The agricultural sector is the backbone which supports the livelihoods and the economic development of nations across the globe. In consequence, the need for robust and continuous monitoring of agricultural crops is primordial to face the interlinked challenges of growth rate population, food security and climate change. Synthetic Aperture Radar (SAR) sensors have the powerful imaging capability of operating at almost all weather conditions, independent of day and night illumination. By penetrating through clouds and into the vegetation canopy, the incident radar signal interacts with the structural and dielectric properties of the vegetation and soil, thus providing critical information of the crop state, such as height, biomass, crop yield or leaf structure, which can help devise sustainable agricultural management practices. This is achieved by means of the Polarimetric SAR Interferometry (PolInSAR) technique, which by coherently combining interferometric SAR acquisitions at different polarization states allows for the retrieval of biophysical parameters of the vegetation. In this framework, this thesis focuses on the development of crop monitoring techniques that properly exploit satellite-based PolInSAR data. All the known InSAR and PolInSAR methodologies for this purpose have been analysed. The sensitivity of these data provided by the TanDEM-X bistatic system to both the physical parameters of the scene (height and structure of the plants, moisture and roughness of the soil) and the sensor configuration (polarization modes and observation geometry) is evaluated. The effect of different simplifications made in the physical model of the scene on the crop estimates is assessed. The interferometric sensitivity requirements to monitor a crop scenario are more demanding than others, such as forests. Steep incidences associated with the largest spatial baselines provided by the available data set lead to the most accurate estimates under all the different model assumptions. Shallower incidences, on the other hand, generally yield important errors due to their characteristic shorter spatial baselines. Through the methodologies proposed in this thesis, PolInSAR data have shown potential to refine current methods for the quantitative estimation of crop parameters. Results encourage to continue further research towards the objective of achieving operational crop monitoring applications. / Work supported by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI) and the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P. Noelia Romero-Puig received a grant from the Generalitat Valenciana and the European Social Fund (ESF) [ACIF/2018/204].

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19283号 / 工博第4080号 / 新制||工||1629(附属図書館) / 32285 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 田村 正行, 教授 小池 克明, 准教授 須﨑 純一 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

In the form of images and videos, visual content has always attracted considerable interest and attention to itself since the early days of the computer era. Although, due to the high density of information in such contents, it has always been challenging to generate, process and broadcast videos and images. These challenges grew along with the demand for higher quality content and attained the research community's attention to themselves. Even though many works have been done by researchers and engineers in academic and industrial environments, the demand for high-quality content introduces new constraints on the quality, performance (speed) and energy consumption. This thesis focuses on a couple of image and video processing applications and introduces new approaches and tweaks to improve the performance and save resources while keeping the functionality intact. In the first part, we target Interferometric Synthetic Aperture Radar (InSAR), an imaging technique used by satellites to capture the earth's surface. Many algorithms have been developed to extract useful information, such as height and displacement, from such images. However, the sheer size of these images, along with the complexity of most of these algorithms, lead to very long processing time and resource utilization. In this work, we take one of the dominant algorithms used for almost every In-SAR application, Phase Unwrapping, and introduce an approach to gain up to 6.5 times speedups. We evaluated our method on InSAR images taken by the Radarsat-2 sensor and showed its impact on a real-world application. In the second part of this thesis, we look at a prevalent application, video streaming. These days video streaming dominates the internet traffic, so any slight improvement in terms of energy consumption or resource utilization will make a sizable difference. Although the streamers use various encoding techniques, the quality of experience of the clients prevents them from overplaying these techniques. On the other hand, there has been a growing interest in another venture of research which focuses on developing techniques that aim to restore the quality of the videos that have been subjected to compression. Although these techniques are used by many users on the receiver side, the streamers often ignore their capabilities. In our work, we introduce an approach that makes the streamer aware of the capabilities of the receiver and utilizes that awareness to reduce the cost of transmission without compromising the end user's quality of experience. We demonstrated the technique and proved our concept by applying it to the HEVC encoding standard and JCT-VC dataset. / Graduate

Permafrost deformation is expected to increase due to climatic perturbations such as amplified air and soil temperatures, resulting in permafrost thawing and subsequent subsidence. Palsas and peat plateaus are uplifted ice-rich peat mounds that experience permafrost subsidence. This is due to the uppermost layer of permafrost, known as the Active Layer (AL), that seasonally thaws and freezes. Interferometric Synthetic Aperture Radar (InSAR) is an interferometric stacking technique successfully applied over permafrost regions when monitoring ground subsidence. The Small Baseline Subset (SBAS) technique is based on interferograms produced by stacking Synthetic Aperture Radar (SAR) acquisitions with small normal baselines. In this study, seasonal Sentinel-1 SAR C-band data obtained during June, July, August and September (JJAS) was used to generate seasonal Line of Sight (LoS) deformation time series of palsas and peat plateaus in Tavvavuoma (Sweden) by using the SBAS technique. Chersky (Russia) has documented permafrost subsidence and was used as a reference site. Findings include that seasonal stacks with short normal baselines generated more robust results than inter-annual stacks with longer normal baselines and temporal data gaps. No instances of pronounced subsidence were reported during JJAS. Nevertheless, minor subsidence during the early season and negative development trends were identified in the Tavvavuoma 2020 andChersky 2020-2021 stacks, respectively. Increased subsidence during the mid-and late thaw season was detected. The SBAS technique performed better and resulted in less temporal and seasonal decorrelation in areas above the tree line (Tavvavuoma) compared to the lowlands in the forest-tundra (Chersky). The challenge lies in whether surface subsidence of palsas and peat plateaus in sporadic permafrost regions experience irreversible long-term changes or seasonally cyclic changes in the permafrost ground regime. Future studies are recommended to implement annual intervals, including winter images over Tavvavuoma.

Lake Mead, the largest reservoir in the United States along the Colorado River on the border between the states of Nevada and Arizona, is one of the nation's most important sources of freshwater. As reported by the U.S. drought monitor (USDM), the entire region has been experiencing recurring severe to extreme droughts since the early 2000s, which have further intensified during the past two years. The drought-driven water deficit caused Lake Mead's water volume to decrease to approximately one-third of its capacity, creating a water crisis and negatively affecting soil and groundwater storage across the region. Water deficits have further reduced the mass of water loading on the Earth's crust, causing it to elastically deform. I observe this process from the ground by recording the vertical land motion occurring at Global Navigation Satellite System (GNSS) stations, or from space via Interferometric Synthetic Aperture Radar (InSAR) technology. In this study, I analyze vertical deformation observations from GNSS sites and multi-temporal InSAR analysis of Sentinel-1A/B to investigate the contribution of water mass changes in lake, soil, and groundwater to the deformation signal. To achieve this, I remove the effects of glacial isostatic adjustment and non-tidal mass loads from GNSS/InSAR observations. Our findings indicate that recent drought periods led to a notable uplift near Lake Mead, averaging 7.3 mm/year from 2012 to 2015 and an even larger rate of 8.6 mm/year from 2020 to 2023. Further, I provide an estimate of the expected vertical crustal deformation in response to well-known changes in lake and soil moisture storage. For that, I quantify hydrological loads through two different loading models. These include the application of Green's functions for an elastic, layered, self-gravitating, spherical Earth, and the Love load numbers from the Preliminary Reference Earth Models (PREMs), as well as elastic linearly homogeneous half-space Earth models. I further test various load models against the GNSS observations. Our research further investigates the impact of local crustal properties and evaluates the output of several elastic loading models using crustal properties and different model types under non-drought and drought conditions. For future studies, I suggest a comprehensive analysis of the deformation field InSAR data. Also, rigorous monitoring of groundwater levels is essential to accurately predict changes in water masses based on deformation. In addition, for each data set, I suggest implementing an uncertainty analysis to assess the predictability of groundwater level changes based on vertical loading deformation observed by INSAR/GNSS data around the region. Obtaining such estimates will provide valuable insight into the dynamic interactions of the local aquifers with Lake Mead. / Master of Science / The drought has led to a decline of approximately 40 meters in Lake Mead since 1999. During the process of water mass loss from a lake, the crust lifts and extends from the center. However, the water mass loss seen on the lake is not sufficient to explain the movement seen at nearby GPS sites. Hence, the uplift loading of water loss in the form of other hydrological components surrounding Lake Mead needs to be estimated. Here, I analyze several models that best fit the geodetic displacements and try to fill in the gap in deformation observations.

The launch of Sentinel-1A/B satellites in 2014 and 2016 marked a pivotal moment in Synthetic Aperture Radar (SAR) technology, ushering in a golden era for SAR. With a revisit time of 6–12 days, these satellites facilitated the acquisition of extensive stacks of high-resolution SAR images, enabling advanced time series analysis. However, processing these stacks posed challenges like interferometric phase degradation and tropospheric phase delay. This study introduces an advanced Small Baseline Subset (SBAS) algorithm that optimizes interferometric pairs, addressing systematic errors through dyadic downsampling and Delaunay Triangulation. A novel statistical framework is developed for elite pixel selection, considering distributed and permanent scatterers, and a tropospheric error correction method using smooth 2D splines effectively identifies and removes error components with fractal-like structures. Beyond geodetic technique advancements, the research explores geological phenomena, detecting five significant slow slip events (SSEs) along the Southern San Andreas Fault using multitemporal SAR interferometric time series from 2015-2021. These SSEs govern aseismic slip dynamics, manifesting as avalanche-like creep rate variations. The study further investigates Managed Aquifer Recharge (MAR) as a nature-engineering-based solution in the Santa Ana Basin. Analyzing surface deformation from 2004 to 2022 demonstrates MAR's effectiveness in curbing land subsidence within Orange County, CA. Additionally, MAR has the potential to stabilize nearby faults by inducing a negative Coulomb stress change. Projecting into the future, a suggested 2% annual increase in recharge volume through 2050 could mitigate land subsidence and reduce seismic hazards in coastal cities vulnerable to relative sea level rise. This integrated approach offers a comprehensive understanding of geological processes and proposes solutions to associated risks. / Doctor of Philosophy / The launch of Sentinel-1A/B satellites in 2014 and 2016 marked a big step forward in radar technology, especially Synthetic Aperture Radar (SAR). These satellites, which revisit the same area every 6-12 days, allowed us to collect many high-quality radar images. This helped us study changes over time in a more advanced way. However, there were challenges in handling all these images, like errors in the radar signals and delays caused by the Earth's atmosphere. We devised a smart algorithm based on the Small Baseline Subset (SBAS) to tackle these challenges. It helps optimize how we use pairs of radar images, reducing errors. We also developed a new method to pick the best pixels in the images and corrected errors caused by the atmosphere using mathematical methods. Moving beyond just technology, our research also looked at interesting Earth events. We found five major slow slip events along the Southern San Andreas Fault by studying radar data from 2015 to 2021. These events are like slow-motion slips along the fault, influencing how the ground moves. We also explored Managed Aquifer Recharge (MAR) as a solution in the Santa Ana Basin. By studying ground movement from 2004 to 2022, we found that MAR helped prevent the land from sinking in Orange County, California. It even has the potential to make nearby faults more stable. Looking ahead, increasing MAR activities by 2% each year until 2050 could protect against land sinking and reduce earthquake risks in coastal cities facing rising sea levels. This combined approach gives us a better understanding of Earth's processes and suggests ways to tackle related problems.

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Many cities in Sweden are partly located on clay and because of that, some urban city centres are undergoing significant subsidence. To measure subsidence in cities, precise leveling has been the traditional technique, but the interest for the Persistent Scatter InSAR (PSI) technique has increased in the last years, in this application. With the PSI technique, a mm-accuracy can be obtained and the analyses can be done over large areas. In this study, a validation between the PSI and the precise leveling techniques was performed for a selection of buildings located in areas that are facing great subsidence. A correlation between the subsidence rate achieved in the PSI analyses and near-surface soil type was also done, to easier identify risk zones. The city of Uppsala was chosen as study area, because it is partly built on deep layers of clay and the consulting company Bjerking AB has established a leveling network with metal pegs on many buildings. One ascending and one descending PSI analysis was performed, with Sentinel-1 data from the period mid-2015 to mid-2019, and the PSI analyses were done in SARPROZ. After the PSI analyses, comparative permanent scatters (PS) points and metal pegs were identified creating validation pairs. 15 different validation pairs were identified in four different objects, which was one or two buildings. The PSI analyses showed that Uppsala is undergoing significant subsidence in some parts, with an annual rate of about 6 mm/year in the line-of-sight (LOS) direction, which corresponds to about 7.5 mm/year in the vertical direction. The areas of greatest deformation were exclusively found on postglacial clay. The standard deviation of the time series were calculated around their linear regression lines, which was a measure of how temporal coherent the points were. The mean of this standard deviation for the PS points in the 15 validation pairs was 1.5 mm. This standard deviation increased to 2.3 mm in the time series where the direction was transformed from LOS to vertical and where the movements were in respect to the benchmarks. Between the PSI and the precise leveling techniques, in the validation, the vertical subsidence rate differed less than 1 mm/year in all validation pairs and the mean of all differences was 0.56 mm/year. Based on these results, Sentinel-1 data can measure urban subsidence in a satisfactory way, when the PSI technique is applied.

La production de Modèles Numériques de Terrain (MNT) a subi d’importantes évolutions durant les deux dernières décennies en réponse à une demande croissante pour des besoins scientifiques et industriels. De nombreux satellites d’observation de la Terre, utilisant des capteurs tant optiques que radar, ont permis de produire des MNT couvrant la plupart de la surface terrestre. De plus, les algorithmes de traitement d’images et de nuages de points ont subi d’importants développements. Ces évolutions ont fourni des MNT à différentes échelles pour tout utilisateur. Les applications basées sur la géomorphologie ont profité de ces progrès. En effet, ces applications exploitent les formes du terrain dont le MNT constitue une donnée de base. Cette étude a pour objectif d’évaluer l’impact des paramètres de production de MNT par photogrammétrie et par InSAR sur la qualité de position et de forme de ces modèles. La qualité de position, évaluée par les producteurs de MNT, n’est pas suffisante pour évaluer la qualité des formes. Ainsi, nous avons décrit les méthodes d’évaluation de la qualité de position et de forme et la différence entre elles. Une méthode originale de validation interne, qui n’exige pas de données de référence, a été proposée. Ensuite, l’impact des paramètres de l’appariement stéréoscopique, du traitement interférométrique ainsi que du rééchantillonnage, sur l’altitude et les formes, a été évalué. Finalement, nous avons conclu sur des recommandations pour choisir correctement les paramètres de production, en particulier en photogrammétrie.Nous avons observé un impact négligeable de la plupart des paramètres sur l’altitude, à l’exception de ceux de l’InSAR. Par contre, un impact significatif existe sur les dérivées de l’altitude. L’impact des paramètres d’appariement présente une forte dépendance avec la morphologie du terrain et l’occupation du sol. Ainsi, le choix de ces paramètres doit être effectué en prenant en considération ces deux facteurs. L’effet des paramètres du traitement interférométrique se manifeste par des erreurs de déroulement de phase qui affectent principalement l’altitude et peu les dérivées. Les méthodes d’interpolation et la taille de maille présentent un impact faible sur l’altitude et important sur ses dérivées. En effet, leur valeur et leur qualité dépendent directement de la taille de maille. Le choix de cette taille doit s’effectuer selon les besoins de l’application visée. Enfin, nous avons conclu que ces paramètres sont interdépendants et peuvent avoir des effets similaires. Leur choix doit être effectué en prenant en considération à la fois l’application concernée, la morphologie du terrain et son occupation du sol afin de minimiser l’erreur des résultats finaux et des conclusions. / The production of Digital Elevation Models (DEMs) has undergone significant evolution duringthe last two decades resulting from a growing demand for scientific as well as industrial purposes.Many Earth observation satellites, using optical and radar sensors, have enabled the production ofDEMs covering most of the Earth’s surface. The algorithms of image and point cloud processing havealso undergone significant evolution. This progress has provided DEMs on different scales, which canfulfill the requirements of many users. The applications based on geomorphology have benefitted fromthis evolution. Indeed, these applications concentrate specifically on landforms for which the DEMconstitutes a basic data.The aim of this study is to assess the impact of the parameters of DEM production byphotogrammetry and InSAR on position and shape quality. The position quality, assessed by DEMproducers, is not sufficient for the evaluation of shape quality. Thus, the evaluation methods ofposition and shape quality and the difference between them are described. A novel method of internalvalidation, which does not require reference data, is proposed. Then, the impact of image matchingand interferometric processing parameters as well as resampling, on elevation and shapes, is assessed.Finally, we conclude on recommendations on how to choose the production parameters correctly,particularly for photogrammetry.We observe little impact from most of the parameters on the elevation, except InSAR parameters.On the other hand, there is a significant impact on the elevation derivatives. The impact of matchingparameters presents a strong dependence on the terrain morphology and the landcover. Therefore,these parameters have to be selected by taking into account these two factors. The effect ofinterferometric processing manifests by phase unwrapping errors that mainly affect the elevation andless the derivatives. The interpolation methods and the mesh size present a small impact on theelevation and a significant impact on the derivatives. Indeed, the value of the derivatives and theirquality depend directly on the mesh size. The selection of this size has to be made according to theforeseen application. Finally, we conclude that these parameters are interdependent and can havesimilar effects. They must be selected according to the foreseen application, the terrain morphologyand the landcover in order to minimize the error in the final results and the conclusions.