ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research

Monitoring of Tsunami/Earthquake Damages by Polarimetric Microwave Remote Sensing Technique

Polarization characterizes the vector state of EM wave. When interacting with polarized wave, rough natural surface often induces dominant surface scattering; building also presents dominant double-bounce scattering. Tsunami/earthquake causes serious destruction just by inundating the land surface and destroying the building. By analyzing the change of surface and double-bounce scattering before and after disaster, we can achieve a monitoring of damages. This constitutes one basic principle of polarimetric microwave remote sensing of tsunami/earthquake. The extraction of surface and double-bounce scattering from coherency matrix is achieved by model-based decomposition. The general four-component scattering power decomposition with unitary transformation (G4U) has been widely used in the remote sensing of tsunami/earthquake to identify surface and double-bounce scattering because it can adaptively enhance surface or double-bounce scattering. Nonetheless, the strict derivation in this chapter conveys that G4U cannot always strengthen the double-bounce scattering in urban area nor strengthen the surface scattering in water or land area unless we adaptively combine G4U and its duality for an extended G4U (EG4U). Experiment on the ALOS-PALSAR datasets of 2011 great Tohoku tsunami/earthquake demonstrates not only the outperformance of EG4U but also the effectiveness of polarimetric remote sensing in the qualitative monitoring and quantitative evaluation of tsunami/earthquake damages

Advances on the investigation of landslides by space-borne synthetic aperture radar interferometry

Landslides are destructive geohazards to people and infrastructure, resulting in hundreds of deaths and billions of dollars of damage every year. Therefore, mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks. In this paper, the main outcomes relevant to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon-5 initiative cooperation project ID 59,339 “Earth observation for seismic hazard assessment and landslide early warning system” are reported. The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks, detect potential landslides in wide regions, and demonstrate EO-based landslide early warning system over selected landslides. This work only focuses on the landslide hazard content of the project, and thus, in order to achieve these objectives, the following tasks were developed up to now: a) a procedure for phase unwrapping errors and tropospheric delay correction; b) an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements; c) the application of polarimetric SAR interferometry (PolInSAR) to increase the number and quality of monitoring points in landslide-prone areas; d) the semiautomatic mapping and preliminary classification of active displacement areas on wide regions; e) the modeling and identification of landslides in order to identify triggering factors or predict future displacements; and f) the application of an InSAR-based landslide early warning system on a selected site. The achieved results, which mainly focus on specific sensitive regions, provide essential assets for planning present and future scientific activities devoted to identifying, mapping, characterizing, monitoring and predicting landslides, as well as for the implementation of early warning systems.This work was supported by the ESA-MOST China DRAGON-5 project with ref. 59339, by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI), and the European Funds for Regional Development under grant [grant number PID2020-117303GB-C22], by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335, by the Natural Science Foundation of China [grant numbers 41874005 and 41929001], the Fundamental Research Funds for the Central University [grant numbers 300102269712 and 300102269303], and China Geological Survey Project [grant numbers DD20190637 and DD20190647]. Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref. [grant number 202006560031] and [grant number 202004180062], respectively

Method for landslides detection with semi-automatic procedures: The case in the zone center-east of Cauca department, Colombia

Landslides are a common natural hazard that causes human casualties, but also infrastructure damage and land-use degradation. Therefore, a quantitative assessment of their presence is required by means of detecting and recognizing the potentially unstable areas. This research aims to develop a method supported on semiautomatic methods to detect potential mass movements at a regional scale. Five techniques were studied: Morphometry, SAR interferometry (InSAR), Persistent Scatterer InSAR (PS-InSAR), SAR polarimetry (PolSAR) and NDVI composites of Landsat 5, Landsat 7, and Landsat 8. The case study was chosen within the mid-eastern area of the Cauca state, which is characterised by its mountainous terrain and the presence of slope instabilities, officially registered in the CGS-SIMMA landslide inventory. This inventory revealed that the type `slide' occurred with 77.4% from the entire registries, `fall' with 16.5%, followed by `creeps' with 3%, flows with 2.6%, and `lateral spread' with 0.43%. As a result, we obtained the morphometric variables: slope, CONVI, TWI, landform, which were highly associated with landslides. The effect of a DEM in the processing flow of the InSAR method was similar for the InSAR coherence variable using the DEMs ASTER, PALSAR RTC, Topo-map, and SRTM. Then, a multiInSAR analysis gave displacement velocities in the LOS direction between -10 and 10 mm/year. With the dual-PolSAR analysis (Sentinel-1), VH and VV C-band polarised radar energy emitted median values of backscatters, for landslides, about of -14.5 dB for VH polarisation and -8.5 dB for VV polarisation. Also, L-band fully polarimetric NASA-UAVSAR data allowed to nd the mechanism of dispersion of CGS landslide inventory: 39% for surface scattering, 46.4% for volume dispersion, and 14.6% for double-bounce scattering. The optical remote sensing provided NDVI composites derived from Landsat series between 2012 and 2016, showing that NDVI values between 0.40 and 0.70 had a high correlation to landslides. In summary, we found the highest categories related to landslides by Weight of Evidence method (WofE) for each spaceborne technique applied. Finally, these results were merged to generate the landslide detection model by using the supervised machine learning method of Random Forest. By taking training and test samples, the precision of the detection model was of about 70% for the rotational and translational types.Los deslizamientos son una amenaza natural que causa pérdidas humanas, daños a la infraestructura y degradación del suelo. Una evaluación cuantitativa de su presencia se requiere mediante la detección y el reconocimiento de potenciales áreas inestables. Esta investigación tuvo como alcance desarrollar un método soportado en métodos semi-automáticos para detectar potenciales movimientos en masa a escala regional. Cinco técnicas fueron estudiadas: Morfometría, Interferometría radar, Interferometría con Persistent Scatterers, Polarimetría radar y composiciones del NDVI con los satélites Landsat 5, Landsat 7 y Landsat 8. El caso de estudio se seleccionó dentro de la región intermedia al este del departamento del Cauca, la cual se caracteriza por terreno montañoso y la presencia de inestabilidades de la pendiente oficialmente registrados en el servicio SIMMA del Servicio Geológico Colombiano. Este inventario reveló que el tipo de movimiento deslizamiento ocurrió con una frecuencia relativa de 77.4%, caidos con el 16.5% de los casos y reptaciones con 3%, flujos con 2.6% y propagación lateral con 0.43%. Como resultado, se obtuvo las variables morfométricas: pendiente, convergencia, índice topográfico de humedad y forma del terreno altamente asociados con los deslizamientos. El efecto de un DEM en el procesamiento del método InSAR fue similar para la variable coherencia usando los DEMs: ASTER, PAlSAR RTC, Topo-map y SRTM. Un análisis Multi-InSAR estimó velocidades de desplazamiento en dirección de vista del radar entre -10 y 10 mm/año. El análisis de polarimetría dual del Sentinel-1 arrojó valores de retrodispersión promedio de -14.5 dB en la banda VH y -8.5dB en la banda VV. Las cuatro polarimetrías del sensor aéreo UAVSAR permitió caracterizar el mecanismo de dispersión del Inventario de Deslizamiento así: 39% en el mecanismo de superficie, 46.4% en el mecanismo de volumen y 14.6% en el mecanismo de doble rebote. La información generada en el rango óptico permitió obtener composiciones de NDVI derivados de la plataforma Landsat entre los años 2012 y 2016, mostrando que el rango entre 0.4 y 0.7 tuvieron una alta asociación con los deslizamientos. En esta investigación se determinaron las categorías de las variables de Teledetección más altamente relacionadas con los movimientos en masa mediante el método de Pesos de Evidencias (WofE). Finalmente, estos resultados se fusionaron para generar el modelo de detección de deslizamientos usando el método supervisado de aprendizaje de máquina Random Forest. Tomando muestras aleatorias para entrenar y validar el modelo en una proporción 70:30, el modelo de detección, especialmente los movimientos de tipo rotacional y traslacional fueron clasificados con una tasa general de éxito del 70%.Ministerio de CienciasConvocatoria 647 de 2014Research line: Geotechnics and Geoenvironmental HazardDoctorad

INSAR COHERENCE AND POLARIMETRIC PARAMETERS BASED CHARACTERIZATION OF FLOODED AREA – CASE STUDY OF A NATURAL WORLD HERITAGE SITE KAZIRANGA NATIONAL PARK

Flood is a major threat to one of the UNESCO world heritage site of India-The Kaziranga National Park. Every year during the monsoon several hundreds of animals which include globally threatened species like single-horned Indian Rhinoceros of Kaziranga lose their lives due to the flood. The Synthetic Aperture Radar (SAR) can be used to monitoring the flood than the optical remote sensors because of their capability of all-weather and time-independent operability. The microwave L band is most suitable for the flood studies because of its higher penetration capability even through the vegetation. In this study, the advantages of SAR polarimetry and Interferometry of multi-temporal L band dual-pol data of ALOS PALSAR 2 were used to characterize the flooded area and also to monitor the flood extent. The H/ A/ Alpha decomposition gives a better characterization of the flooded area. The separability analysis is done with a different combination of decomposition parameters and the parameters having high-class separability between water and non-water areas are selected. Polarimetric classification using Random forest classifier is done on these selected decomposition parameters to classify the study into water and non-water areas. The classified images of different months before, during and after the flood time is used to quantitatively estimate the flood extent and for time series analysis. The Interferometric SAR coherence images along with the backscatter images are used to generate the RGB composites which also gives times series information on the flood impact

Monitoring von Hangbewegungen mit InSAR Techniken im Gebiet Ciloto, Indonesien

In this doctoral thesis, the InSAR techniques are applied to detect the ground movement phenomenon and to assess the InSAR result geometrically in the Ciloto area, Indonesia. Mainly, one of those techniques, the SB-SDFP algorithm, overcomes the limitations of conventional InSAR in monitoring rural and agricultural areas and can observe extremely slow landslides. The InSAR strategy is positively known as a promising option to detect and quantify the kinematics of active landslides on a large areal scale. To minimize the bias of the InSAR displacement result, the correction of the tropospheric phase delay was carried out in a first step. This procedure is demonstrated in experiments both in the small study area in Ciloto and in a larger area. The latter is an area located in Northern Baja California, Mexico and is dominated by tectonic activity as well as groundwater-induced subsidence. A detailed investigation of the slope movement's behavior in the Ciloto district was conducted utilizing multi-temporal and multi-band SAR data from ERS1/2 (1996-1999), ALOS PALSAR (2007-2009) and Sentinel-1 (2014-2018) satellites. The region was successfully identified as a permanent active landslide prone area, especially in the vicinity of the Puncak Pass and Puncak Highway. The full 3D velocity field and the displacement time series were estimated using the inversion model. The velocity rate was classified from extremely slow to slow movement. To comprehend the landslide's behavior, a further examination of the relationship between InSAR results and physical characteristics of the area was carried out. For the long period of a slow-moving landslide, the relationship between precipitation and displacement trend shows a weak correlation. It is concluded that the extremely slow to slow deformation is not directly influenced by the rainfall intensity, yet it effectuates the subsurface and the groundwater flow. The run-off process with rainfall exceeding a soil's infiltration capacity was suspected as the main driver of the slow ground movement phenomenon. However, when analyzing rapid and extremely rapid landslide events at Puncak Pass, a significant increase in the correlation coefficient between precipitation and displacement rate could be observed.In dieser Doktorarbeit wird die Anwendung von erweiterten Verarbeitungsstrategien von InSAR Daten zur Erkennung und geometrischen Bewertung der Bodenbewegungen im Ciloto - Indonesien dargestellt. Dieser Ansatz überwindet die Beschränkungen konventioneller SAR-Interferometrie und ermöglicht sowohl ein kontinuierliches Monitoring dieses landwirtschaftich geprägten Gebietes als auch die Erfassung extrem langsamer Hangrutschungen. Um eine Verzerrung der InSAR Deformationsergebnisse zu minimieren, wurde zunächst eine Korrektur der troposphärischen Phase durchgeführt. Diese neuartige Strategie wird sowohl im Forschungsgebiet Ciloto als auch an einem größeren Gebiet demonstriert. Bei letzterem handelt es sich um einen Küstenstreifen im nördlichen Niederkalifornien, Mexiko, welcher durch hohe tektonische Aktivität und grundwasserinduzierte Landsetzungen charakterisiert ist. Die detaillierte Untersuchung des Verhaltens von Hangrutschungen im Ciloto erfolgte durch die Verarbeitung multi-temporaler SAR-Daten unter Nutzung verschiedener Frequenzbänder, darunter ESR1/2 (1996-1999), ALOS PALSAR (2007-2009) und Sentinel-1 (2014-2018) Daten. Die Region konnte erfolgreich als permanent aktives Hangrutschungsgebiet identifiziert werden, wobei der Puncak Pass und der Puncak Highway ein erhöhtes Gefahrenpotential aufweisen. Ein 3D- Geschwindig-keitsfeld der Deformation und die zugehörigen Zeitreihen wurden mit dem Inversionsmodell berechnet. Die Geschwindigkeitsrate wurde als langsam bis extrem langsam klassifiziert. Um das dynamische Verhalten der Hangrutschung zu verstehen wurde, in einer weiteren Untersuchung die Beziehung zwischen dem InSAR-Ergebnis und den physikalischen Begebenheiten im Forschungsgebiet analysiert. Es wird der Schluss gezogen, dass die langsame bis extrem langsame Verformung nicht direkt von der Niederschlagsintensität beeinflusst wird, diese sich aber auf den Untergrund und die Grundwasserströmung auswirkt. Es wird vermutet, dass der Oberflächenablauf, welcher die Infiltrationskapazität des Bodens übersteigt, ausschlaggebend für das Phänomen der langsamen Bodenbewegung ist. Für die schnellen und extrem schnellen Hangrutschungen jedoch konnte eine signifikante Erhöhung des Korrelationskoeffizienten zwischen Niederschlag und Verschiebungsrate bei Untersuchungen der Hangrutschung am Puncak-Pass nachgewiesen werden

Application of Landsat-8 and ALOS-2 data for structural and landslide hazard mapping in Kelantan, Malaysia

Identification of high potential risk and susceptible zones for natural hazards of geological origin is one of the most important applications of advanced remote sensing technology. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan River basin, Peninsular Malaysia. Flooding and subsequent landslide occurrences generated significant damage to livestock, agricultural produce, homes and businesses in the Kelantan River basin. In this study, remote sensing data from the recently launched Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) on board the Advanced Land Observing Satellite-2 (ALOS-2) were used to map geologic structural and topographical features in the Kelantan River basin for identification of high potential risk and susceptible zones for landslides and flooding areas. The data were processed for a comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. The analytical hierarchy process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index (NDVI), land cover, distance to drainage, precipitation, distance to fault and distance to the road were extracted from remote sensing satellite data and fieldwork to apply the AHP approach. Directional convolution filters were applied to ALOS-2 data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. The combination of different polarization channels produced image maps that contain important information related to water bodies, wetlands and lithological units. The N-S, NE-SW and NNE-SSW lineament trends and dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan River basin. The analysis of field investigation data indicates that many of flooded areas were associated with high potential risk zones for hydrogeological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topographic regions. Numerous landslide points were located in a rectangular drainage system that is associated with a topographic slope of metamorphic and quaternary rock units. Consequently, structural and topographical geology maps were produced for Kelantan River basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping and identification of high potential risk zone for hydrogeological hazards. Geohazard mitigation programs could be conducted in the landslide recurrence regions and flooded areas to reduce natural catastrophes leading to loss of life and financial investments in the Kelantan River basin. In this investigation, Landsat-8 and ALOS-2 have proven to successfully provide advanced Earth observation satellite data for disaster monitoring in tropical environments

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Rapid Detection of Earthquake-triggered Landslides from Satellite Radar

Triggered landslides pose a major risk following large earthquakes in mountainous areas and disrupt emergency response efforts. If information on the spatial distribution of these landslides can be generated quickly enough, it is therefore invaluable to emergency response coordinators. At present, this information is commonly generated manually from optical satellite imagery, which is labour-intensive and can be delayed or left incomplete due to cloud cover. This means a complete picture of triggered landsliding is often unavailable within the time frame of the emergency response. Alternatively, empirical models can predict landslide probability based on factors such as shaking intensity and slope steepness within hours of an earthquake, but these models are static in time and not always reliable as they do not contain any observations of landslides. Satellite radar offers a third alternative method of generating landslide information for emergency response. These data can be acquired through cloud and are now available within days of any continental earthquake. Radar data are sensitive to landslides, which alter the scattering properties of the Earth’s surface, so could be used to generate all-weather information on landslide spatial distributions within days of an earthquake. Satellite radar data are routinely used to generate other products for emergency response, but for landslide detection, the testing and development of radar methods is not yet sufficiently advanced for them to be widely applied. In this thesis, I present new methods of landslide detection based on satellite radar coherence, a measure of the level of noise in an interferogram that reflects physical changes in the Earth’s surface such as landslides. I carry out systematic testing of new and existing methods of coherence-based landslide detection across four case study earthquakes using data from two satellite radar sensors, allowing identification of which method is preferable depending on the data available after an earthquake. Finally I experiment with combining empirical models and radar coherence methods. Overall, I demonstrate that useful information on landslide intensity can be generated within two weeks of an earthquake using satellite radar data, and that the addition of these data to empirical models can significantly improve their performance