Land Cover Classification using Sentinel-1 Radar Mission Interferometry

Synthetic Aperture Radar (SAR) has been widely used for many years in the field of remote sensing. SAR has valuable contribution due to its ability to provide complementary information to optical systems, penetration of radar waves through volumetric targets and high-resolution. SAR has the ability to operate during day and night. It provides operational services under all weather conditions. SAR imagery has many applications including land cover changes, environmental monitoring, climate change and military surveillance. This work focuses on land cover classification with SAR interferometry (InSAR) technique using Sentinel-1 space radar image pair. Sentinel-1 data were collected over the southern part of Estonia. Two SLC SAR images were acquired from both Sentinel-1A and Sentinel-1B with six days temporal difference. In this study, interferometric coherence and backscattering intensity processing chains have been set up and applied to Sentinel-1 SAR image pair. The Sentinel Application Platform (SNAP) has been used for processing of single pair for Sentinel-1 mission. The SNAP is an European Space Agency (ESA) software. The Sentinel-1 image pair processing has been done using Sentinel-1 Toolbox (S1TBX) which is a part of SNAP. Corine Land Cover (CLC) 2012 database has been used as a reference data with 20 m resolution. The CLC2012 contains land use/cover information for most of the European countries. A single optical image from Sentinel-2A was additionally used for feature extraction. An overall accuracy of 68% to 73% was achieved when performing classification into five classes (Urban, Field, Forest, Peat-land, Water) using supervised classification with k-nearest neighbour (kNN) algorithm. The accuracy assessment was done by using confusion matrices

Resonant oscillations in the Hawai`ian archipelago and tropical instability vortices and their fronts, frontal instabilities, and cross-frontal differences

Ph.D

Remote Sensing of the Oceans

This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements

A Study on Coastal Winds and Wind Waves UsingHigh-Resolution SAR Images

Tohoku University課

Semantic Search and Discovery for Earth Observation Products using Ontology Services

Η πρόσβαση σε δεδομένα που έχουν προέλθει από την παρατήρηση της Γης παραμένει δύσκολη για τους περισσότερους απλούς χρήστες μέχρι και σήμερα. Οι υπάρχουσες μηχανές αναζήτησης απευθύνονται σε ειδικούς του πεδίου παρατήρησης της Γης, αδυνατώντας να καλύψουν τις ανάγκες επιστημονικών κοινοτήτων από άλλα πεδία, καθώς και απλών χρηστών που δεν είναι εξοικειωμένοι με τα δεδομένα παρατήρησης της Γης. Στα πλαίσια αυτής της διπλωματικής αναπτύχθηκαν σημασιολογικές τεχνολογίες οι οποίες ενσωματώθηκαν σε μια πλατφόρμα αναζήτησης ΕΟ-netCDF δεδομένων. Οι τεχνολογίες αυτές με τη χρήση οντολογιών επιτρέπουν την εύκολη αναζήτηση και πρόσβαση σε δεδομένα που έχουν προέλθει από την παρατήρηση της Γης.Access to Earth Observation products remains difficult for end-users in most domains. Although various search engines have been developed, these are targeted for advanced Earth Observation users, and fail to support scientific communities from other domains, as well as casual users not familiar with the concepts of Earth Observation.In the context of this thesis, we developed semantic technologies that were used to semantically enhance a search engine for EO-netCDF product. We present how these technologies utilize ontology services to substantially improve the ability of end-users to explore, understand and exploit the vast amount of Earth Observation data that is available nowadays

Utilização da Norma JPEG2000 para codificar proteger e comercializar Produtos de Observação Terrestre

Applications like, change detection, global monitoring, disaster detection and management have emerging requirements that need the availability of large amounts of data. This data is currently being capture by a multiplicity of instruments and EO (Earth Observation) sensors originating large volumes of data that needs to be stored, processed and accessed in order to be useful – as an example, ENVISAT accumulates, in a yearly basis, several hundred terabytes of data. This need to recover, store, process and access brings some interesting challenges, like storage space, processing power, bandwidth and security, just to mention a few. These challenges are still very important on today’s technological world. If we take a look for example at the number of subscribers of ISP (Internet Service Providers) broadband services on the developed world today, one can notice that broadband services are still far from being common and dominant. On the underdeveloped countries the picture is even dimmer, not only from a bandwidth point of view but also in all other aspects regarding information and communication technologies (ICTs). All this challenges need to be taken into account if a service is to reach the broadest audience possible. Obviously protection and securing of services and contents is an extra asset that helps on the preservation of possible business values, especially if we consider such a costly business as the space industry. This thesis presents and describes a system which allows, not only the encoding and decoding of several EO products into a JPEG2000 format, but also supports some of the security requirements identified previously that allows ESA (European Space Agency) and related EO services to define and apply efficient EO data access security policies and even to exploit new ways to commerce EO products over the Internet.Aplicações como, detecção de mudanças no terreno, monitorização planetária, detecção e gestão de desastres, têm necessidades prementes que necessitam de vastas quantidades de dados. Estes dados estão presentemente a ser capturados por uma multiplicidade de instrumentos e sensores de observação terrestre, que originam uma enormidade de dados que necessitam de ser armazenados processados e acedidos de forma a se tornarem úteis – por exemplo, a ENVISAT acumula anualmente varias centenas de terabytes de dados. Esta necessidade de recuperar, armazenar, processar e aceder introduz alguns desafios interessantes como o espaço de armazenamento, poder de processamento, largura de banda e segurança dos dados só para mencionar alguns. Estes desafios são muito importantes no mundo tecnológico de hoje. Se olharmos, por exemplo, ao número actual de subscritores de ISP (Internet Service Providers) de banda larga nos países desenvolvidos podemos ficar surpreendidos com o facto do número de subscritores desses serviços ainda não ser uma maioria da população ou dos agregados familiares. Nos países subdesenvolvidos o quadro é ainda mais negro não só do ponto de vista da largura de banda mas também de todos os outros aspectos relacionados com Tecnologias da Informação e Comunicação (TICs). Todos estes aspectos devem ser levados em consideração se se pretende que um serviço se torne o mais abrangente possível em termos de audiências. Obviamente a protecção e segurança dos conteúdos é um factor extra que ajuda a preservar possíveis valores de negócio, especialmente considerando industrias tão onerosas como a Industria Espacial. Esta tese apresenta e descreve um sistema que permite, não só a codificação e descodificação de diversos produtos de observação terrestre para formato JPEG2000 mas também o suporte de alguns requisitos de segurança identificados previamente que permitem, á Agência Espacial Europeia e a outros serviços relacionados com observação terrestre, a aplicação de politicas eficientes de acesso seguro a produtos de observação terrestre, permitindo até o aparecimento de novas forma de comercialização de produtos de observação terrestre através da Internet

Extraction d'informations de changement à partir des séries temporelles d'images radar à synthèse d'ouverture

A large number of successfully launched and operated Synthetic Aperture Radar (SAR) satellites has regularly provided multitemporal SAR and polarimetric SAR (PolSAR) images with high and very high spatial resolution over immense areas of the Earth surface. SAR system is appropriate for monitoring tasks thanks to the advantage of operating in all-time and all-weather conditions. With multitemporal data, both spatial and temporal information can simultaneously be exploited to improve the results of researche works. Change detection of specific features within a certain time interval has to deal with a complex processing of SAR data and the so-called speckle which affects the backscattered signal as multiplicative noise.The aim of this thesis is to provide a methodology for simplifying the analysis of multitemporal SAR data. Such methodology can benefit from the advantages of repetitive SAR acquisitions and be able to process different kinds of SAR data (i.e. single, multipolarization SAR, etc.) for various applications. In this thesis, we first propose a general framework based on a spatio-temporal information matrix called emph{Change Detection Matrix} (CDM). This matrix contains temporal neighborhoods which are adaptive to changed and unchanged areas thanks to similarity cross tests. Then, the proposed method is used to perform three different tasks:1) multitemporal change detection with different kinds of changes, which allows the combination of multitemporal pair-wise change maps to improve the performance of change detection result;2) analysis of change dynamics in the observed area, which allows the investigation of temporal evolution of objects of interest;3) nonlocal temporal mean filtering of SAR/PolSAR image time series, which allows us to avoid smoothing change information in the time series during the filtering process.In order to illustrate the relevancy of the proposed method, the experimental works of the thesis is performed on four datasets over two test-sites: Chamonix Mont-Blanc, France and Merapi volcano, Indonesia, with different types of changes (i.e., seasonal evolution, glaciers, volcanic eruption, etc.). Observations of these test-sites are performed on four SAR images time series from single polarization to full polarization, from medium to high, very high spatial resolution: Sentinel-1, ALOS-PALSAR, RADARSAT-2 and TerraSAR-X time series.La réussite du lancement d'un grand nombre des satellites Radar à Synthèse d'Ouverture (RSO - SAR) de nouvelle génération a fourni régulièrement des images SAR et SAR polarimétrique (PolSAR) multitemporelles à haute et très haute résolution spatiale sur de larges régions de la surface de la Terre. Le système SAR est approprié pour des tâches de surveillance continue ou il offre l'avantage d'être indépendant de l'éclairement solaire et de la couverture nuageuse. Avec des données multitemporelles, l'information spatiale et temporelle peut être exploitée simultanément pour rendre plus concise, l'extraction d'information à partir des données. La détection de changement de structures spécifiques dans un certain intervalle de temps nécessite un traitement complexe des données SAR et la présence du chatoiement (speckle) qui affecte la rétrodiffusion comme un bruit multiplicatif. Le but de cette thèse est de fournir une méthodologie pour simplifier l'analyse des données multitemporelles SAR. Cette méthodologie doit bénéficier des avantages d'acquisitions SAR répétitives et être capable de traiter différents types de données SAR (images SAR mono-, multi- composantes, etc.) pour diverses applications. Au cours de cette thèse, nous proposons tout d'abord une méthode générale basée sur une matrice d'information spatio-temporelle appelée Matrice de détection de changement (CDM). Cette matrice contient des informations de changements obtenus à partir de tests croisés de similarité sur des voisinages adaptatifs. La méthode proposée est ensuite exploitée pour réaliser trois tâches différentes: 1) la détection de changement multitemporel avec différents types de changements, ce qui permet la combinaison des cartes de changement entre des paires d'images pour améliorer la performance de résultat de détection de changement; 2) l'analyse de la dynamicité de changement de la zone observée, ce qui permet l'étude de l'évolution temporelle des objets d'intérêt; 3) le filtrage nonlocal temporel des séries temporelles d'images SAR/PolSAR, ce qui permet d'éviter le lissage des informations de changement dans des séries pendant le processus de filtrage.Afin d'illustrer la pertinence de la méthode proposée, la partie expérimentale de la thèse est effectuée sur deux sites d'étude: Chamonix Mont-Blanc, France et le volcan Merapi, Indonésie, avec différents types de changements (i.e. évolution saisonnière, glaciers, éruption volcanique, etc.). Les observations de ces sites d'étude sont acquises sur quatre séries temporelles d'images SAR monocomposantes et multicomposantes de moyenne à haute et très haute résolution: des séries temporelles d'images Sentinel-1, ALOS-PALSAR, RADARSAT-2 et TerraSAR-X