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Preliminary Material /Ray Purdy and Denise Leung -- Foreword /Tanja Masson-Zwaan -- Introduction /Ray Purdy and Denise Leung -- Technical Introduction to Satellite EO /Shaida Johnston -- Science, Policy and Evidence in EO /Ray Harris -- The Use of Satellite Imagery in Environmental Crimes Prosecutions in The United States: A Developing Area /Kris Dighe , Todd Mikolop , Raymond W. Mushal and David O'Connell -- The Use of EO Data As Evidence in the Courts of Singapore /Gérardine Goh Escolar -- Ten Years of Using Earth Observation Data in Support of Queensland's Vegetation Management Framework /Bruce Goulevitch -- EO in the European Union: Legal Considerations /Sa'id Mosteshar -- Satellite Data As Evidence in the Courts of Taiwan /Dennis Tsai -- Satellite Evidence in International Institutions /Maureen Williams -- The Use of EO Technologies in Court by the Office of the Prosecutor of the International Criminal Court /Eya David Macauley -- Outer Space Law Principles and Privacy /Frans G. von der Dunk -- Privacy and EO: An Overview of Legal Issues /George Cho -- The Impact of Copyright Protection and Public Sector Information Regulations on the Availability of Remote Sensing Data /Catherine Doldirina -- The Use of Remote Sensing Evidence at Trial in the United States—One State Court Judge's Observations /Merideth Wright -- Satellite Images As Evidence for Environmental Crime in Europe: A Judge's Perspective /Carole M. Billiet -- Authentication of Images /Alan Shipman -- Introducing Digital Signatures and Time-Stamps in the EO Data Processing Chain /Willibald Croi , Fréderic-Michael Foeteler and Harold Linke -- Pulling the Threads Together and Moving Forward /Ray Purdy -- Selected Bibliography /Ray Purdy and Denise Leung -- Index /Ray Purdy and Denise Leung.

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ ; Nowadays, constellations and distributed networks of satellites are emerging as clear development trends in the space system market to enable augmentation, enhancement, and possibilities of new applications for future Earth Observation (EO) missions. While the adoption of these satellite architectures is gaining momentum for the attaining of ever more stringent application requirements and stakeholder needs, the efforts to analyze their benefits and suitability, and to assess their impact for future programmes remains as an open challenge to the EO community. In this context, this paper presents the mission and system architecture conceived during the Horizon 2020 ONION project, a European Union research activity that proposes a systematic approach to the optimization of EO space infrastructures. In particular, ONION addressed the design of complementary assets that progressively supplement current programs and took part in the exploration of needs and implementation of architectures for the Copernicus Space Component for EO. Among several use cases considered, the ONION project focused on proposing system architectures to provide improved revisit time, data latency and image resolution for a demanding application scenario of interest: Marine Weather Forecast (MWF). A set of promising system architectures has been subject of a comprehensive assessment, based on mission analysis expertise and detailed simulation for evaluating several key parameters such as revisit time and data latency of each measurement of interest, on-board memory evolution and power budget of each satellite of the constellation, ground station contacts and inter-satellite links. The architectures are built with several heterogeneous satellite nodes distributed in different orbital planes. Each platform can embark different instrument sets, which provide the required measurements for each use case. A ...

8 pags., 7 figs., 1 tab. ; Determining reflectance factor and its variability across reference sites for Earth observation satellites is a problem involving large amounts of data and measurement time. Principal component analysis (PCA) may be used to simplify this problem by reducing the size of the data and by highlighting spectral features that could be related to physical phenomena. This work presents the results obtained in applying PCA to two reference sites for calibration and validation of Earth observation satellites located at La Crau (France) and Gobabeb (Namibia), respectively. ; To the European Metrology Research Program (EMRP), supporter of this work within the joint research project ENV53 "European metrology for Earth observation and climate" (MetEOC2). The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union. We thank CNES for access to La Crau and their support with the measurements at both La Crau and Gobabeb. The IO-CSIC authors are also grateful to Comunidad de Madrid for funding the program SINFOTON-CM: S2013/MIT-2790

Satellite Earth Observation (EO) is nowadays receiving significant attention. In this regard, the latency of EO products provision to the ground segment is undoubtedly among the first key performance indicators for these systems. Traditionally, small EO satellites rely on the flight segment for raw data acquisition and compression, while the image processing tasks are performed at the ground segment. The latency of raw data transmission prevents such systems from achieving better than Near Real-Time (NRT) delivery of EO products, which are typically available to the end-user after 1h to 3h from acquisition time. The European Union Horizon 2020 EO-ALERT project aims at significantly reducing this latency by moving all the critical processing tasks on the flight segment and accelerating them using high-performance commercial off-the-shelf (COTS) devices. The resulting architecture minimizes the amount of transmitted data and eliminates ground-based data processing from the EO data chain, hence achieving actual real-time product delivery in less than 5min with optical and Synthetic Aperture Radar (SAR) data. The centerpiece of the proposed architecture is the embedded CPU Scheduling, Compression, Encryption, and Data Handling (CS-CEDH) Subsystem, essentially fulfilling two roles: 1) acquire and move images and products among the image processing and communications subsystems, therefore also coordinating their tasks; 2) compress and encrypt the input and output data with different settings depending on the mission requirements. From an optimal design and resource allocation perspective, these aspects are complementary: while the former is software-focused, aiming at maximizing modularity, flexibility, and dynamic scalability, required by the inherent system-level real-time event-driven nature of the CPU Scheduling processes, the latter represents an intrinsically highly-specialized, computationally expensive data-processing function, better suited for hardware implementation. In order to achieve the overall goal of ...

This is a copy of the article published in Sea-Technology Magazine, which the authors have bought the rights to redistribute. ; With an uncertain future that includes climate change, sea level rise and increasing coastal populations, being able to make informed policy decisions in coastal zones will be critical for ensuring the well-being of citizens, the environment and the sustainability of economic activities. Earth observation (EO) can be used to efficiently and systematically provide the key information needed to make these decisions. However, getting access to the right EO in- formation can be a complicated and costly business, limiting availability. However, the launch in April 2014 of the first Sentinel satellite from Europe's flagship EO program, Copernicus, represents a major advance in the availability of EO data, which has great potential to benefit numerous sectors involved in marine and coastal activities. We discuss some examples of applications being developed and give an example of a new service which intends to support nature-based flood defense schemes. ; The research leading to these results has received funding from the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement n° 607131. All views presented are those of the authors. The EU is not liable for any use that may be made of the information contained herein. ; PDF, 5 pages, 20.4 Mb

Earth observation (EO) is a prerequisite for sustainable land use management, and the open-data Landsat mission is at the forefront of this development. However, increasing data volumes have led to a "digital-divide", and consequently, it is key to develop methods that account for the most data-intensive processing steps, then used for the generation and provision of analysis-ready, standardized, higher-level (Level 2 and Level 3) baseline products for enhanced uptake in environmental monitoring systems. Accordingly, the overarching research task of this dissertation was to develop such a framework with a special emphasis on the yet under-researched drylands of Southern Africa. A fully automatic and memory-resident radiometric preprocessing streamline (Level 2) was implemented. The method was applied to the complete Angolan, Zambian, Zimbabwean, Botswanan, and Namibian Landsat record, amounting 58,731 images with a total data volume of nearly 15 TB. Cloud/shadow detection capabilities were improved for drylands. An integrated correction of atmospheric, topographic and bidirectional effects was implemented, based on radiative theory with corrections for multiple scatterings, and adjacency effects, as well as including a multilayered toolset for estimating aerosol optical depth over persistent dark targets or by falling back on a spatio-temporal climatology. Topographic and bidirectional effects were reduced with a semi-empirical C-correction and a global set of correction parameters, respectively. Gridding and reprojection were already included to facilitate easy and efficient further processing. The selection of phenologically similar observations is a key monitoring requirement for multi-temporal analyses, and hence, the generation of Level 3 products that realize phenological normalization on the pixel-level was pursued. As a prerequisite, coarse resolution Land Surface Phenology (LSP) was derived in a first step, then spatially refined by fusing it with a small number of Level 2 images. For this purpose, a novel data fusion technique was developed, wherein a focal filter based approach employs multi-scale and source prediction proxies. Phenologically normalized composites (Level 3) were generated by coupling the target day (i.e. the main compositing criterion) to the input LSP. The approach was demonstrated by generating peak, end and minimum of season composites, and by comparing these with static composites (fixed target day). It was shown that the phenological normalization accounts for terrain- and land cover class-induced LSP differences, and the use of Level 2 inputs enables a wide range of monitoring options, among them the detection of within state processes like forest degradation. In summary, the developed preprocessing framework is capable of generating several analysis-ready baseline EO satellite products. These datasets can be used for regional case studies, but may also be directly integrated into more operational monitoring systems " e.g. in support of the Reducing Emissions from Deforestation and Forest Degradation (REDD) incentive. In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Trier University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. ; Erdbeobachtung ist eine Grundvoraussetzung für nachhaltiges Landnutzungsmanagement. Hierbei kommt der Landsat Mission, nicht zuletzt wegen ihrer freien Datenpolitik, eine zentrale Rolle zu. Der hiermit verbundene starke Anstieg von verfügbaren Datenmengen hat allerdings zu einer "digitalen Kluft" geführt. Somit ist es von höchster Wichtigkeit, Methodenentwicklung voranzutreiben um die rechenintensivsten Vorverarbeitungsschritte zu automatisieren. Die damit verbundene Generierung von Analyse-fertigen, standardisierten, höherwertigen (Level 2 und Level 3) Satellitenbildbasisprodukten erhöht wiederum das operationelle Potential von Umweltüberwachungssystemen. Die übergreifende Forschungsaufgabe dieser Dissertation war die Entwicklung eines solchen Systems mit speziellem Fokus auf den noch untererforschten Trockengebieten des südlichen Afrikas. Eine vollautomatische und Speicher-residente radiometrische Vorverarbeitungskette (Level 2) wurde entwickelt, implementiert, und auf das gesamte Landsat-Archiv von Angola, Sambia, Simbabwe, Botswana und Namibia angewendet. Dies entspricht 58.731 Bildern und einem Gesamtdatenvolumen von ca. 15 TB. Eine Verbesserung der Wolken- und Wolkenschattendetektion wurde für Trockengebiete vorgenommen. Eine integrierte Korrektur für atmosphärische, topographische und bidirektionelle Effekte wurde auf Grundlage von Strahlungstransfertheorie inklusive Berücksichtigung von Mehrfachstreuungen und Nachbarschaftseffekten implementiert. Des Weiteren wurde ein mehrstufiges Verfahren zur Schätzung der Aerosol optischen Dicke über persistenten dunklen Objekten beziehungsweise der Rückgriff auf eine räumich-zeitlich variable Aerosolklimatologie entwickelt. Topographische und bidirektionelle Effekte wurden jeweils mit einer semi-empirischen C-Korrektur und einem globalen Korrekturparameterset reduziert. Anschließend wurde eine Kachelung und Reprojizierung vorgenommen, um die effiziente Weiterverarbeitung der Daten zu vereinfachen. Die Auswahl von phänologisch ähnlichen Beobachtungen ist eine wichtige Voraussetzung für Analysen im Bereich der Umweltüberwachung, und somit wurde ein Level 3 Produktgenerierungssystem entwickelt, das eine phänologische Normalisierung auf Pixelebene realisiert. Um dies zu erreichen, wurde zunächst ein räumlich grob aufgelöster Phänologiedatensatz erzeugt, dessen räumliche Auflösung anschließend unter Hinzunahme einiger weniger Level 2 Produkte verbessert wurde. Hierfür wurde auf Basis von mehrskaliger Information unterschiedlicher Datenquellen ein Datenfusionsansatz entwickelt. Phänologisch normalisierte Bildkomposite (Level 3) wurden schließlich erzeugt, indem der Zieltag (wichtigstes Auswahlkriterium) mit dem erzeugten Phänologiedatensatz gekoppelt wurde. Zur Demonstration des Ansatzes wurden Komposite zum Maximum, Ende und Minimum der Vegetationsperiode erzeugt, und mit einer statischen Variante verglichen (festgelegter Zieltag). Es konnte gezeigt werden, dass die phänologische Normalisierung Höhen- und Landnutzungsbedingte Unterschiede in der Vegetationsentwicklung ausgleichen kann. Außerdem hat sich gezeigt, dass die Nutzung der Level 2 Daten eine Vielzahl an Umweltüberwachungsoptionen bietet, unter anderem die Detektion gradueller Landschaftsveränderungen. In Zusammenfassung wurde eine Vorprozessierungskette entwickelt, die in der Lage ist mehrere grundlegende Analyse-fertige Erdbeobachtungs-Satellitenbildprodukte zu generieren. Diese Datensätze können nun für regionale Fallstudien, aber auch für die direkte Integration in operationellere Umweltüberwachungssysteme, wie z.B. im "Reducing Emissions from Deforestation and Forest Degradation" (REDD) Programm verwendet werden. In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Trier University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.

The growing number of planned Earth Observation (EO) satellites, together with the increase in payload resolution and swath, brings to the fore the generation of unprecedented volumes of data that need to be downloaded, processed and distributed with low latency. This creates a severe bottleneck problem, which overloads operations and ground infrastructure, communications to ground, and hampers the provision of EO products to the End User with the required performances. The EO-ALERT project (http://eo-alert-h2020.eu/), an H2020 European Union research activity led by DEIMOS Space, proposes the definition of next-generation EO missions by developing an on-board high-speed EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite. EO-ALERT achieves, globally, latencies below 5 minutesfor EO products delivery, achieving latencies below 1 minute in some scenarios. Considering the innovative on-board processing chain implemented in the EO-ALERT project, the end users consider that the corresponding technology advances can enable very competitive and effective applications in the latency of sensitive scenarios, such as maritime surveillance and disaster management, especially to cope with extreme weather eventsand the expected needs to detect, monitor and mitigate the effects of climate change. These application scenarios require a high responsiveness to events, reducing the response time to a few hours, or even to minutes, after an emergency situation arises. This paper presents the definition of the user requirements for the EO-ALERT EO data processing chain, based on the identified market needs and application scenarios, a high-level mission analysis and concept of operations for the identified scenarios and lastly the experimental campaign carried out in July 2020 to collect validation data. The European EO missions that have been selected to develop and test the on-board data processing chain and ...

The political history of U.S. commercial remote sensing began in 1984 when the U.S. government first attempted to commercialize its civil earth observation satellite system " Landsat. Since then, the high technology of earth imaging satellite systems has generated intense debates and policy conflicts, primarily centered on U.S. government concerns over the national security and foreign policy implications of high-resolution commercial satellite systems. Conversely, proponents of commercial observation satellites have urged U.S. policymakers to recognize the scientific and socio-economic utility of commercial remote sensing and thus craft and implement regulatory regimes that allow for a greater degree of information openness and transparency in using earth observation satellite imagery. This dissertation traces and analyzes that tumultuous political history and examines the policy issues and social construction of commercial remote sensing to determine the role of knowledge in the effective crafting and execution of commercial remote sensing laws and policies. Although individual and organizational perspectives, interests, missions, and cultures play a significant role in the social construction of commercial observation satellite systems and programs, the problem of insufficient knowledge of the myriad dimensions and complex nature of commercial remote sensing is a little studied but important component of this social construction process. Knowledge gaps concerning commercial remote sensing extend to various dimensions of the subject matter, such as the global, economic, technical, and legal/policy aspects. Numerous examples of knowledge voids are examined to suggest a connection between deficient knowledge and divergent policy perceptions as they relate to commercial remote sensing. Relevant knowledge voids are then structurally categorized to demonstrate the vastness and complexity of commercial remote sensing policy issues and to offer recommendations on how to fill such knowledge gaps to effect increased collaboration between the US government and the U.S. commercial remote sensing industry. Finally, the dissertation offers suggestions for future STS studies on policy issues, particularly those that focus on the global dimensions of commercial remote sensing or on applying the knowledge gap concept advanced by this dissertation to other areas of science and technology policymaking. ; Ph. D.

Offering a balanced review of differing approaches based on remote sensing methods to monitor ecosystem services related to biodiversity conservation, carbon and water cycles, and the energy balance of the terrestrial ecosystem, this book identifies the relevant issues and challenges of assessment, presents cutting-edge sensing techniques, uses globally implemented tools to quantify ecosystem functions, and provides numerous examples of successful monitoring programs. Covering recent developments undertaken on the global and national stage from earth observation satellite data, it includes

Terrestrial ecosystems provide a variety of benefits for human life and production, and are a key link for achieving sustainable development goals (SDGs). The basin ecosystem is one type of terrestrial ecosystem. Ecological security (ES) assessments are an important component of the overall strategy to achieve regional sustainable development. The Huaihe River Basin (HRB) has the common characteristics of most basins, such as high population density, a rapidly developing economy, and many environmental problems. This study constructed an ES evaluation system by applying a pressure-state-response framework as an assessment method for the sustainable development of basins. Taking the HRB as an example, this study determined the ES status of the region from 2001 to 2019 and analyzed crucial factors for any variation observed by combining remote sensing and climate data, relevant policies, and spatial information technology. The results highlight the importance of reserves and the negative impact of urban expansion on ES. Additionally, the enactment of policies had a positive impact on ES, whereas precipitation had a negative effect on ES in most areas of the HRB. Based on these results, the government should strengthen the protection of forests, grasslands, and wetlands and improve water conservation facilities. This study provides guidance for the subsequent economic development, environmental protection, and the achievements of SDG 15 in the HRB.