly. Although in-situ measurements have been adopted in general, these have a number of limitations of spatial and temporal resolutions because of the high cost. However, the use of interferometric synthetic aperture radar (InSAR) can overcome these disadvantages. In this study, we carried out two experiments using the InSAR method. We then compared the interferometric coherence between ALOS PALSAR and TerraSAR-X data and measured the ground subsidence using multi-temporal TerraSAR-X data acquired from ascending and descending paths. The mean coherences from the ALOS PALSAR and TerraSAR-X interferograms were 0.26 and 0.54, respectively. The coherence from TerraSAR-X was nearly 2 times higher than that of ALOS PALSAR, despite its shorter wavelength of radar signal. These results showed that the data with the shorter temporal baseline is appropriate to monitor the ground subsidence on landfill park areas. As a result of measuring surface deformation, the mean line-of-sight (LOS) deformation rates estimated from the small baseline subset (SBAS) method were −2.4 and −3.2 cm/year for the ascending and descending data of TerraSAR-X, respectively. Also, the mean deformation rate in the vertical and east–west directions were −5.7 and −1.7 cm/year, respectively. The root mean square error (RMSE) of InSAR measurements by comparing with the in-situ measurements was about 1.2 cm/year and the coefficient of determination () was about 0.97. These results indicated good agreements between the InSAR measurements and the in-situ measurements.

Archaeological sites as Distributed Long-term Observing Networks of the Past (DONOP)

Archaeological records provide a unique source of direct data on long-term human-environment interactions and samples of ecosystems affected by differing degrees of human impact. Distributed long-term datasets from archaeological sites provide a significant contribution to establish local, regional, and continental-scale environmental baselines and can be used to understand the implications of human decision-making and its impacts on the environment and the resources it provides for human use. Deeper temporal environmental baselines are essential for resource and environmental managers to restore biodiversity and build resilience in depleted ecosystems. Human actions are likely to have impacts that reorganize ecosystem structures by reducing diversity through processes such as niche construction. This makes data from archaeological sites key assets for the management of contemporary and future climate change scenarios because they combine information about human behavior, environmental baselines, and biological systems. Sites of this kind collectively form Distributed Long-term Observing Networks of the Past (DONOP), allowing human behavior and environmental impacts to be assessed over space and time. Behavioral perspectives are gained from direct evidence of human actions in response to environmental opportunities and change. Baseline perspectives are gained from data on species, landforms, and ecology over timescales that long predate our typically recent datasets that only record systems already disturbed by people. Biological perspectives can also provide essential data for modern managers wanting to understand and utilize past diversity (i.e., trophic and/or genetic) as a way of revealing, and potentially correcting, weaknesses in our contemporary wild and domestic animal populations.

Tracking Human-Induced Landscape Disturbance at the Nasca Lines UNESCO World Heritage Site in Peru with COSMO-SkyMed InSAR

The “Lines and Geoglyphs of Nasca and Palpa” in Peru are among the most well-known UNESCO World Heritage Sites globally, and an exemplar of site where heritage assets cannot be separated from their natural and anthropogenic environment. The site is exposed to interactions with natural processes, as well as human presence. In this work, 3-m resolution synthetic aperture radar (SAR) StripMap HIMAGE HH-polarised scenes acquired by the X-band COSMO-SkyMed constellation are exploited to track two events of human-induced landscape disturbance that occurred in December 2014 and January 2018. Pre-, cross-, and post-event interferometric SAR (InSAR) pairs characterised by small temporal and normal baselines allow the detection of temporal decorrelation associated with the two events, the extent and time reference of which match with online photographic and video evidence, published literature, web news, and press releases by the Ministry of Culture in Peru. Further elements enhancing the understanding of the 2018 event come from 10-m resolution Sentinel-2B satellite data that reveal the occurrence of apparent changes of surface reflectance due to uncovering of the light grey-yellow clay underneath the darker pebble constituting the fragile surface of the Pampa de Jumana. This scientific study confirms that SAR imagery archives, such as those being built by COSMO-SkyMed for Nasca, prove valuable for the retrospective analysis and digital recording of human-induced landscape disturbance events from space. These archives therefore act as essential sources of geospatial information on the conservation history of heritage sites and assets.

Detection of Forest Disturbance With Spaceborne Repeat-Pass SAR Interferometry

Focusing on open forests and woodlands within the Injune Landscape Collaborative Project research area in central southeast Queensland, Australia, and using dual-pol (HH and HV) ALOS PALSAR repeat-pass InSAR data (temporal baseline of 92 days), this paper explores the detection of forest disturbance from the spaceborne repeat-pass InSAR correlation magnitude by developing a simple and efficient forest disturbance detection approach. In particular, a generic physical InSAR scattering model is derived by accounting for the forest disturbance information as well as the normal temporal decorrelation effects that are later compensated for using the modified Random Volume over Ground model. Based on the generic model, a quantitative indicator of forest disturbance is retrieved, namely, disturbance index that varies from 0 (no disturbance) to 1 (complete deforestation). This index is compared with that identified using a time series of Landsat sensor data over a selective logging area and has a relative root mean square error of 13% at a spatial resolution of 0.8 ha. This paper highlights the use of the co-pol InSAR correlation magnitude for forest disturbance detection, which serves as a complimentary application to using the cross-pol counterpart for forest height inversion in a companion work. Given the global availability of this type of data (e.g., Japanese Aerospace Exploration Agency’s ALOS-1/2 and NASA-ISRO’s NISAR), the method is anticipated to contribute to the range of tools being developed for large-scale forest disturbance assessment and monitoring.

A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery

Reliable information about the spatial distribution of surface waters is critically important in various scientific disciplines. Synthetic Aperture Radar (SAR) is an effective way to detect floods and monitor water bodies over large areas. Sentinel-1 is a new available SAR and its spatial resolution and short temporal baselines have the potential to facilitate the monitoring of surface water changes, which are dynamic in space and time. While several methods and tools for flood detection and surface water extraction already exist, they often comprise a significant manual user interaction and do not specifically target the exploitation of Sentinel-1 data. The existing methods commonly rely on thresholding at the level of individual pixels, ignoring the correlation among nearby pixels. Thus, in this paper, we propose a fully automatic processing chain for rapid flood and surface water mapping with smooth labeling based on Sentinel-1 amplitude data. The method is applied to three different sites submitted to recent flooding events. The quantitative evaluation shows relevant results with overall accuracies of more than 98% and F-measure values ranging from 0.64 to 0.92. These results are encouraging and the first step to proposing operational image chain processing to help end-users quickly map flooding events or surface waters.

L-Band Temporal Coherence Assessment and Modeling Using Amplitude and Snow Depth over Interior Alaska

Interferometric synthetic aperture radar (InSAR) provides the capability to detect surface deformation. Numerous processing approaches have been developed to improve InSAR results and overcome its limitations. Regardless of the processing methodology, however, temporal decorrelation is a major obstacle for all InSAR applications, especially over vegetated areas and dynamic environments, such as Interior Alaska. Temporal coherence is usually modeled as a univariate exponential function of temporal baseline. It has been, however, documented that temporal variations in surface backscattering due to the change in surface parameters, i.e., dielectric constant, roughness, and the geometry of scatterers, can result in gradual, seasonal, or sudden decorrelations and loss of InSAR coherence. The coherence models introduced so far have largely neglected the effect of the temporal change in backscattering on InSAR coherence. Here, we introduce a new temporal decorrelation model that considers changes in surface backscattering by utilizing the relative change in SAR intensity between two images as a proxy for the change in surface scattering parameters. The model also takes into account the decorrelation due to the change in snow depth between two images. Using the L-band Advanced Land Observation Satellite (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) data, the model has been assessed over forested and shrub landscapes in Delta Junction, Interior Alaska. The model decreases the RMS error of temporal coherence estimation from 0.18 to 0.09 on average. The improvements made by the model have been statistically proved to be significant at the 99% confidence level. Additionally, the model shows that the coherence of forested areas are more prone to changes in backscattering than shrub landscape. The model is based on L-band data and may not be expanded to C-band or X-band InSAR observations.

Estimation of ground subsidence in the city of Morelia, Mexico using Satellite Interferometry (INSAR)s

In recent years, the city of Morelia, in central Mexico, has been affected by differential subsidence of the soil evidenced by faults and fractures on the ground. The goal of this study is to obtain ground deformation time series from InSAR interferograms, in order to determine the temporal and spatial evolution of subsidence in the city of Morelia. Twenty-eight ENVISAT-ASAR images, acquired from May 2003 to September 2010, were processed. Perpendicular and temporal baselines of less than 400 m and 420 days respectively, were used as criteria to select interferograms. From a total of 378 interferograms, only 65 were considered to be of sufficient quality, based on the observed signal decorrelation. The results show that most of the city of Morelia is not affected by significant subsidence. In the areas where subsidence occurs, the rates of subsidence vary between 0.7 and 5 cm/yr. Most of the subsidence is in the form of discrete circular patterns and along segments of the observed surface faults. Ground subsidence is concentrated in specific areas on the footwalls of La Colina, Central Camionera and La Paloma faults. Subsidence, however, is not continuous along these faults, but observed only in some segments. In some cases, as in the case of La Paloma fault, the subsidence appears to be directly associated with the strong lithological contrast between the footwall and the hanging wall. In the other two cases, such as the Central Camionera and La Colina faults, the differential subsidence observed appears to be related with the complex basement and sedimentary structure of the volcanic subsoil of the city of Morelia and related primarily to differential compaction of the sedimentary fill.

An Assessment of Temporal Decorrelation Compensation Methods for Forest Canopy Height Estimation Using Airborne L-Band Same-Day Repeat-Pass Polarimetric SAR Interferometry

We assess and compare several algorithms to compensate for temporal decorrelation observed in repeat-pass L-band polarimetric interferometric synthetic aperture radar (PolInSAR) measurements of forest canopy height. The analysis is performed on data acquired with an approximately 45-min temporal baseline using the uninhabited aerial vehicle synthetic aperture radar collected in August 2009 over temperate and boreal forests of the U.S. state of Maine and the Canadian province of Quebec. This investigation presents several compensation methods based on the classical random volume over ground model, which include fixing the value of the extinction parameter, fixing the temporal decorrelation magnitude, or varying temporal decorrelation estimates with height. We also compare results with the random motion over ground model. While these methods have been presented in the literature previously, a comparison of the different methods and an assessment of their height estimation accuracy applied to the same datasets have not yet been performed. In addition, we introduce the use of ancillary reference forest height data from airborne large footprint lidar to estimate model parameters and to mitigate solution ambiguities. We finally demonstrate that this mitigation strategy is robust and suitable for use with future spaceborne lidar missions such as the Global Ecosystems Dynamics Investigation. The resulting PolInSAR canopy height estimates correspond well with those obtained from coincident field and airborne lidar data. Height estimation differences of 3.4 m (RMSE) were observed between the PolInSAR- and lidar-derived canopy height maps when using the fixed extinction method. These can be partially attributed to inherent differences in the sensor spatial resolutions and geolocation accuracy. The RMS error between the PolInSAR height estimates and the field collected Lorey's heights was 2.4 m.

Spatial and Temporal Baseline Information on Marine Megafauna-Data Facilitated by a Wildlife Tour Operator

The protection of marine megafauna within Europe is rather fragmented. Developing conservation measures for highly mobile species presents definite challenges, particularly due to the many knowledge gaps. Recent studies have shown that these gaps can be filled in by Platforms of Opportunity (PO) which create low-cost approaches. However, the number of wildlife tour operators actively collecting PO data related to distribution and relative abundance of marine fauna remains limited. In this study, we investigated whether effort-corrected data on marine megafauna facilitated by a wildlife tour operator afforded robust long temporal data (2011-2015). Sightings data, collected in the wider Mount’s Bay area (southwest Cornwall, UK), along with a GPS application, were collected to accurately record survey effort. In addition, radial sighting distances and detection curves were computed to explore the robustness of the data. Density maps of marine megafauna indicated that encounters occurred throughout the area in all three seasons but the temporal distribution was significantly different with numbers peaking in autumn. Odontocetes were mostly recorded during autumn, basking shark (Cetorhinus maximus) and ocean sunfish (Mola mola) were more abundant during summer and leatherback turtles (Dermochelys coriacea) were recorded occasionally. Our data showed that this shallow coastal environment is particularly important as a nursing area for harbour porpoises (Phocoena phocoena). Risso’s dolphins (Grampus griseus) showed a high semi-residency pattern for adults with calves within one core-habitat. As such, the study provides important spatial and temporal baseline data that are essential for the protection of marine megafauna through the development of an ecological network of marine protected areas within UK waters. Although, data facilitated by wildlife operators have certain shortcomings we highlight that the protocols developed here secured efficient and precise data. Such collection protocols can be implemented on a larger scale, ultimately enhancing research monitoring efforts and marine ecosystem management.

Airborne DInSAR Results Using Time-Domain Backprojection Algorithm: A Case Study Over the Slumgullion Landslide in Colorado With Validation Using Spaceborne SAR, Airborne LiDAR, and Ground-Based Observations

The major impediment to accurate airborne repeat-pass differential synthetic aperture radar (SAR) interferometry (DInSAR) is compensating for aircraft motion caused by air turbulence. Various motion compensation (MoCo) procedures have been used in the airborne DInSAR processing to acquire reliable deformation mapping. In this paper, we present the use of time-domain backprojection (BP) algorithm for SAR focusing in an airborne DInSAR survey: No MoCo procedure is needed because the BP algorithm is inherently able to compensate for platform motion. In this study, we present the results of a pilot study aimed at demonstrating the feasibility of deformation mapping with an airborne SAR system based on the monitoring of the Slumgullion landslide in Colorado, USA between July 3 and 10 of 2015. The employed airborne SAR system is an Artemis SlimSAR that is a compact, modular, and multi-frequency radar system. Airborne light detection and ranging and global navigation satellite system (GNSS) observations, as well as spaceborne DInSAR results using COSMO-SkyMed (CSK) images, were used to verify the performance of the airborne SAR system. The surface velocities of the landslide derived from the airborne DInSAR observations showed good agreement with the GNSS and spaceborne DInSAR estimates. A three-dimensional deformation map of the Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topographic variation. This study shows that an inexpensive airborne L -band DInSAR system has the potential to measure centimeter level deformation with flexible temporal and spatial baselines.