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The creation of Smart Cities is an emerging research and application field that has the objective to increase city resilience and improve the quality of life for citizens. In this paper an extensive and thorough gap analysis that was performed in the framework of the SMURBS1 project is presented. The gap analysis identified 117 gaps in the legal, methodological, and technological framework, in the thematic areas of air quality, disasters, urban growth and migration. The identified gaps can be used by policy makers in local, regional, national, or even at EU or UN level to form new policies that will bridge these gaps and lead to the creation of resilient and sustainable smart cities.

Over the course of the 21st century, a century in which the urbanization process of the previous one is ever on the rise, the novel smart city concept has rapidly evolved and now encompasses the broader aspect of sustainability. Concurrently, there has been a sea change in the domain of Earth observation (EO) where scientific and technological breakthroughs are accompanied by a paradigm shift in the provision of open and free data. While the urban and EO communities share the end goal of achieving sustainability, cities still lack an understanding of the value EO can bring in this direction, an next a consolidated framework for tapping the full potential of EO and integrating it in their operational modus operandi. The “SMart URBan Solutions for air quality, disasters and city growth” H2020 project (SMURBS/ERA-PLANET) sits at this scientific and policy crossroad, and, by creating bottom-up EO-driven solutions against an array of environmental urban pressures, and by expanding the network of engaged and exemplary smart cities that push the state-of-the-art in EO uptake, brings the international ongoing discussion of EO for sustainable cities closer to home and contributes in this discussion. This paper advocates for EO as an integral part of a smart and sustainable city and aspires to lead by example. To this end, it documents the project's impacts, ranging from the grander policy fields to an evolving portfolio of smart urban solutions and everyday city operations, as well as the cornerstones for successful EO integration. Drawing a parallel with the utilization of EO in supporting several aspects of the 2030 Agenda for Sustainable Development, it aspires to be a point of reference for upcoming endeavors of city stakeholders and the EO community alike, to tread together, beyond traditional monitoring or urban planning, and to lay the foundations for urban sustainability.

UNESCO and the United Nations have recently identified cultural heritage (CH) as a key enabler of sustainability by incorporating it into several Sustainable Development Goals (SDGs). Accurate and efficient reporting on CH is considered fundamental despite known limitations due to the lack of sufficient and harmonized data. This paper presents a spatially enabled web application for urban CH monitoring for the city of Thessaloniki in Northern Greece. The objective was to integrate the information provided by several independent public registries on CH into a common 2D mapping and reporting platform and to enrich it with additional data provided by other built environment agencies. An estimation of the expected cost for the structural evaluation by experts of the city’s CH assets was also implemented for SDG’s Indicator 11.4.1. The methodology involved stakeholder identification, data collection and pre-processing, field verification and documentation, calculation of Indicator 11.4.1, and the actual coding process. The application can be found online, providing useful insights and statistical information on the city’s heritage in a dashboard format. The key challenges included the lack of updated data, the existence of several individual registries, and the need for regular field inspection due to the rapidly changing urban fabric.

The purpose of this study is the photogrammetric survey of a forested area using unmanned aerial vehicles (UAV), and the estimation of the digital terrain model (DTM) of the area, based on the photogrammetrically produced digital surface model (DSM). Furthermore, through the classification of the height difference between a DSM and a DTM, a vegetation height model is estimated, and a vegetation type map is produced. Finally, the generated DTM was used in a hydrological analysis study to determine its suitability compared to the usage of the DSM. The selected study area was the forest of Seih-Sou (Thessaloniki). The DTM extraction methodology applies classification and filtering of point clouds, and aims to produce a surface model including only terrain points (DTM). The method yielded a DTM that functioned satisfactorily as a basis for the hydrological analysis. Also, by classifying the DSM–DTM difference, a vegetation height model was generated. For the photogrammetric survey, 495 aerial images were used, taken by a UAV from a height of ∼200 m. A total of 44 ground control points were measured with an accuracy of 5 cm. The accuracy of the aerial triangulation was approximately 13 cm. The produced dense point cloud, counted 146 593 725 points.

Here we show and discuss the first results arising from the SAVEMEDCOASTS-2 Project (Sea Level Rise Scenarios along the Mediterranean Coasts - 2, funded by the European Commission ECHO), which aims to respond to the need for people and assets prevention from natural disasters in the Mediterranean coastal zones placed at less than 1 m above sea level, which are vulnerable to the combined effect of sea-level rise and land subsidence.We use geodetic data from global navigation satellite system (GNSS), synthetic aperture radar interferometric measurements (InSAR), Lidar and tide gauge data, and the latest IPCC - SROCC projections of sea-level rise released by the Intergovernmental Panel on Climate Change, to estimate the Relative Sea Level Rise to realize marine flooding scenarios expected for 2100 AD in six targeted areas of the Mediterranean region.We focus on the Ebro (Spain), Rhone (France), and Nile (Egypt) river deltas; the reclamation area of Basento (Italy), the coastal plain of Thessaloniki (Greece), and the Venice lagoon (Italy). Results, from Copernicus Sentinel-1A (S1A) and Sentinel-1B (S1B) sensors, highlighted the variable spatial rates of land subsidence up to some cm/yr in most of the investigated areas representing a relevant driver of local SLR. All the investigated zones show valuable coastal infrastructures and natural reserves where SLR and land subsidence are exacerbating coastal retreat, land flooding, and storm surges.The hazard implications for the population living along the shore should push land planners and decision-makers to take into account scenarios similar to that reported in this study for cognizant coastal management.

&Alpha, bstract: To date, countless satellite image fusions have been made, mainly with panchromatic spatial resolution to a multispectral image ratio of 1/4, fewer fusions with lower ratios, and relatively recently fusions with much higher spatial resolution ratios have been published. Apart from this, there is a small number of publications studying the fusion of aerial photographs with satellite images, with the year of image acquisition varying and the dates of acquisition not mentioned. In addition, in these publications, either no quantitative controls are performed on the composite images produced, or the aerial photographs are recent and colorful and only the RGB bands of the satellite images are used for data fusion purposes. The objective of this paper is the study of the addition of multispectral information from satellite images to black and white aerial photographs of the 80s decade (1980&ndash, 1990) with small difference (just a few days) in their image acquisition date, the same year and season. Quantitative tests are performed in two case studies and the results are encouraging, as the accuracy of the classification of the features and objects of the Earth&rsquo, s surface is improved and the automatic digital extraction of their form and shape from the archived aerial photographs is now allowed. This opens up a new field of use for the black and white aerial photographs and archived multispectral satellite images of the same period in a variety of applications, such as the temporal changes of cities, forests and archaeological sites.

New techniques and methodological procedures, which would allow at a short time and at low cost for the identification of a new archaeological sites, were always in the interest of archaeologists. In addition, fast and accurate 3D modelling and documentation techniques were also always a hot research topic because they can help archeologists to document active excavation sites fast, thus helping them to advance the excavation in a timely manner. In this chapter, aerial and remote sensing archaeology issues will be analyzed, both as measuring tools for the documentation of existing archaeological structures as well as tools of archaeology prospection, which are based on the appearance of the reflection of covered structures in images (i.e., the so-called marks).

The focus of this chapter is the contribution of remote sensing (RS) technologies in climate risk mainly for archaeological landscapes and built heritage. It will study the use of RS technologies for sea level rise scenario risk assessment and the use of multi-temporal multisource data and statistical indices for the detection of changes in built heritage. This chapter is divided in two sections: the first one focuses on sea level rise and potential threats, while the second one focuses on monitoring of temporal changes in built heritage using multisource multi-temporal data and indices.

New techniques and methodological procedures, which would allow at a short time and at low cost for the identification of a new archaeological site, were always in the interest of archaeologists. In this paper, aerial and remote sensing archaeology issues will be analyzed, both as measuring tools for the documentation of existing archaeological structures as well as tools of archaeology prospection, which are based on the appearance of the reflection of covered structures in images, i.e. the so-called marks.

Three dimensional modelling of artefacts and building interiors is a highly active research field in our days. Several techniques are being utilized to perform such a task, spanning from traditional surveying techniques and photogrammetry to structured light scanners, laser scanners and so on. New technological advancements in both hardware and software create new recording techniques, tools and approaches. In this paper we present a new recording and modelling approach based on the SwissRanger SR4000 range camera coupled with a Canon 400D dSLR camera. The hardware component of our approach consists of a fixed base, which encloses the range and SLR cameras. The two sensors are fully calibrated and registered to each other thus we were able to produce colorized point clouds acquired from the range camera. In this paper we present the initial design and calibration of the system along with experimental data regarding the accuracy of the proposed approach. We are also providing results regarding the modelling of interior spaces and artefacts accompanied with accuracy tests from other modelling approaches based on photogrammetry and laser scanning.

Global climate changes are a main factor of risk for infrastructures and people living along the coasts around the world. In this context, sea level rise, coastal retreat and storm surges pose serious threats to coastal zones. In order to assess the expected coastal changes for the next decades, a detailed knowledge of the site’s topography (coastline position, DTM, bathymetry) is needed. This paper focuses on the use of very high resolution satellite data and UAV imagery for the generation of accurate very-high and ultra-high mapping of coastal areas. In addition, the use of very high resolution multi-spectral satellite data is investigated for the generation of coastal bathymetry maps. The paper presents a study for the island of Lipari and the coasts of Cinque Terre (Italy) and the island of Lefkas (Greece). For Lefkas, two areas of the island were mapped (the city of Lefkas and its adjoining lagoon in the north side of the island, and the Bay of Vasiliki at the south part of the island) using World View 1, and Wolrd View 3 satellite images, and UAV imagery. The satellite processing provided results that demonstrated an accuracy of approximately 0.25 m plannimetrically and 0.70 m vertically. The processing of the UAV imagery resulted in the generation of DTMs and orthophotos with an accuracy of approximately 0.03-0.04 meters. In addition, for the Vasiliki bay in the south of the island the World View 3 imagery was used for the estimation of a bathymetry map of the bay. The achieved results yielded an accuracy of 0.4 m. For the sites of Lipari and Cinque Terre (both in Italy), UAV surveys allowed to extract a DTM at about 2 cm of pixel resolution. The integration of topographic data with high resolution multibeam bathymetry and expected sea level rise from IPCC AR5 2.6 and 8.5 climatic scenarios, will be used to map sea level rise scenarios for 2050 and 2100, taking into account the Vertical Land Motion (VLM) as estimated from CGPS data. The above-mentioned study was realized during the implementation of the SAVEMEDCOASTS project (Sea level rise scenarios along the Mediterranean coasts, funded by the European Commission ECHO A.5, GA ECHO/SUB/2016/742473/PREV16, www.savemedcoasts.eu).

Remote sensing facilitates the extraction of information for earth’s surface through its capability of acquiring images covering large areas and the availability of commercial software for their processing. The aim of this study is the feature extraction from three Geoeye-1 stereo pairs for forested area. The study area is located in central mountainous forested peninsula of Chalkidiki, in northern Greece. Dominant forest tree species of the site are oak (Quercus conferta), beech (Fagus moesiaca), black pine (Pinus nigra) and calabrian pine (Pinus brutia). Very High Resolution (VHR) Geoeye-1 stereo pair satellite images were utilized in panchromatic and multispectral mode. The panchromatic mode was employed for Digital Surface Model (DSM) generation and its evaluation. In this study the High Pass Filter (HPF) data fusion technique was applied between panchromatic and multispectral mode for acquiring a new image with the benefits of both contracting images. Because of the fact that the feature extraction was attempted in a forested region, NDVI index and Tasseled Cap transformation were applied in the fused images’ evaluation procedure. Optical assessment was also applied. The accuracy of the generated DSM and the evaluation results of the fused images were remarkable.

Within the field of forestry, forest road mapping and inventory plays an important role in management activities related to wood harvesting industry, sentiment and water run-off modelling, biodiversity distribution and ecological connectivity, recreation activities, future planning of forest road networks and wildfire protection and fire-fighting. Especially in countries of the Mediterranean Rim, knowledge at regional and national scales regarding the distribution and the characteristics of rural and forest road network is essential in order to ensure an effective emergency management and rapid response of the fire-fighting mechanism. Yet, the absence of accurate and updated geodatabases and the drawbacks related to the use of traditional cartographic methods arising from the forest environment settings, and the cost and efforts needed, as thousands of meters need to be surveyed per site, trigger the need for new data sources and innovative mapping approaches. Monitoring the condition of unpaved forest roads with unmanned aerial vehicle technology is an attractive option for substituting objective, laboursome surveys. Although photogrammetric processing of UAV imagery can achieve accuracy of 1-2 centimeters and dense point clouds, the process is commonly based on the establishment of control points. In the case of forest road networks, which are linear features, there is a need for a great number of control points. Our aim is to evaluate low-cost UAV orthoimages generated over forest areas with GCP’s captured from existing national scale aerial orthoimagery, satellite imagery available through a web mapping service (WMS), field surveys using Mobile Mapping System and GNSS receiver. We also explored the direct georeferencing potential through the GNSS onboard the low cost UAV. The results suggest that the GNSS approach proved to most accurate, while the positional accuracy derived using the WMS and the aerial orthoimagery datasets deemed satisfactory for the specific task at hand. The direct georeferencing procedure seems to be insufficient unless an onboard GNSS with improved specifications or Real-Time Kinematic (RTK) capabilities is used.

The study refers to the visual representation of the coastal front of the historical center of Thessaloniki in northern Greece and its changes that have occurred through the years. Most of the old town was destroyed by fire on August 18, 1917. A few years later, the French architect and archeologist Ernest Hebrard proposed the reconstruction of the city centre, but his plans were never fully implemented. Since then, a series of interventions changed the form of the old town and consequently the coastal cityscape. The research was initially based on the photogrammetric processing of archive aerial images (1938) of Thessaloniki's city centre. Besides the vertical images, high oblique aerial images dated back to 1932, proved to be a significant source of information. A rich archive of old photographic material, sketches, drawings and gravures of the coastal forehead of the city was also used. Ortho-images of the coastal front, derived from laser scanning (2010), and a 3D model of the historical city center, derived from the stereo photogrammetric process of aerial images (1990), contributed decisively at the multi temporal study of the city front. The main outcomes of the present documentation study are the 3D representation (at scale of 1:200, accuracy 5 cm) of temporal changes of a part of the coastal front of the historical center of Thessaloniki and the 2D representation (at scale 1:100, accuracy 1–2 cm) of these changes with respect to variations on skyline, lacunas, interventions in old buildings, etc.

There is a continuous and increasing demand for solutions, both software and hardware-based, that are able to productively handle underground utilities geospatial data. Innovative approaches that are based on the use of the European GNSS, Galileo and EGNOS, sensor technologies and LBS, are able to monitor, document and manage utility infrastructures’ data with an intuitive 3D augmented visualisation and navigation/positioning technology. A software and hardware-based system called LARA, currently under develop- ment through a H2020 co-funded project, aims at meeting that demand. The concept of LARA is to integrate the different innovative components of existing technologies in order to design and develop an integrated navigation/positioning and information system which coordinates GNSS, AR, 3D GIS and geodatabases on a mobile platform for monitoring, documenting and managing utility infrastruc- tures on-site. The LARA system will guide utility field workers to locate the working area by helping them see beneath the ground, rendering the complexity of the 3D models of the underground grid such as water, gas and electricity. The capacity and benefits of LARA are scheduled to be tested in two case studies located in Greece and the United Kingdom with various underground utilities. The paper aspires to present the first results from this initiative. The project leading to this application has received funding from the European GNSS Agency under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 641460.

In this paper, we address the orientation of ground-level motion imagery captured by sensors roaming in an urban area. We investigate the use of building facades (instead of traditional points), as matching features for ground-level motion imagery orientation. We assume a situation where few images in our sequence are already absolutely oriented, and present a novel approach to orient all remaining inbetween image sequences relative to them. This innovative version of dependent orientation allows us to propagate orientation information within sequences of ground level imagery, establishing a novel orientation scheme. Experimental results show accuracies on the order of 0.18 to 0.29 degrees in rotation estimation, and 0.17 to 0.29 meters in camera position determination.

Balkan countries do not have a coherent and continuous approach towards the challenge of implementing integrated Earth Observation (EO) applications in environmental monitoring and management. Most of the Balkan countries, except Greece, are not full ESA members. Additionally, Albania, Serbia, Bulgaria, FYROM, Montenegro and Bosnia Herzegovina are also not members of the Group on Earth Observation (GEO). The OBSERVE Research Programme, funded under the theme "ENV.2010.4.1.4-1, Identification and Networking of EO activities in the Balkan area" and with a full title "Strengthening and Development of Earth Observation Activities for the Environment in the Balkan Area," has as its main objectives to collect and compile all the necessary information for delivering an integrated analysis on the current status of EO activities and networks in the Balkans regarding environmental monitoring, and to determine the potential benefit from the full exploitation of an integrated capacity development strategy and the prospect of creating a relevant permanent EO Community in the broader region. One of the most important activities to accomplish the above mentioned objectives is the collection and compilation of the National Thematic Reports concerning EO capacities delivered by the separate Balkan participants in the Project.

[EN] The concept of marginal land (ML) is dynamic and depends on various factors related to the environment, climate, scale, culture, and economic sector. The current methods for identifying ML are diverse, they employ multiple parameters and variables derived from land use and land cover, and mostly reflect specific management purposes. A methodological approach for the identification of marginal lands using remote sensing and ancillary data products and validated on samples from four European countries (i.e., Germany, Spain, Greece, and Poland) is presented in this paper. The methodology proposed combines land use and land cover data sets as excluding indicators (forest, croplands, protected areas, impervious areas, land-use change, water bodies, and permanent snow areas) and environmental constraints information as marginality indicators: (i) physical soil properties, in terms of slope gradient, erosion, soil depth, soil texture, percentage of coarse soil texture fragments, etc.; (ii) climatic factors e.g. aridity index; (iii) chemical soil properties, including soil pH, cation exchange capacity, contaminants, and toxicity, among others. This provides a common vision of marginality that integrates a multidisciplinary approach. To determine the ML, we first analyzed the excluding indicators used to delimit the areas with defined land use. Then, thresholds were determined for each marginality indicator through which the land productivity progressively decreases. Finally, the marginality indicator layers were combined in Google Earth Engine. The result was categorized into 3 levels of productivity of ML: high productivity, low productivity, and potentially unsuitable land. The results obtained indicate that the percentage of marginal land per country is 11.64% in Germany, 19.96% in Spain, 18.76% in Greece, and 7.18% in Poland. The overall accuracies obtained per country were 60.61% for Germany, 88.87% for Spain, 71.52% for Greece, and 90.97% for Poland., [ES] El concepto de tierra marginal (ML) es dinámico y depende de factores relacionados con el entorno, el clima, la escala, la cultura y la economía. los métodos actuales de identificación de ML son también diversos y están basados en múltiples parámetros y variables derivados del uso y cobertura del suelo reflejando, en su mayoría, fines de gestión específicos. En este artículo se presenta una propuesta metodológica para la identificación de tierras marginales mediante el uso de productos derivados de teledetección y datos auxiliares, validándose sobre muestras obtenidas en cuatro países europeos: Alemania, España, Grecia y Polonia. La metodología combina datos de usos y coberturas del suelo como indicadores excluyentes (bosque, tierras de cultivo, áreas protegidas, áreas impermeables, cambios de usos del suelo, cuerpos de agua y áreas de nieve permanente) e información ambiental como indicadores de marginalidad, esto es, (i) propiedades físicas del suelo como la pendiente, profundidad de suelo, erosión del suelo, textura, porcentaje de fragmentos de textura gruesa del suelo, etc.; (ii) factores climáticos como el índice de aridez; (iii) propiedades químicas del suelo como pH, capacidad de intercambio catiónico, contaminantes y toxicidad, entre otros, con el objetivo de abordar una visión común de la marginalidad que integre un enfoque multidisciplinar. Para obtener las coberturas de ML primero se analizaron los indicadores excluyentes para delimitar las áreas con un uso del suelo establecido. En segundo lugar, se determinaron los umbrales para cada indicador de marginalidad a través de los cuales el suelo se transforma, disminuyendo progresivamente su aprovechamiento productivo. Finalmente, la superposición de las capas de indicadores de marginalidad se llevó a cabo con la herramienta Google Earth Engine. El resultado final se categorizó en 3 niveles de ML con diferente productividad: alta, baja y tierras potencialmente inadecuadas. Los resultados obtenidos indican que el porcentaje de tierras marginales sobre la extensión total de cada país analizado es de 11,64% en Alemania, 19,96% en España, 18,76% en Grecia y 7,18% en Polonia. La precisión global obtenida por país fue del 60,61% para Alemania, del 88,87% para España, del 71,52% para Grecia y del 90,97% para Polonia., This research has been funded by the European Commission through the H2020-MSCA-RISE-2018 MAIL project (grant 823805) and by the Fondo de Garantía Juvenil en I+D+i from the Spanish Ministry of Labour and Social Economy.