Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas

Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR) techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs), (high coherence features) to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process

Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas

Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR) techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs), (high coherence features) to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process

Remote Sensing Approaches and Related Techniques to Map and Study Landslides

Landslide is one of the costliest and fatal geological hazards, threatening and influencing the socioeconomic conditions in many countries globally. Remote sensing approaches are widely used in landslide studies. Landslide threats can also be investigated through slope stability model, susceptibility mapping, hazard assessment, risk analysis, and other methods. Although it is possible to conduct landslide studies using in-situ observation, it is time-consuming, expensive, and sometimes challenging to collect data at inaccessible terrains. Remote sensing data can be used in landslide monitoring, mapping, hazard prediction and assessment, and other investigations. The primary goal of this chapter is to review the existing remote sensing approaches and techniques used to study landslides and explore the possibilities of potential remote sensing tools that can effectively be used in landslide studies in the future. This chapter also provides critical and comprehensive reviews of landslide studies focus¬ing on the role played by remote sensing data and approaches in landslide hazard assessment. Further, the reviews discuss the application of remotely sensed products for landslide detection, mapping, prediction, and evaluation around the world. This systematic review may contribute to better understanding the extensive use of remotely sensed data and spatial analysis techniques to conduct landslide studies at a range of scales

Time series analysis of very slow landslides in the three Gorges region through small baseline SAR offset tracking

Sub-pixel offset tracking has been used in various applications, including measurements of glacier movement, earthquakes, landslides, etc., as a complementary method to time series InSAR. In this work, we explore the use of a small baseline subset (SBAS) Offset Tracking approach to monitor very slow landslides with centimetre-level annual displacement rate, and in challenging areas characterized by high humidity, dense vegetation cover, and steep slopes. This approach, herein referred to as SBAS Offset Tracking, is used to minimize temporal and spatial de -correlation in offset pairs, in order to achieve high density of reliable measurements. This approach is applied to a case study of the Tanjiahe landslide in the Three Gorges Region. Using the TerraSAR-X Staring Spotlight (TSX-ST) data, with sufficient density of observations, we estimate the precision of the SBAS offset tracking approach to be 2-3 cm on average. The results demonstrated accord well with corresponding GPS measurements

SAR Phase Unwrapping Using Path-Based Least-Squares Phase Estimation and Region-Growing with Polynomial-Based Phase Prediction

Differential SAR interferometry (DInSAR) has proven to be a processing approach that is well-suited to precisely identifying large-scale land deformation patterns. This is useful for many environmental monitoring applications, but the speckle noise and temporal decorrelation present in SAR images presents particular challenges in processing SAR images. This research focuses on the phase unwrapping problem, proposing two new approaches: Polynomial-Based Region-Growing Phase Unwrapping (PBRGPU), which expands upon the traditional region-growing approach to phase unwrapping; and Path-Based Least-Squares Phase Unwrapping (PBLSPU), which extends the least-squares phase unwrapping models in a path-based framework. Both algorithms were tested using simulated data and interferograms generated from RADARSAT-2 data. Both approaches significantly reduced the root mean square error compared to the algorithms they build from, and achieved a similar level of performance to the commonly-used SNAPHU algorithm without the need for masking low coherence areas

Constructive and Destructive Processes During the 2018–2019 Eruption Episode at Shiveluch Volcano, Kamchatka, Studied From Satellite and Aerial Data

Dome-building volcanoes often develop by intrusion and extrusion, recurrent destabilization and sector collapses, and renewed volcanic growth inside the collapse embayment. However, details of the structural architecture affiliated with renewed volcanic activity and the influences of regional structures remain poorly understood. Here, we analyze the recent activity of Shiveluch volcano, Kamchatka Peninsula, characterized by repeated episodes of lava dome growth and destruction due to large explosions and gravity-driven collapses. We collect and process a multisensor dataset comprising high-resolution optical (aerial and tri-stereo Pleiades satellite), radar (TerraSAR-X and TanDEM-X satellites), and thermal (aerial and MODIS, Sentinel-2, and Landsat 8 satellites) data. We investigate the evolution of the 2018–2019 eruption episode and evaluate the morphological and structural changes that led to the August 29, 2019 explosive eruption and partial dome collapse. Our results show that a new massive lava lobe gradually extruded onto the SW flank of the dome, concurrent with magmatic intrusion into the eastern dome sector, adding 0.15 km3 to the lava dome complex. As the amphitheater infilled, new eruption craters emerged along a SW-NE alignment close to the amphitheater rim. Then, the large August 29, 2019 explosive eruption occurred, followed by partial dome collapse, which was initially directed away from this SW-NE trend. The eruption and collapse removed 0.11 km3 of the dome edifice and led to the formation of a new central SW-NE-elongated crater with dimensions of 430 m × 490 m, a collapse scar at the eastern part of the dome, and pyroclastic density currents that traveled ∼12 km downslope. This work sheds light on the structural architecture dominated by a SW-NE lineament and the complex interplay of volcano constructive and destructive processes. We develop a conceptual model emphasizing the relevance of structural trends, namely, 1) a SW-NE-oriented (possibly regional) structure and 2) the infilled amphitheater and its decollement surface, both of which are vital for understanding the directions of growth and collapse and for assessing the potential hazards at both Shiveluch and dome-building volcanoes elsewhere

Recent technological and methodological advances for the investigation of landslide dams

River-damming by landslides is a widespread phenomenon around the world. Recent advances in remote sensing technology and the rising commercial availability of their products enable the assemblage of increasingly more complete inventories and improve monitoring efforts. On the ground, multi-method dating campaigns enhance our understanding of the timelines of dam formation and failure. In comparison to single-dating methods, they reduce uncertainty by using different materials from the landslide deposit, facilitate the advantages of each method, and consider the deposit and the source area. They can pin dates on the time of lake drainage where backwater sediments are included in the dating campaign and thus inform about dam longevity. Geophysical methods provide non-invasive and rapid methods to investigate the properties and interior conditions of landslide dams. By identifying, e.g. evolving zones of weakness and saturation they can aid in the monitoring of a dam in addition to providing information on interior stratification for scientific research. To verify results from geophysical campaigns, and to add details of dam interior structures and geotechnical properties, knowledge of their sedimentology is essential. This information is gathered at sections from breached dams, other (partially) eroded landslide deposits, and through laboratory testing of sampled material. Combining the knowledge gained from all these methods with insights from blast-fill and embankment dam construction, physical and numerical modelling in multi-disciplinary research projects is the way forward in landslide dam research, assessment and monitoring. This review offers a broad, yet concise overview of the state-of-the-art in the aforementioned research fields. It completes the review of Fan et al. (2020) on the formation and impact on landslide dams

Landslides

Landslides - Investigation and Monitoring offers a comprehensive overview of recent developments in the field of mass movements and landslide hazards. Chapter authors use in situ measurements, modeling, and remotely sensed data and methods to study landslides. This book provides a thorough overview of the latest efforts by international researchers on landslides and opens new possible research directions for further novel developments

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing