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

Soil Moisture Estimation for landslide monitoring: A new approach using multi-temporal Synthetic Aperture RADAR data

This study explores the utility of the Spotlight2 X-band Synthetic Aperture Radar product developed by the Italian Space Agency for use in multi-temporal estimation of soil moisture in a landslide monitoring context, using a time series of monthly images of the Hollin Hill Landslide Observatory – North Yorkshire, UK. The study shows the complexity of surface soil moisture at an active landslide, using high resolution in situ soil moisture data. This in situ data is also used for ground truthing the soil moisture estimations from the SAR data. The study shows the limitations of inter-and intra-sensor calibration within the Cosmo-SkyMed array and contextualises this problem within the current research climate where SAR imagery is increasingly being created using multi-satellite constellation, while being used, increasingly, by environmental scientists rather than remote sensing specialists

Europe's Space capabilities for the benefit of the Arctic

In recent years, the Arctic region has acquired an increasing environmental, social, economic and strategic importance. The Arctic’s fragile environment is both a direct and key indicator of the climate change and requires specific mitigation and adaptation actions. The EU has a clear strategic interest in playing a key role and is actively responding to the impacts of climate change safeguarding the Arctic’s fragile ecosystem, ensuring a sustainable development, particularly in the European part of the Arctic. The European Commission’s Joint Research Centre has recently completed a study aimed at identifying the capabilities and relevant synergies across the four domains of the EU Space Programme: earth observation, satellite navigation, satellite communications, and space situational awareness (SSA). These synergies are expected to be key enablers of new services that will have a high societal impact in the region, which could be developed in a more cost-efficient and rapid manner. Similarly, synergies will also help exploit to its full extent operational services that are already deployed in the Arctic (e.g., the Copernicus emergency service or the Galileo Search and rescue service could greatly benefit from improved satellite communications connectivity in the region).JRC.E.2-Technology Innovation in Securit

Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work

Object-based Interpretation Methods for Mapping Built-up Areas

Osajulkaisut: Publication 1: Leena Matikainen, Juha Hyyppä, and Marcus E. Engdahl. 2006. Mapping built-up areas from multitemporal interferometric SAR images - A segment-based approach. Photogrammetric Engineering and Remote Sensing, volume 72, number 6, pages 701-714. Publication 2: Leena Matikainen, Juha Hyyppä, and Hannu Hyyppä. 2003. Automatic detection of buildings from laser scanner data for map updating. In: Hans-Gerd Maas, George Vosselman, and Andre Streilein (editors). Proceedings of the ISPRS Working Group III/3 Workshop on 3-D Reconstruction from Airborne Laserscanner and InSAR Data. Dresden, Germany. 8-10 October 2003. International Society for Photogrammetry and Remote Sensing. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, volume 34, part 3/W13, pages 218-224. ISSN 1682-1750. Publication 3: Leena Matikainen, Juha Hyyppä, and Harri Kaartinen. 2009. Comparison between first pulse and last pulse laser scanner data in the automatic detection of buildings. Photogrammetric Engineering and Remote Sensing, volume 75, number 2, pages 133-146. Publication 4: Leena Matikainen. 2006. Improving automation in rule-based interpretation of remotely sensed data by using classification trees. The Photogrammetric Journal of Finland, volume 20, number 1, pages 5-20. Publication 5: Leena Matikainen, Juha Hyyppä, Eero Ahokas, Lauri Markelin, and Harri Kaartinen. 2010. Automatic detection of buildings and changes in buildings for updating of maps. Remote Sensing, volume 2, number 5, pages 1217-1248. Publication 6: Leena Matikainen and Kirsi Karila. 2011. Segment-based land cover mapping of a suburban area - Comparison of high-resolution remotely sensed datasets using classification trees and test field points. Remote Sensing, volume 3, number 8, pages 1777-1804.There is a growing demand for high-quality spatial data and for efficient methods of updating spatial databases. In the present study, automated object-based interpretation methods were developed and tested for coarse land use mapping, detailed land cover and building mapping, and change detection of buildings. Various modern remotely sensed datasets were used in the study. An automatic classification tree method was applied to building detection and land cover classification to automate the development of classification rules. A combination of a permanent land cover classification test field and the classification tree method was suggested and tested to allow rapid analysis and comparison of new datasets. The classification and change detection results were compared with up-to-date map data or reference points to evaluate their quality. The combined use of airborne laser scanner data and digital aerial imagery gave promising results considering topographic mapping. In automated building detection using laser scanner and aerial image data, 96% of all buildings larger than 60 m2 were correctly detected. This accuracy level (96%) is compatible with operational quality requirements. In automated change detection, about 80% of all reference buildings were correctly classified. The overall accuracy of a land cover classification into buildings, trees, vegetated ground and non-vegetated ground using laser scanner and aerial image data was 97% compared with reference points. When aerial image data alone were used, the accuracy was 74%. A comparison between first pulse and last pulse laser scanner data in building detection was also carried out. The comparison showed that the use of last pulse data instead of first pulse data can improve the building detection results. The results yielded by automated interpretation methods could be helpful in the manual updating process of a topographic database. The results could also be used as the basis for further automated processing steps to delineate and reconstruct objects. The synthetic aperture radar (SAR) and optical satellite image data used in the study have their main potential in land cover monitoring applications. The coarse land use classification of a multitemporal interferometric SAR dataset into built-up areas, forests and open areas lead to an overall accuracy of 97% when compared with reference points. This dataset also appeared to be promising for classifying built-up areas into subclasses according to building density. Important topics for further research include more advanced interpretation methods, new and multitemporal datasets, optimal combinations of the datasets, and wider sets of objects and classes. From the practical point of view, work is needed in fitting automated interpretation methods in operational mapping processes and in further testing of the methods.Laadukkaan paikkatiedon tarve kasvaa jatkuvasti, ja paikkatietokantojen ajantasaistukseen tarvitaan tehokkaita menetelmiä. Tässä tutkimuksessa käytettiin useita uudenaikaisia kaukokartoitusaineistoja. Niiden pohjalta kehitettiin ja testattiin automaattisia, objektipohjaisia tulkintamenetelmiä yleispiirteiseen maankäytön luokitteluun, yksityiskohtaiseen maanpeitteen ja rakennusten kartoitukseen sekä rakennusten muutostulkintaan. Rakennusten tulkintaan ja maanpeiteluokitteluun sovellettiin automaattista luokittelupuumenetelmää, jonka avulla voidaan automatisoida luokittelusääntöjen kehittäminen. Uusia aineistoja voidaan analysoida ja vertailla nopeasti, kun luokittelupuumenetelmää käytetään yhdessä pysyvän maanpeiteluokittelutestikentän kanssa. Luokittelu- ja muutostulkintatuloksia verrattiin niiden laadun arvioimiseksi ajantasaiseen kartta-aineistoon tai referenssipisteisiin. Ilmalaserkeilausaineisto ja digitaalinen ilmakuva-aineisto yhdessä antoivat lupaavia tuloksia maastotietojen kartoitusta ajatellen. Automaattisessa rakennusten tulkinnassa 96 % kaikista yli 60 m2:n rakennuksista tunnistettiin oikein. Tämä tarkkuustaso (96 %) vastaa käytännön laatuvaatimuksia. Automaattisessa muutostulkinnassa noin 80 % kaikista referenssirakennuksista luokiteltiin oikein. Maanpeiteluokittelussa neljään luokkaan saavutettiin laserkeilaus- ja ilmakuva-aineistoa käyttäen 97 %:n kokonaistarkkuus referenssipisteisiin verrattuna. Pelkkää ilmakuva-aineistoa käytettäessä tarkkuus oli 74 %. Tutkimuksessa verrattiin myös ensimmäiseen ja viimeiseen paluupulssiin perustuvia laserkeilausaineistoja rakennusten tulkinnassa. Vertailu osoitti, että viimeisen paluupulssin käyttö ensimmäisen sijasta voi parantaa tulkintatuloksia. Automaattisten tulkintamenetelmien tuloksista voisi olla hyötyä maastotietojen manuaalisessa ajantasaistusprosessissa tai lähtötietoina kohteiden automaattisessa rajauksessa ja mallinnuksessa. Tutkimuksessa käytettyjen synteettisen apertuurin tutkan (SAR) tuottamien kuvien ja optisen satelliittikuvan tärkeimmät hyödyntämismahdollisuudet liittyvät maanpeitteen kartoitukseen. Yleispiirteisessä maankäyttöluokittelussa kolmeen luokkaan saavutettiin moniaikaista interferometrista SAR-aineistoa käyttäen 97 %:n kokonaistarkkuus referenssipisteisiin verrattuna. Aineisto osoittautui lupaavaksi myös rakennettujen alueiden jatkoluokitteluun rakennustiheyden perusteella. Jatkotutkimusten kannalta tärkeitä aiheita ovat edistyneemmät tulkintamenetelmät, uudet ja moniaikaiset aineistot, eri aineistojen optimaalinen yhdistäminen sekä useampien kohteiden ja luokkien tarkastelu. Käytännön näkökulmasta työtä tarvitaan automaattisten tulkintamenetelmien sovittamiseksi operatiivisiin kartoitusprosesseihin. Myös menetelmien testausta on jatkettava

Stolen Heritage Multidisciplinary Perspectives on Illicit Trafficking of Cultural Heritage in the EU and the MENA Region

It is a well-known fact that organised crime has developed into an international network including very diverse actors – ranging from the simple ‘grave diggers’ to powerful and wealthy white-collar professionals – that adopt illegal practices like money laundering, fraud and forgery. This criminal system, ultimately, damages and disintegrates our cultural identity and, in some cases, fosters political corruption, terrorism or civil unrest through the transnational and illicit trafficking of cultural property. The forms of ‘ownership’ of Cultural Heritage are often indistinct, and – depending on the national legislation of reference – the proprietorship and trade of historical and artistic assets of value may be legitimate or not. Casual collectors and criminals have always taken advantage from these ambiguities and managed to place on the market items obtained by destruction and looting of museums, monuments and archaeological areas. Thus, over the years, even the most renowned museum institutions might have - more or less consciously – displayed, hosted or lent cultural objects of illicit origin. Ransacking, thefts, clandestine exports and disputable transactions are crimes that primarily affect countries that are rich in artistic and archaeological assets, but such activities do not involve just some countries. This is an international border-crossing phenomenon that starts in given countries and expands to many others. Some are briefly passed through while a handful of powerful and rich ones are the actual destination marketplaces. Drawing from the experience of the conference Stolen Heritage (Venice, December 2019), held in the framework of the H2020 NETCHER (NETwork and digital platform for Cultural Heritage Enhancing and Rebuilding) project, this edited volume focuses on illicit trafficking in cultural property addressing the issue from a multidisciplinary perspective and featuring papers authored by international experts and professionals actively involved in Cultural Heritage protection. The articles included expand on such diverse topics as the European legislation regulating import, export, trade and restitution of cultural objects; ‘conflict antiquities’ and cultural heritage at risk in the Near and Middle East; looting activities and illicit excavations in Italy; the use of technologies to counter looting practices and the publication of unprovenanced items. This collection is meant as a valuable resource to disseminate new results of the research as well as to facilitate a better understanding of the international legislation related to the protection of Cultural Heritage

Oil spill and ship detection using high resolution polarimetric X-band SAR data

Among illegal human activities, marine pollution and target detection are the key concern of Maritime Security and Safety. This thesis deals with oil spill and ship detection using high resolution X-band polarimetric SAR (PolSAR). Polarimetry aims at analysing the polarization state of a wave field, in order to obtain physical information from the observed object. In this dissertation PolSAR techniques are suggested as improvement of the current State-of-the-Art of SAR marine pollution and target detection, by examining in depth Near Real Time suitability

Semantic Labelling of Globally Distributed Urban and Non-Urban Satellite Images Using High Resolution SAR Data

While the analysis and understanding of multispectral (i.e., optical) remote sensing images has made considerable progress during the last decades, the automated analysis of SAR (Synthetic Aperture Radar) satellite images still needs some innovative techniques to support non-expert users in the handling and interpretation of these big and complex data. In this paper, we present a survey of existing multispectral and SAR land cover image datasets. To this end, we demonstrate how an advanced SAR image analysis system can be designed, implemented, and verified that is capable of generating semantically annotated classification results (e.g., maps) as well as local and regional statistical analytics such as graphical charts. The initial classification is made based on Gabor features and followed by class assignments (labelling). This is followed by the inclusion. This can be accomplished by the inclusion of expert knowledge via active learning with selected examples, and the extraction of additional knowledge from public databases to refine the classification results. Then, based on the generated semantics, we can create new topic models, find typical country-specific phenomena and distributions, visualize them interactively, and present significant examples including confusion matrices. This semi-automated and flexible methodology allows several annotation strategies, the inclusion of dedicated analytics procedures, and can generate broad as well as detailed semantic (multi-)labels for all continents, and statistics or models for selected countries and cities. Here, we employ knowledge graphs and exploit ontologies. These components could already be validated successfully. The proposed methodology can also be adapted to other instruments

Remote sensing applied to landslide risk management and governance

The main objective of this doctoral thesis is to analyze the use of remote sensors, the information that can be obtained to determine how these sensors and methodologies can be used to generate and update geospatial information for risk management and governance. To acquire this objective, after an extensive review, it is intended to develop from a purely practical and applied point of view, which are materialized in different case studies. And, applied to projects that are immersed in risk management focused on mass movements in Ecuador. This thesis is conformed of six chapters addressing mass movements from different perspectives objectives and, study areas