This PDF file contains the front matter associated with SPIE Proceedings Volume 11524, including the Title Page, Copyright information, and Table of Contents

The concept of digitalization of agricultural production in the Russian Federation provides for the implementation of measures to develop and create a system of geographic information monitoring and decision support in crop production. The aim of the research was to conduct geoinformation monitoring of rice crops to develop methods for automated mapping of their condition and yield forecasting. The studies were carried out on a test site of the Federal State Budget Scientific Institution "Federal Scientific Center of Rice" with an area of 327 hectares. The main cultivated crop is the Flagman rice variety. The survey was performed by a quadcopter with a MicaSense RedEdge-M multispectral camera mounted on a fixed suspension. The shooting period using an unmanned aerial vehicle (UAV) was limited to early June and additionally used the Sentinel-2A satellite data covering the entire analyzed period (06/05/2019 - 08/29/2019). To assess the state of rice crops, the normalized relative vegetative index NDVI was used. Based on the NDVI distribution and yield information from the combine TUCANO 580 (CLAAS), a statistical analysis was carried out in fields 7 and 9 All-Russian Research Institute of Rice (“VNII Rice”). Testing of the experimental methodology for monitoring crops in 2019 on the basis of remote sensing of test plots and geoinformation modeling and the statistical apparatus should be considered satisfactory.

Productivity of maize (Zea mays L.) is strongly regulated by the availability of water. There are critical stages of crop development, in which water deficit could have a detrimental effect on crop functioning and yield. Facing the challenges related to climate changes and rapidly depleting water resources, it is of utmost importance for agriculture, biologically optimal water status of different crops, at different stages of ontogeny to be determined. In order to achieve this aim, it is necessary a continuous monitoring of crops and assessment of their functioning during each of the growth stages and in different environmental conditions to be conducted. Remote sensing (RS) methods enable valuable information about crop functioning to be obtained. In the present study remotely sensed spectral vegetation indices and orthogonalization of multispectral satellite data are used, in order changes related to phenological dynamics and biomass accumulation to be studied. The suggested methodology facilitates identification of the timing of phenological transitions that are related to maize physiological development. The research evaluates the dynamics of maize phenological development in the environmental conditions of growing season 2019, using multispectral imagery, acquired by Sentinel-2 sensor of the European Space Agency Program for Earth Observation “Copernicus” and daily measured field climatic data.

The Common Agricultural Policy, and specifically the part referring to Cross Compliance (CC) is the main tool with which the European Union promotes and enforces environmentally sound practices in agriculture. CC requirements however are extremely complex. Additionally, on-the-spot checks (inspections), the main tool for checking compliance, report ex post facto, are expensive and difficult to perform due to their low level of controllability and verifiability. This paper presents results from the work that has been carried out under RE.CAP (EU Horizon 2020 Research and Innovation Programme Grant Agreement No. 693171). The project aimed at: a) simplifying CC rules, b) facilitating compliance of the farmers with the CC rules and c) reducing the burden of checking cross-compliance while at the same time increasing the controllability and verifiability level of the inspections, through remote sensing, self assessment and acting ex-ante. The novelty of this work is that it presents how remote sensing results are incorporated in a real-world system in a form of a pilot that covered a major part of Thessaly (Greece), including 140 farmers and more than 80 agro-consultants. The remote-sensing algorithms used mainly Sentinel-2 images, and provided accurate crop classification for all five major crops that make up 85% of the Greek agricultural land. The presentation will show: a) the RE.CAP system and how remote sensing algorithms were incorporated in it, b) how inspections validated the results, c) The results of the satisfaction survey and d) real-data estimation of the administrative burden reduction due to RE.CAP. Overall, the work presented here shows for the first time that an integrated solution combining farmers and inspector participation through self-assessment and remote sensing using Sentinel-2 open data can practically be employed and used to carry out environmental monitoring and protection on a national level.

Evapotranspiration (ET) constitutes a meteorological and hydrogeological parameter which plays a critical role to climate, crop irrigation and water management (aquifer and surface water supplies). The scarcity of ground-based data along with the call for regional and global scale research, led to the emergence of remote sensing methods and products. Thus, algorithms and adaptations of the empirical methods have been developed to incorporate satellite data or a combination of satellite and meteorological data. The current study reviews popular models, namely, surface energy balance (SEB) algorithms (i.e. SEBAL, S-SEBAL, SEBAL-Tasumi, SEBS, T-SEB, S-SEBI, SSEBop, ASEBAL, METRIC), models based on vegetation and soil moisture indices (e.g. EVI, NDVI, LAI, GVMI) such as NDVI-CWS and modifications of established ET equations such as Penman-Monteith, Priestley-Taylor, Hargreaves-Samani, Granger, Carlson and Buffum, Droogers-Allen, REMCT incorporating satellite data. The aforementioned models come with their limitations in ET estimation depending on parameters such as scale, landuse/landcover (LU/LC) of the study area, quality of meteorological and satellite data, spatiotemporal resolution of satellite products, number of inputs and usability. Uncertainties occur when coarse MODIS-retrieved data inputs are incorporated. In Greece few research attempts employing satellite data for ET estimation are numbered, the majority of which of field scale or local scale over Thessaly. Future research could implement interpolation of measurements derived from a wide number of meteorological stations distributed over the study area at regional scale. Moreover, comparisons of ET estimations to pan evaporation measurements are recommended, aiming at obtaining more sophisticated, area-tailored models and quantifiable physical relations.

The use of express methods for assessing of soil degradation degree is a global trend. Numerous studies suggest the possibility of using spectrometric methods for determination of chemical compounds in the soil. In this work, an attempt is made to determine the agrochemical parameters by spectrometric methods for agricultural soils of the subboreal zone of the east of the European Plain. The main types of spectrograms for gray forest soils and leached chernozems were determined and compared with the results of agrochemical analyzes at soil sampling points. The main regularities in indicators change depending on spectrometric curves type are analyzed. The results of the work can be claimed for express determination of agricultural soils degradation degree for a given natural zone.

Effective and efficient control of the agrarian obligations imposed by the Common Agricultural Policy (CAP) and the high-level decision making for national and global food security, requires systematic and timely monitoring of the agricultural land. In this study we focus on rice paddy monitoring in South Korea to ultimately deliver food security related information. Food security monitoring demands knowledge at large scales to allow for decision making at the highest level. In this work, we monitor the growth of rice using the TIMESAT solution on a time-series of Normalized Difference Vegetation Index (NDVI), extracting useful metrics with reference to the phenological phases of the crop, but also biomass and yield indicators. TIMESAT requires user provided parameters to define the start and the end of season to then compute the relevant metrics. In order to automate this procedure, the vegetation indices Normalized Difference Water Index (NDWI) and Plant Senescence Reflectance Index (PSRI) are used to develop a data based parameter tuning for TIMESAT.

In the field of Cultural Heritage preservation and enhancement, detecting objects quickly and inexpensively, with the possibility of repeating measurements several times for monitoring any deterioration, has become an increasingly significant requirement. The existence of a conspicuous historical heritage across the Italian territory often forces local authorities to orient their survey strategies towards the research of the most economic, but still efficient, solutions. Due to these reasons, also in consideration of possible emergency situations, it is necessary to find the optimal solution to allow a timely and comprehensive detection of exhaustive 3D digital object reconstructions. An important task is therefore to test the potential accuracies of recent measurement technologies and procedures in order to produce high quality results. This study analyzes the generation of three-dimensional reconstructions of Torre Zozzoli, an historic fortified tower located 25 km from Taranto (Apulia region, Italy), through two close-range detection techniques, by comparing Terrestrial Laser Scanner (TLS) and Unmanned Aerial Vehicles (UAVs) photogrammetric imagery. To arrange and improve the methodologies of ground control point measurements, two survey techniques were implemented by means of a Total Station (TS) and a GNSS receiver in nRTK mode. Lastly, using the cloud-to-cloud (C2C) comparison tools and implementing three distributions of GCPs, UAVs and TLS points clouds were compared. Considering their accessibility in terms of costs and use, photogrammetric products from UAVs, represent a valid alternative to TLS-based 3D data in multi-temporal analysis.

This work is a part of the research aimed at developing a system of analysis of the risks of destruction of archaeological sites on the territory of the Republic of Tatarstan. Most of fortified settlements of the Volga-Bulgarian period (X-XIII centuries AD) are located on the small river banks. In order to identify the risk of archaeological sites transformation by fluvial processes, the river dynamics in the area of Lukovskoye, Bolsheklyarinskoye and Zelenovskoye fortified settlements was assessed. Field studies were conducted using UAV and GNSS techniques to describe the relief and current state of the site’s territory. The measured data were analyzed using the GIS to evaluate intensity of bank erosion. Historical maps, archival remote sensing data and orthophotomaps compared to get quantitative characteristics of monument territory damage. In addition, as a result of photogrammetric image processing, the DEM of monuments territory were constructed and analyzed. As a result, maps of the river dynamics and quantitative characteristics of the intensity of the site’s destruction were obtained. The main factors affecting bank erosion are the meandering of the riverbed, the height of the bank and its component rocks. The study showed the importance of using remote sensing and 3D-modelling methods to study and predict the dynamics of river processes as a factor in the destruction of archaeological sites. Results of the research will help to reveal tendencies in cultural heritage objects condition and to estimate risks of their destruction.

Rapid technological development, as well as the great interest in the three-dimensional (3D) digitization of cultural heritage had resulted in the research project “Ecclesiastical Cultural Heritage Digitization Pilots for the Churches of Cyprus and Crete.” The main objective is to document churches using a variety of non-invasive techniques to generate 3D models of the church for the management and promotion of cultural heritage sites, such as churches. In this paper, the integration of various technologies was used to document the 17th century Church of Αgios Athanasios and Kyrillos in Agios Athansios in Cyprus. Technologies such as spectroscopy, laser scanning, multispectral and RGB imaging and photogrammetry were used to obtain a high-quality 3D-metric model for documentation. The implemented techniques on the 3D-models assist in qualifying pathologies in the cultural heritage site. Through the use of spectroscopy and multispectral imaging, the authors attempt to qualify the pathologies at church using a proposed Lithology Condition Index (LCI). The implrinting of the monument was run through an “INTERREG V-A Greece-Cyprus 2014-2020” project namely “Ecclesiastical Cultural Heritage Digitization Pilots for the Churches of Cyprus and Crete” while the methodology was developed within the framework of the EXCELSIOR project.

Islands are the most important tourist destinations in Greece because in addition to natural beauty they offer a rare combination of tourist products and services. In many cases, however, the natural environment is transformed as an unjustified receiver of pollutants produced by tourism activities, which could be possible, degraded the environment and disturb the ecological balance. This fact activated an original research effort to study whether the potential ecological and environmental distortions in the island were to be identified so that a tourism policy could be adapted to the island's natural environment. During the data collection, tourist accommodation was recorded in all Lefkada's municipalities by additional data collection of natural, cultural, human and artificial environment. The resulting data were further processed with software programs and showed that the geological specificity of Lefkada's island affects the spatial arrangement and distribution of local and seasonal tourist populations. As an impact of this, the potential zones of pressure in Lefkada are separated into coastal outer zone and two inner, semi-mountainous zones. The coastal zone receives the highest pressure and has the highest potential for pollution, mainly on the north and east sides of the island, due to the existence of ports and natural anchors and the explosive development of small and multi-purpose tourist accommodation within 2 Km of the coastline. Semi-mountainous areas that may be prone to land use problems have also been surveyed due to the growing tourism spatial activity. Higher altitudes show a continuing trend of improving alternative forms of tourism, but the potential for pollution is limited but this does not mean that the ecological balance cannot be disturbed.

The RESEARCH project (Remote Sensing techniques for Archaeology; H2020-MSCA-RISE, 2018-2022, grant agreement: 823987) addresses the design and development of a multi-task platform, combining advanced remote sensing technologies with Geographical Information System (GIS) application for mapping and long-term monitoring of Archaeological Heritage (AH) at risk, to identify changes due to climate change and anthropic pressures. The Earth Observation (EO) processing chain will address significant risks affecting AH including soil erosion, land movement and land-use change. The paper describes one of the main goals of RESEARCH project. It refers to a state of the art analysis of Synthetic Aperture Radar (SAR) methods applied to the land movement detection such as landslide and subsidence. Satellite SAR is a rapidly evolving remote sensing technology that offers a high potential for detecting, documenting and monitoring heritage targets. Satellite SAR interferometry (InSAR), Differential Interferometry (DinSAR) and Persistent Scatterer Interferometry (PSI) are different techniques that, depending on the available data and the required accuracy, can be used for deformation monitoring of AH.

European cultural heritage (CH) is at risk, threatened by environmental processes strengthened by climate change and anthropogenic pressure. In particular, the slow (landslides, subsidence) and seismic (earthquakes) movements of the soil have a strong impact on the structural stability of our cultural heritage (CH). The actions to be carried out to protect and safeguard CH are in continuous development and this is where the STABLE (STructural stABiLity risk assEssment) project fits. STABLE concerns the design and development of a thematic platform, which combines structural stability models, simulation and damage assessment tools, advanced remote sensing, in situ monitoring technologies, geotechnical and cadastral data sets with the WebGIS application for mapping and long-term monitoring of the CH. The thematic platform, which is the final objective of the project, will therefore support the authorities responsible for the conservation of cultural heritage in the design and implementation of policies for monitoring, preserving and safeguarding our heritage. This will allow effective monitoring and management of CH to prevent or at least reduce the possible irreparable damages. STABLE will coordinate existing skills and research in a synergistic plan of collaborations and staff exchanges to offer a complete transfer of knowledge and training to researchers in the specific area under study. The development of the platform will be the strategy that scientists will have to follow to share and improve CH safeguard methods. It will serve professionals to apply the most advanced technologies in their fields.

The authors aim to present the collecting of in-situ spectral data for filling in a thematic database of Earth observation as a part of joint project. In-situ spectrometric measurements were made for acquiring spectral data of the rock samples during and after a field campaign in the selected test site. The selected test points are around the town of Novi Iskar where space test site “Novi Iskar” is established. The related land covers in the studied area will also be taken into account in the analysis of satellite images of the region. These in-situ measurements are part of an integrated system for remote sensing and ground-based observations and in line with Copernicus In-Situ Component. In-situ spectrometric measurements have potential for long-term practical application to verify data, which increases their accuracy. Filling in the thematic database for monitoring over test site with the collecting spectral and ancillary data leads to an optimal correlation between the different methods of studying the different types of land covers, increases the effectiveness of scientific investigations in the field of Earth remote sensing, creates synergy between different scientific fields and helps to share information between researchers from different areas of scientific and practical interest. The team is developing a data base structure which is going to be available through SRTI-BAS website. The data base is going to include information about specific spectral properties of the studied objects in the test site. This work is supported by “National Science Fund” in Bulgaria under Contract number KP-06-M27/2.

Lignite mining in Greece has been a huge industry. Especially, in the extraction site of Western Macedonia many villages were relocated due to the site's spatial growth. Public Power Corporation (PPC) SA Ptolemaida lignite mine is the biggest in Balkans that contributes significantly to country's electricity production. This paper aims at formulating a methodological procedure in order to delineate rapidly the lignite coal mine boundaries through an object based image analysis, in Orfeo ToolBox and QGIS. Site boundaries can be modified through expansion of mining activities or unexpectedly due to a natural disaster. For that reason, a Sentinel-2A imagery was obtained and three frequent segmentation approaches were applied including MeanShift, Watershed and Morphological profiles, from a notable remote sensing open source package (Orfeo Toolbox). Following various tests, the optimal parameters for each segmentation algorithm are presented alongside with the corresponding results regarding lignite mine area boundaries delineation. In addition, the proposed methodological framework may apply to different environmental subjects monitoring including large constructions, mineral extraction, landfills and archaeological sites.

The general idea of the study is to emphasize the necessity of Interim Ecological Monitoring application based on remote sensing tools for effective monitoring on water bodies used to supply drinking water to urban areas. The aim of the study is to identify the changes in the water surface of the “Studena dam” for a period of three years (2018-2020) and in different seasons. The investigation is made based on Sentinel 1 and Sentinel 2 (MSI optical) data for different time intervals. Orthogonalization of Sentinel 2 data has been applied. Correlation between the obtained data from Sentinel 1 and Sentinel 2 has been defined. The results have been verified by additional data generated by analyzing the inflow and outflow in watershed and alluvial outflow based on officially published information by the Ministry of Environment and Water in Bulgaria (e.g. monthly schedules for water usage from dams with great importance for Republic of Bulgaria, calculations, etc.) and the influence of climate factors (precipitation and temperature). The final results from IEM application based on remote sensing data could be applied to generate tendency for changes in dam water volume in different time periods and gives opportunity for decision-makers to undertake preventive actions or effective actions in case of a water crisis.

The problem with application of exact biooptical models of PROSPECT and PROSAIL type for description of green vegetation reflectance (GVR) spectra is the necessity for a special supportive study to investigate the influence of rather specific biophysical and computational input parameters on resulting spectra. To simplify this task for designers of cyber-physical systems, we have constructed an empirical easy-to-use approximate compact model for GVR spectrum in wavelength range 400-900 nm. Based on measured spectra and PROSPECT-D simulations, a maximally compact model with 5 setup points at significant wavelength values has been formulated. After further normalization via assigning the unit value to the chlorophyll-caused 670 nm minimum, only 4 easily understood tuning parameters will define the GVR spectrum with a satisfactory accuracy. The Fermi-Dirac like step functions and Gaussian bell functions are used as building blocks to describe the most important spectrum features: flat or slanted ground level, green apex, red 700 nm step and infrared plateau. For fitting of the common 9 wavelength-related parameters and of the 4 sample-dependent amplitude parameters, the 7 datasets measured by hyperspectral camera and compact spectrograph were used. The constructed model may be employed as an easy-to-use simplified submodel in the development of larger cyber-physical systems for civil and military applications where identification or hiding of artificial objects in the presence of natural background is needed. For the rough estimation tasks the offered model can yield approximate GVR spectrum with only 2 parameters defined (relative heights of red step and green apex).

The importance of monitoring soil properties is constantly increasing among researchers and policy-makers. In this context, it is imperative to identify cost effective and reliable strategies for soil mapping compared to the costlier traditional solutions. A wide range of tools are becoming available that enable better utilization of Earth Observation capabilities to monitor the soil ecosystem. This work is an effort of assessing the potential of Sentinel-2 imagery data for mapping Soil Organic Matter (SOM) contents and investigating the possibilities of its enhancement through ASTER derived information. The rural area around the lake Zazari, located in the Western Macedonia district of Greece, was chosen as study area. Initially, pixel-wise vegetation indices (NDVI and NBR2) were calculated, utilizing a local version of the CEOS Open Data Cube for masking Sentinel-2 bare soil pixels extending a three-year period (2017–2019). The generated mask was used to extract soil spectral signatures at the image level over selected 100 field samples. The resulting time series was expanded through the conjunction of ASTER Thermal InfraRed bands by matching the exact data acquisition dates of two platforms. The conclusive part of the work contains the application of regression modelling to effectively assess soil variables. The local Partial Least Square regression algorithm was chosen, due to its characteristics of performing inherently local predictions. Five-fold cross-validation technique was used for reporting the models’ accuracy, which was assessed through R 2 coefficient, RPIQ ratio and RMSE. The model estimated SOM values among a synthetic bare soil composite image that was acquired over study area’s agricultural fields. Two models were trained and compared; one over Sentinel-2 imagery bands that were used as the predictor variables’ set and a second over an expanded predictor variables’ set, including ASTER thermal bands. The results signified evidence of accuracy increase of SOM content assessment, through spaceborne imagery analysis.

Sea ice plays a major role in our planet’s climate. It’ acts as a reflector of solar energy, mainly in spring and summer. Sea ice covered with fresh snow can reflect 75-90% of solar energy, the open sea reflects just 5-15%. Sea ice acts as an insulator in autumn and winter. This insulating effect limits the amount of both heat and moisture the ocean loses to the atmosphere. The declining sea ice disrupts the climate, societies and fauna of Polar areas, but encourages the econcmic and industrial development. The relevance of this study is related to current trends in the use of remote sensing in solving problems of a different nature in environmental monitoring. The sea ice was analyzed and mapped according to the European Space Agency data (ESA), acquired by sensors of Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel- 2MSI (Multi Spectral Instrument), Sentinel- 3 and GIS. The subject of the study is to demonstrate the dynamics, during the summer season from 2015 to 2019, around the coastline of Livingston Island, New Shetland Islands in Antarctica and Longyearbyen in the Arctic. Changes in environmental objects are indicated by radar images through different processing approaches. The results clearly show that sea ice melting can be best recorded by using SAR data through the C-band. The results obtained are data in the form of thematic maps showing the spatial reflectance of sea ice and its dynamics over time.

Cloud contamination represents a large obstacle for mapping the earth’s surface using remotely sensed data. Therefore, cloudy pixels should be identified and eliminated before any further data processing can be achieved. Although several threshold, multi-temporal and machine learning applications have been developed to tackle this issue, it still remains a challenge. The main challenges are imposed by the difficulty to detect thin clouds and to separate bright clouds from bright non-cloud objects. Convolutional neural networks (CNNs) have proven to be one of the most promising methods for image classification tasks and their use is rapidly increasing in remote sensing problems. CNNs present interesting properties for image processing since they directly exploit not only the spectral information but also the spatial covariance of the data. In this work, we study the applicability of CNNs in cloud detection of Sentinel-2 imagery, a complex remote sensing problem with crucial spatial context. A patch-to-pixel CNN architecture consisting of three convolutional layers and two fully connected layers is trained on a recently available manually created public dataset. The results were evaluated both qualitatively and quantitatively through comparison with ground truth cloud masks and state-of-the art pixel-based algorithms (Fmask, Sen2Cor). It was shown that the proposed architecture even though simpler than the deep learning architectures proposed by recent literature, performs very favorably, especially in the challenging cases. Besides the evaluation of the results, feature maps where observed as an initial effort to extract the weights of the useful kernels for cloud masking applications.

Marine Spatial Planning (MSP) is a key tool in managing the interaction of activities in the coastal and marine environment. It analyzes and allocates human activities to achieve the ecological, economic, and social goals established through a political process. Under this project, data was collected for various activities such as tourism, aquaculture, fisheries, renewable energy, ship routes, etc. This study focuses on the data referring to ship detection. Ship routes in Cyprus EEZ were created using position signals of ships in the EEZ for a temporal resolution of 15 minutes. These signals are compared to the positions of these ships using the radar backscatter derived from Sentinel-1A and Sentinel1B satellite images, which have a temporal resolution of 6 days. The radar backscatter for a certain period calculated using the Google Earth Engine platform, was then compared to the ship signals provided. This research is supported by the project entitled “Cross border Cooperation for Implementation of Marine Spatial Planning referred as THAL-CHOR 2” and is Co-funded by the European Regional Development Fund (ERDF) and by national funds of Greece and Cyprus under the Cooperation Programme Interreg V-A Greece-Cyprus 2014-2020.

The ERATOSTHENES Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment (ECoE) that will be established through the EXCELSIOR project will provide cutting-edge Earth Observation (EO) research in Cyprus, the Eastern Mediterranean, Middle East and North Africa (EMMENA) region, Europe and Internationally for the benefit of the environment and society. The ECoE will focus on the thematic clusters of Environment and Climate, Resilient Society and Big Earth Data Analytics and conduct research and develop applications within the focus areas of climate change monitoring, disaster risk reduction, access to energy, water resources management and big EO data analytics. The ECoE can serve as an innovation gateway for Cyprus and EMMENA in the areas of Earth observation and remote sensing, thereby providing applications and services for issues that are unique to the EMMENA region. The success indicators to measure the ECoE’s sustainability are also discussed.

Over the years, passive and active reflectors are becoming indispensable parts in ground deformation monitoring using Interferometric SAR geodetic techniques. The evolution and the need for more practical and compact in size reflectors motivated the implementation of Electronic Corner Reflectors, namely ECR Transponders. ECR Transponders are compact active permanent scatterers, which are used in the estimation of physical or man-induced deformation processes. Their main advantage lies their compact size and the fact that a sole unit accounts for both ascending and descending tracks, instead of having two opposite-facing ordinary Corner Reflectors configuration. To date, ECR transponders mainly operate in C-band and, thus, are compatible with Sentinel-1 and Radarsat. Although experiments are in initial stage, the results seem quite promising with respect to the classic passive corner reflectors in many sectors. In this paper, an analysis of the ECR-C band transponders is carried out, along with a worldwide overview and a comparison of their results in various application sectors using different satellite radar missions and techniques.

Detailed resource or impact assessment studies often call for higher spatial resolution data products. Remote sensing data e.g., SAR (Synthetic Aperture Radar) provide high spatial resolution wind information but suffer from the satellite’s relatively poor revisit time. This paper focuses on the preliminary assessment of offshore wind speed derived from diverse data sources, characterized by different spatial and temporal resolution. A univariate statistical analysis and a match-up comparison between in-situ Cyprus meteorological stations wind speed measurements and Sentinel-1A and 1B VV-polarized SAR wind field estimates were conducted for a two-year period between 1st June, 2017-1st June, 2019. Results indicate that SAR data overestimate the in-situ measurements resulting in an average bias of 0.7 m/s, which was gradually increasing in parallel to the wind speed values. Errors also proved to vary spatially with Akrotiri demonstrating the highest average errors comparing to Pafos and Larnaca. Despite the discrepancies found, Sentinel-1 SAR Level-2 OCN can be considered as a reliable source for offshore wind field estimation. The initial assessment presented in this paper can be considered as the basis for a future in-depth analysis of Cyprus offshore wind resource assessment.

The changes observed in forest line, have recently drawn much interest, in part because forest line altitude may be used as an indicator of environmental changes. Forest line ecotone located in the zone between closed forest and to treeless herbaceous vegetation, are transitional areas are widely used as indicators for the observation of landscape response to climate change. The objective of this study was to evaluate the changes in time of the forest line at six mountains in mainland Greece from 1945 to2019. Aerial, remotesensing data acquired in 1945 and 2007 were processed for information extraction through a visual interpretation approach. Subsequently, the 2007 forest line and canopy cover maps served as reference for developing a modelling procedure based on freely satellite data and extrapolate the forest line predictions over 2019. Spectral and texture predictor variables were extracted from Landsat 5 imagery captured in summer 2007 and used as input to Random Forest models. All models for the various scenes resulted a coefficient of determination of more than 0.6 for tree canopy cover density estimation. The developed RF models for tree canopy cover estimation were applied to Landsat-8 surface reflectance scenes covering the respective geographical extent. Finally, the forest line and tree canopy cover maps, were overlaid within a GIS environment and changes were detected. The change detection procedure revealed both an upslope shift of the forest line as well as an increase in the tree canopy cover in these areas. From these changes, significant implications for ecosystem functioning and ecosystem services provision are likely to occur.

Forests ecosystems are extremely vulnerable to the changes of climatic parameters such as quantity and seasonal distribution of precipitations, temperature variation, heat transfer, soil moisture content and others. The consequences of forest vegetation alterations include growth and productivity failures, insect outbreaks, biodiversity changes, and increase in the incidence of forest fires and floods. Remote sensing has been identified as an effective tool for better understanding how forest ecosystems respond to dynamics of climatic parameters and their impact to forest vegetation state in terms of the occurrence of hazard events. In the present study spectral indices like Normalized difference greenness indices (NDGI), Normalized Difference Vegetation Index (NDVI), Improved Modified Chlorophyll Adsorption Ratio Index (MCARI₂), Moisture Stress Index (MSI), and Normalized Difference Water Index (NDWI), derived trough remote sensing methods have been applied for monitoring of the forest state before and after fire event occurred on 29 July 2016. Using a model based on the three major Tasseled Cap components, a Disturbance Index (DI) for the affected forest ecosystem was quantified. The study area is situated in southeastern Bulgaria – a region, highly vulnerable to forest disturbances due to climate changes. The results obtained after the application of the suggested indices show that changes observed in the forest ecosystem state could be assessed with a high accuracy. These results were confirmed with statistical analyses with high correlation coefficients for greenness component and Normalized Difference Vegetation Index (NDVI).

Humanity is associated with the environment throughout all stages of mankind evolution. Ongoing processes occurring with forest resources are being investigated on the territory of Kazakhstan. In order to quickly obtain information on the state of forests, it is necessary to organize a multi-level monitoring system based on integration of ground-based data and remote observations using innovative capabilities of geographic information technologies. This article discusses issues related to the semi-automatic thematic processing of forest resources of the Republic of Kazakhstan based on GIS using Earth remote sensing data. In order to increase productivity the model has been created in the specialized ArcGIS software. Using the satellite remote sensing data set, the model enables semi-automatic processing for detection of forest areas that have undergone changes, in particular, forest logging, burned areas, etc. The studies were carried out on a scientific basis using image analysis methods, spatial data analysis of remote sensing, the latest achievements in the field of modern GIS technologies.

Digital Elevation Models (DEMs) have become a widely used tool and product in the last 20 years. They provide a snapshot of the landscape and landscape features while also providing elevation values. They have allowed us to better visualize and interrogate topographic features. A landscape feature is a road and the location of the road is the “foundation” of any road. A road constructed in a poor location can fail and cause serious environmental damage, as well as add financial strain from continuous and costly maintenance problems. The forest managers know that forest roads must be inspected regularly and maintained as necessary to minimize erosion of the road surface, otherwise, they will require costly repairs. Forest roads represent a significant investment by forest owners and as such, this investment must be preserved. Nowadays forest managers expect the field survey also use DEM and orthophotos datasets to better understand the condition of the road network and to set maintenance and upgrade priorities. In this study, we validate several DEMs and we compare them to the measurements of a detailed road surveying with geodesic GPS. The aim is to use DEMs to spot troubles in the forest road network and relieve the forest owner from the cost of periodic field survey of the forest roads.

Assessment of potential risk of land degradation, especially after fire events, is essential for identifying and prioritizing sites for post-fire management. This study aimed to model potential post-fire land degradation risk in Lebanon in order to plan and prioritize post-fire management actions. The specific objectives were to 1) map “burn severity” of the year 2019 using Landsat 8 and Sentinel 2-A imagery and 2) model post-fire land degradation risk using a Geographic ObjectBased Image Analysis (GEOBIA) approach. Initially, mapping burned areas of the 2019 fire season involved the use of a differenced Normalized Burn Ratio (dNBR) of Sentinel 2-A imagery. Another dNBR image was produced with the use of Landsat 8 imagery. Mapping overall burn severity was conducted based on cross-mapping between the two dNBR images which involved data sources of different spatial and spectral characteristics. Potential post-fire degradation risk was modelled in GEOBIA with the combined use of burn severity and topographic data (i.e., slope gradients). In addition, field data was collected to produce a Composite Burn Index (CBI) of fire-affected sites. The correlation between field data (i.e., CBI scores) and imagery analysis (i.e., dNBR data from Sentinel 2-A and Landsat 8) was assessed using a Spearman correlation test. The combined use of satellite remote sensing images (i.e., polygons of postfire degradation risk) and their corresponding ancillary data (i.e., CBI and soil texture) allowed the prioritization of fire affected sites for implementing post-fire restoration measures.

Forest opening-up is one of the most important interventions in a forest ecosystem and is carried out by planning and constructing of a transport network (forest roads, skidding tracks, etc.), satisfying not only the need for skidding and transporting of forest products, but also forest protection and recreation activities. The primary concern of a forest engineer should be the compatibility of such infrastructural projects with the environment. For this reason, the assessment criteria for forest infrastructural works are used to examine and evaluate the impact on the natural environment of such projects, as well as to choose the best (compatible) environmental solution from various alternatives before undertaking the project. In the present effort describes the initial steps of a simple Decision Support System that could be applied for the assessment of the activity’s intensity and the forest ecosystem’s absorbing capacity using multicriteria analysis. The system embodies three multi-criteria analysis methods and can be used for a single-project analysis as well as for the evaluation of multiple/alternative opening-up projects. A combination of digital photogrammetry and GIS technology was used to evaluate the compatibility between the general forest infrastructural works and the natural environment. In order to evaluate the compatibility, practical criteria of the intensity of the human influence, as well as criteria of the environment resilience to such interventions were used (Multi-criteria evaluation analysis).

Integrated sustainable development of mountainous regions has as objective to increase the economic investments to profit of residents of region, without however it influences drastic the natural environment. Green Infrastructure (GI) can be broadly defined as a strategically planned network of high quality natural and semi-natural areas with other environmental features, which is designed and managed to deliver a wide range of ecosystem services and protect biodiversity. More specifically GI, being a spatial structure providing benefits from nature to people, aims to enhance nature’s ability to deliver multiple valuable ecosystem goods and services in perpetuity, such as timber, clean air or water. Above all, GI offers us a smart, integrated way of managing and development the natural capital. Aim of the paper is to indicate manners of integrated sustainable development with direct priority the conservation of natural environment in conjunction with the sustainable rural development. As research area is chosen the public forest complex of Ano Rou Mornou of Fokida Prefecture a typical example of a multifunctional GI one that can combine forestry, farming, housing, as well as tourism and recreational activities in the same space whilst at the same time keeping our freshwater systems clean, our air healthy and our wildlife safe. Advantages of registration in the form of a spatial tool, especially when many types of information participate, are presented and give us a visual potential of how can forest operation and ecosystem services can be create a large multi-functional landscape.

The term sustainable development indicates a policy for continued economic and social development without destroying the environment and natural resources, but instead ensures their rational viability. The Treaty on European Union is defined as “respecting the environment development”, i.e. one that “ensures the environmental viability”. Sustainable development of semi mountainous forest regions supports an increase in economic investments in order to profit the residents of region, without however having drastic negative influences on the natural environment. Green Infrastructure (GI) can be broadly defined as a strategically planned network of high quality natural and semi-natural areas with other environmental features, which is designed and managed to deliver a wide range of ecosystem services and protect biodiversity. The objective of this study is the specification of strategic directions for an integrated development of semi mountainous forest areas through global measures in relation to zoning policies and proposals regarding specialized production activities, according to a proper typology that characterizes the differentiation of regional problems, needs, and perspectives. The sustainable development of these areas of Greece targets regional and social cohesion in the framework of especial strategic targets. Any development plan addresses the specific development physiognomy of the region for which drawn. Particularly for vulnerable and sensitive semi mountainous forest areas, integrated development is not only necessary but also feasible. The integration capabilities of modern methods and techniques and GIS to establish the necessary infrastructure integrated measurement and qualitative information on such areas can be a very important tool for developing credible land.

Sustainable management of forest resources can only be achieved through a well-organized road network. Road upgrading is a major forest engineering task on an existing road to ensure it is capable of timber harvest or forest fire protection. The purpose of this operation is to bring a currently substandard road up to full standard. Forest road managers considering the technical, economic, and environmental factors that affect forest road not only when they plan forest roads but also when they are going to upgrade them. This paper describes the methodology of decision making when you have limited resources to upgrade the forest road network and you have to prioritize the forest roads that are going to be upgraded. In a Mediterranean island, the timber harvest is not a reason to upgrade a forest road but the fire protection and the growth of tourists that visits a forest ecosystem is. When technical and economic factors are identical the prioritization of forest road upgrade is based on the environmental factors and to the environmental impact assessment (EIA) of each forest road that needs an upgrade. With this work, we suggest that the forest road managers should consider upgrading the forest network based on environmental prioritization in areas with the same characteristics.

Forest roads are necessary to provide access to the forest for general management, maintenance, timber extraction and recreation. Forest roads is a costly investment made by the forest owner and the proper design and planning will reduce its maintenance cost. Following economic and environmental considerations, the designer will prepare tentative or provisional road location lines on a map which he will then inspect on the ground. The designer may have to amend the route before a final selection of the chosen location. Except for the road location line, the designer will consider and propose the construction of forest technical work along the road. Usually, the technical works are proposed after the inspection of the ground or after the construction of the forest road, in this study and with the use spatial analysis of high accuracy DEM we find the slopes that need to be stabilized with a retaining wall in a forest road network that is used already. With this methodology, the forest manager can analyse the needs for forest technical works like a retaining wall of all the forest network and after he can go for ground inspection to the specific areas. The forest manager can alter the spatial criteria from the office and run different scenarios with knowing the locations that will need slope stabilization with a retaining wall. With this preliminary spatial analysis, the forest manager will be more accurate to the economic cost of each forest road maintenance without a costly field survey of all the forest network.

Forest roads are mentioned as necessary and functional structures in forest lands which supply access of forestry workers, machines and others for management, afforestation, harvesting, transportation, protection, recreation, hunting activities and wildlife safely and efficiently during the year. Forest roads is a type of low-volume roads (Defined as roads with traffic volumes of no more than 400 vehicles per day, they have enormous impacts on economies, communication, and social interaction). Effective road drainage is crucial to protect the road prism from damage and to keep the road surface stable for the road quality. The quality of the road is very substantial for forestry activities and it has been a major problem for Greek forestry sector. The most effective method for controlling erosion on forest roads is to keep water from accumulating on and running down the road surface. Water should be diverted from the road surface and dispersed into vegetation and ground litter with cross culverts, rolling dips, diversion ditches and water bars. The creation of standards for drainage systems is one of the most important technical developments in forest road construction. Mapping of the locations in the forest road network in which a technician is required to safely drain rainwater. In the present study, sample points of locations were taken using global positioning system (GPS) for the determination of culverts and then remote sensing and GIS were used for a map creation. The goal is to provide a simple road structure of adequate strength to support heavy vehicle traffic and provide drainage structures to pass water at its normal level through the road corridor.

It is noted that Jordan consumes more water than is available from renewable sources. Renewable water supply currently only meets about half of total water consumption. Shortages are caused by unsustainable groundwater extraction, including thousands of illegal private wells. As a result, many communities in Jordan have long experienced tensions over water scarcity even before the arrival of Syrian refugees. With this rapid influx in population, the gap between available water and demand, particularly in the north, has widened significantly. In response, there is available funding to strengthen water management and governance and reduce water losses, especially by focusing on Non-Revenue Water (NRW). Jordan is estimated to have NRW levels of more than 50% in many areas. This is quite alarming given that Jordan is considered to be one of the fourth most arid countries in the world. The condition of the Jordan water distribution system poses a great number of problems like: 1. Very high percentage of water losses, more than 50%. The NRW represents 220 MCM/year of water losses, which is equal to more than $500 million. 2. Strong pressure variations within the system lead to frequent new pipe breaks. 3. Large number of illegal connections. 4. Old water network. It is important to reduce the NRW to improve the efficiency of the water sector and the financial sustainability, and to conserve Jordan’s limited water resources. Revenues will be increased by the reduction of NRW and will generate more returns for water utilities as a result of accurate metering, billing, and revenue collection. In addition, the cost for the operation and maintenance required will be reduced.

In the framework of the HERMES project [1] a network of four buoys/monitoring stations were deployed, three in the Eastern Mediterranean Sea and one in the Black Sea. The monitoring platforms were deployed in the coastal areas in the Northern Aegean Sea (Greece), in the Larnaca bay (Cyprus), in the SE Ionian Sea (Albania) and in the SW Black Sea (Bulgaria). The monitoring stations provide in near real time data for the sea currents, waves, sea level variation, sea temperature and suspended particles. Moreover, numerical modeling tools were implemented for the provision of forecasting data for sea currents, sea temperature, salinity and waves for all the four areas under study of the HERMES project The data management of the in-situ and forecasting data, a dedicated database was developed using MySQL DBMS, which includes 8 tables, two for each monitoring station. The data archive and online data access to the in-situ and forecasting data a dedicated software was developed including a User Interface. The UI allows to select the desirable in-situ data from the selected monitoring station for a given requested time interval. The data are presented as interactive time series plots. Selected data can be downloaded in SDN ODV format. The modules of the HERMES Web GIS were used to generate files with the in-situ time series data in the well known SeaDataCloud and EMODNET Ingestion formats. For the generation of the metadata of the monitoring stations the SDN MIKADO software was used. A similar Web GIS for archiving and providing access to data from monitoring stations was implemented also for the Kacively monitoring station in the northern Black Sea, which operated by MHI-RAS. The development of software for archiving and providing access to Kacively monitoring station was carried out in the framework of the Task No. 0827- 2019-0004 “Coastal researches” of the MHI-RAS.

The present work deals with the systematic field observation, archiving, accessing and visualization of the vegetation land cover data in the abrasive coastal zone of the Krasnodar region in the Black Sea. Particularly, the field observation of the species composition of the higher vascular plants was carried out at the coastal area of the Tuapkhat massif, a cliff of 80-100 meters high. The field observations were divided into 112 sites taking into account the local geomorphologic features. After the analyzes of the obtained data from the field observations of the vascular plants, a dedicated on line Web GIS database was developed. At present, the online database consists of two tables, the first one includes the coordinates of the area covered by the different types of the vegetation plant, their quantities in each area and their statistical characteristics. The second one includes the description of each type of the vegetation plant with their characteristics and the corresponding images of each type of plant. The User Interface (UI) was developed using jQuery and mapBox GL, in order to provide online access to the vegetation plants characteristics in the above areas of interest. The UI allows the user to access and visualize a number of different types of data concerning the land vegetation plant, covering each area under study, i.e. species, family, life form, fruits, relation to moisture, relation to light, relation to substrate, Red Book, photo, etc.

The recent new developments for updating the user interface (UI) of the Black Sea oceanographic database are described in the current work. The developments dedicated to the use of new techniques at the base of WebG, for the visualization of the Black Sea oceanographic data and the online data access functions and features. The updated Black Sea oceanographic database is realized in two parts using the PostgreSQL. The first part of the database, which is responsible for accessing the metadata was designed and developed for interactive transaction processing (OLTP access template). The second part, which is responsible for the in-situ data archiving was developed following the “star” architecture. The latter is typical for the OLAP access template. The selection of the WebGL for the updated Black Sea UI is based on the advantages in using the modern technology for data visualization and analysis. The WebGL provides fast visualization of geographic objects at the user browser using GPU. Therefore, the previous implemented Mapserver for the Black Sea oceanographic GIS has been abandoned in favor of the WebGL. The updated UI of the Black Sea Oceanographic database includes a main menu, providing access to several online friendly user functions. The UI provides access to the data through several filters/criteria, such as the cruise name, date of cruise, ship name, sea area, hydrological and hydrochemical parameters, etc. The selected data are provided in the form of maps, profiles and metadata.

In recent decades integration of GIS platform is the primary for land use change monitoring and forecast it. Among various methods of GIS integration in agricultural or forest studies have a very important role in region such the Republic of Mari El. Land use change can directly transform wide landscapes, impact on the biodiversity and ecoproductivity. Hence, observations and methods needed to quantitatively assessment land cover dynamics that influence the sustainability of forest management. The relevance of the problem is due to the importance of forest disturbances monitoring, tracking of changes and defense from emergency situations. The main objective of this research is to create the maps of land use change of the Republic of Mari El using remote sensing data and geospatial technologies. GISbased map algebra was applied for calculating land use change with the use of integration of remote sensing data. The resulting maps show how different types of land use and land cover parameters have changed. The entire modeling approach support the essential logic of probabilistic indicates of change.

This paper aims at the study of the timeless changes in land use of the area of Anthousa. Its vegetation belongs to the Olea-Ceratonion area and consists mainly of pine forests and brushwood, as well as of cultivated vineyards and moreover of broadleaf, fruitful and ornamental trees. As far as is concerned, the area is a refuge for smaller members of the Mediterranean fauna. It is a growing city, keeping its air clean of pollutants, as it is built at the foot of Mount Pendelikon, in an altitude of 332 meters and 15 kilometers far from Athens center and 2 kilometers far from Pallini. It belongs to the Athens conurbation. The extent of the community amounts to 3.9 km² . In order to investigate the changes that took place over the last decades in the region, the remote sensing method was used in conjunction with Geographic Information Systems (GIS) for the processing of the satellite images, as well as a study of the historical and socioeconomic development of the area. After an analysis of all the natural and anthropogenic factors that contributed to the formation and change of the land use and land cover of the area, useful conclusions were made indicating the degradation of the forest ecosystems and wooded land in transitional forest-bushy areas due to successive fires that have plagued the area, as well as the gradual development of the industrial and residential activity, which has led to an upward population development in the region.

As an innovation research action in the spatial planning and in the social innovation arena for Renewable Energy Landscapes (REL), the Planning And Engagement Arenas For Renewable Energy Landscapes (PEARLS) project will reinforce the population’s commitment to secure, clean and efficient energy. REL focus on the change of the population’s relationship with energy and their landscape perception. Paros, Greek Cycladic island as a “isolated piece of land” was selected to investigate several aspects for REL. Paros has wind parks infrastructure establishments, active and inactive. Also, the administrative authorities are “on hold” in several areas, since the infrastructure is outdated and no studies for noise pollution and “line of sight” viewing have been executed. The 3D monitoring of the established infrastructure and 3D GIS techniques highlight the crucial necessity for studies, before any wind parks establishment. PEARLS project, in general, will bring a step change to the way that REL are addressed and monitored before, during and after their establishment, by providing crucial support for the Pan-European Energy Challenge.

Land cover data derived from satellite images must be accompanied by information on their quality in order to be properly and fully used. The main purpose of this paper is to present the results of the evaluation of the Urban Atlas (UA) and Street Tree Layer (STL) datasets for Bulgaria for the reference 2012 year. This verification task is part of a project, managed by the European Environmental Agency (EEA) under the Copernicus program. A quantitative assessment approach is applied, based on stratified random sampling at polygon level. The working steps completed are, as follows: preparation of input and reference data, creation of a sample set of land cover/land use (LC/LU) polygons, visual interpretation of selected samples and evaluation of results. The LACO-Wiki web-based tool is used for sampling-related activities. Very highresolution (VHR) satellite imagery and digital aerial photos form major part of the reference data. This way, a scientifically based estimate of the thematic accuracy of UA and STL dataset are obtained and of some geometric characteristics, as well. The following features are estimated: user and producer's accuracy by LC/LU class, overall user's accuracy, uncertainty values, and correctness of delineation by LC/LU class. Comments by LC/LU class are provided. More than 89% of UA polygons have correctly delineated area. The detail of delineation accuracy is over 98%, while the positional accuracy is more than 97%. The overall weighted thematic accuracy of UA is 83.9%, which is higher than the target accuracy of 80%. STL product shows overall accuracy of 94.1% - higher than the required 85%. Relevant and diverse reference data sources together with appropriate stratification and sampling design tailored to the purpose and resources of the project helped to produce realistic accuracy results.

The aim of the study is to analyze historical village and present changes in architectural or historical elements Karavas village region. The main target that may be aimed at preserving the historical, architectural and cultural fabric of its area and policies appear as a result of analysis. Within this framework, Karavas village urban quarter pattern is analyzed by researching building storey, function, development period, building materials, roof type-materials, structural condition, architectural features, changes in façade or mass, elements of architectural features. Each building is digitized and field survey is completed then data is inputted in geographical information system environment. Additional satellite images and data obtained from local offices in order to control data within the study area. By analyzing changes, it is clear say that that some parts of Karavas village have been dramatically changed in terms of architectural features. Heights of the buildings area have been increased from 2 to 3 in the eastern and northern part. Detached, semi-detached 2 storey buildings are replaced by new apartments. These apartments also changed the character of the historical environment. Moreover, many traditional buildings have many different façade and mass changes, which is very common in Karavas Village. Results show that the buildings have a historical, monumental or architectural character that forms historical urban patter is in danger.

Timely and accurate maps of land cover changes are crucial for understanding the evolution of Earth's features and, consequently, the relationships between individual and collective needs. Therefore, this information is extremely important to develop future planning strategies and tackle environmental issues. This paper aims to exploit the use of Google Earth Engine (GEE) platform to examine land cover changes over a period of about fiftheen years in the pilot site of Siponto, an historical municipality in Puglia, Southern Italy. Six atmospherically corrected Landsat data, two for each selected mission (5, 7 and 8), were collected: the former was acquired in fall and the latter in spring. Land cover information was automatically extracted from each image through the implementation of an innovative Landsat Images Classifications algorithm (LICA) based on spectral indices analysis. Six classes (water, built-up, mining areas, bare soil, dense and sparse vegetation) were detected from each image, with an average overall accuracy higher than 85%. Land cover changes were assessed comparing classification maps of the same season, showing bare soil areas as the most altered ones, having been converted into arable lands in consideration of the adavantageous geomorphological features of the investigated site. This is also confirmed by the historical events experienced by the area.

This article aims to present the developed, adapted and applied methodology for the study, mapping, and evaluation of the effect and intensity of the urban heat island(UHI) within the urban space of the city of Sofia, while assessing its potential impact on the structure of the city and the prospects for its development and structure. For this purpose, a combination of GIS-based spatial analysis techniques is used, based both on the application of traditional satellite data sources and on the use of state-of-the-art unmanned aerial vehicle systems (UAVs), delivering highresolution information. The results obtained from the study are adapted towards their use for the purpose of supporting urban planning processes in the city and could greatly assist in the establishment of more adequate models of spatial planning in the urban area of Sofia, in the context of global climate change and the expected intensification of the UHI effects in the near future.

Satellite radar instruments deliver SAR data that are able to provide information on the magnitude of ground motions in range of centimeters. Such information is of extreme importance is assessing the consequences of natural or man-made disasters. Since earthquakes are occurring constantly and are not possible to predict it is recognized that any information on the size of this events is important for the local and national authorities responsible for mitigation of the post-event damages. In this research presented are the results obtained after processing two sets of SAR data along with other supplementary data in order to produce two interferometric images that provide information on the deformation processes after several earthquakes that took place on the Ionian shore of Albania in the second half of November 2019. The resulting deformation maps from ascending and descending orbits of the Sentinel1 satellite mission were compared to increase the reliability of the conclusions made upon them. The outcomes reported suggest that it would be possible to deliver to the national authorities details on deformation in regions that are problematical to inspect directly.

The territorial distribution of landslides along the Northern Bulgarian Black Sea coast has been evaluated by analyzing the results of field surveys for 2018 and 2019 based on geological surveys and processing of interferometric images from synthesized aperture radars (SAR). A local image archive of Sentinel-1A / B was created for the period 2015 - 2019 for this region and interferograms were produced every 4 months, 8 months, 1 year and in case of registering an event, led to the activation of landslide processes. A raster map of the concentration of deformations of the Earth's crust was created based on data from the obtained interferograms. Areas with active landslide movements along the Northern Bulgarian Black Sea coast have been identified for monitoring with the Global Navigation Satellite Systems (GNSS). A geodynamic network of 30 points covering the landslide circus ”Dalgiya Yar” and landslide “Thracian Cliffs“ was established and the first measurement cycle was carried out.

Rockfalls clusters can be systematic monitored using many different in situ or remote sensing methods: topographical survey measurements with total stations or GPS, mapping with terrestrial laser or photogrammetry using airphotos or high resolution satellite images. As the costs of the aerial photo campaign and the acquisition of very high resolution satellite data are quite expensive the use of cameras on board Unmanned Aerial Vehicles (UAVs) could be an identical solution for repeated campaigns and systematic monitoring of a rockfall. During the last years UAVs have proved their efficiency for remote sensing monitoring of small areas. The purpose of this work is to demonstrate a cheap but effective solution for an active rockfall monitoring. We present the first experimental results of the synergistic use of UAV and GPS measurements for a rockfall monitoring in Zachlorou village near to the city of Kalavrita, Western Greece. Three UAV flights with RGB, multispectral and thermal cameras were performed. Very accurate digital airphotos, high accuracy DSM and thermal mosaics were produced and the results are presented in the current study.

Panagopoula landslide is one of the most famous disasters occurred in Greece during the last fifty years. Many studies describing the geology of the broader area and the geotechnical characteristics of the landslide that took place on May 1971 have been published. The specific instability zone has been activated in the past several times and remains active until now. According to the literature, the landslide was 350m wide and the landslide materials had covered and destroyed totally the highway and the railway. For many months, the land transportation between Athens and Patras was interrupted and ferries carried all the vehicles between two piers that were constructed in the broader area. In 1972, another big mass movement was activated on the same place. Although, Panagopoula landslide is very well studied an accurate mapping of the slide area and calculation of the mass volume has never been performed. In the current study aerial photos and Declassified Satellite Imagery were processed in order to map the landslides extent fifty years after the disaster. Digital Photogrammetry and GIS techniques were combined and the results are presented.

The global exposure of population and the built environment to natural hazards has significantly increased over the last decades. Consequently, important initiatives, such as the SENDAI framework for disaster risk reduction have risen to promote a global culture of effective disaster reduction policies, including mitigation actions on the social and economic impact of geohazards. Efficient prevention and mitigation rely on meticulous observation and monitoring of geohazards triggering factors using space- and ground-based techniques. The most prominent space techniques are Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) satellite missions. The combination of GNSS and SAR observables through the integration of CORS networks and Corner Reflector arrays forms a seamless and continuous ground displacement monitoring system. The purpose of this paper is to present current permanent infrastructures dedicated in space-based deformation monitoring, perform analysis of their instrumentation, review their monumentation types and procedures, and examine the required spatial distribution of network multi-sensor stations. Finally, CyCLOPS, a new regional integrated monitoring system, which enables robust and seamless monitoring of earthquake and landslide activity in Cyprus and the Southeastern Mediterranean Region is presented in this paper.

The anthropization of many territories observed in the last decades has caused an increase in waterproof surfaces, with alterations of the hydrological cycle. The soil waterproofing reduces hydrological losses by increasing surface runoffs, with the same atmospheric event. Also, the climate changes significantly affect the atmospheric events that generate intense rainfall and sea storms and the major consequences are observed in the case of concomitant events. Generally, in the scientific literature floods and sea storms are studied and analyzed separately. Most of the research mainly focuses on the effects generated on the territory rather than on the analysis of the causes that favor the concurrence of these events. Vulnerable territories such as the Italian and Calabrian ones can be affected by these events. The paper analyzes the conditions that favor the contemporaneity between floods and sea storms, focusing mainly on the geo-morphological and climatic aspects of the Calabrian territory, and in particular of the metropolitan city of Reggio Calabria, which, due to its geomorphological and climatic characteristics, it is subject to concurrent events.

During last decade, due to fast progress of geospatial technology development, all weather, high-resolution and highdynamic range, a huge time-series data base is available for earthquake precursors anomalies monitoring in active geotectonic areas. In this paper, changes before and after the Vrancea earthquakes in the crustal dynamics as well as in the land and atmospheric parameters (land surface temperature LST, surface latent heat flux -SLHF, and air surface temperature- AT anomalies, have been investigated on the basis of time-series geospatial (NOAA AVHRR and MODIS Terra/Aqua) and field data analysis for January 2012- January 2020 period. For some analyzed earthquakes, starting with ten days up to one week prior to a moderate or earthquakes a transient thermal infrared rise appeared in LST (5-10 K° ), SLHF (tens of W/m² ), and AT (2-10 C° ) values higher than the normal, function of the magnitude and focal depth, which disappeared after the main shock. The joint analysis of geospatial, geophysical, and geological information revealed new insights for Vrancea zone seismicity in Romania. Since the variations of the solar and geomagnetic indices follow a normal behavior during the whole period of the observed anomalies between 3 and 10 days before the earthquake, it can be concluded that multi-precursors analysis is very important to detect the possible Lithosphere Atmosphere Ionosphere Coupling (LAIC) effects.

We used C-band data from the ESA satellites (ERS, ENVISAT and SENTINEL-1) to map ground motion patterns in the vicinity of Evinos dam in central Greece. The stability of the body of the dam was also examined. In the dam reservoir area, we obtained displacements up to 17 mm/year along the line of sight (LOS) in the vicinity of village Klepas (ENVISAT dataset; 2003- 2010). Several active landslides in the InSAR data were confirmed on the field (September 2017). Regarding the dam body, ENVISAT data show no significant deformation (less than 7 mm/year along the LOS). The SENTINEL-1 data (up to 2017) continue to show the same behaviour, however, a periodic signal and differential deformation on the dam body of the order of -8 mm/year along the LOS were detected and needs further investigation. We also mapped small ground motions inside several villages upstream the dam. A new landslide inventory for the dam upstream area was created from optical data.

The aim of the work is to study the longitudinal sediment transport in the coastal zone under the influence of surface waves. In the structure of surface waves, two main components are distinguished: purely wind waves and swell. For the climatic period of time, the volumes of sandy sediments, transported under the influence of wind waves and swell were calculated. The possible dominance of the swell contribution to the morphodynamic appearance of separate coastal sections is shown.

The creation of coherent radio lines is one of the ways to increase the noise-resistance and reach conditions making possible the reception of the optimal signals. The purpose of this paper is to propose a method and a device for accurate independent and coherent reproduction of the shape of the transmitted frequency hopping spread spectrum signals in the transmitter and receiver.

Anapa bay-bar is largest sand accumulative coastal form of the Caucasus Black Sea coast. Bay-bar of the Solenoye Lake is the northern part of the geosystem of Anapa bay-bar. Research opportunities of the relief and the landscapemorphological structure of the bay-bar transformation using remote data are shown in this paper. Simultaneous satellite images from open sources were the basis for analyzing of the dynamics of the sea and lagoon shores of the bay-bar. In addition airborne laser scanning and digital aerial photography of the Solenoye Lake bay-bar have performed in 2013 and 2015. Further, aerial laser scanning data and aerial photography were used to create high-precision digital elevation models (DEMs) and orthophotoplans of bay-bar and adjacent coastal sections. The analysis of digital elevation models made it possible to obtain linear and volumetric morphometric characteristics of this accumulative form. Relief and plan cover changes of the bay-bar, recorded using differential DEM or found in photographs, have both anthropogenic and natural genesis. Relief changes caused by hydrogenic processes are concentrated within the beach and erosion cuts. It has been established that beach topography restructuring occurs in almost every severe storm. The alternation of areas with increasing and lowering surface and fluctuations of the beach width due to coastline migration is characteristic. Most of the changes of the relief and vegetation in the central part and on the lagoon coast of the bay-bar are caused by anthropogenic impact. Leveling surfer of bay-bar for buildings, tents, parking and the dike creation to protect territory are marked. In the future, the destruction of dikes under storm influence and the dune restoration under influence of eolian processes are observed.

One of the main concerns in adopting citizen science is data quality. Derived products inherit intrinsic limitations of the capture methodology as well as the uncertainties in observations. OpenStreetMap tools are designed to minimize uncertainties in positional accuracy by ensuring a good co-registration of the observations with imagery or direct use of GPS. When thematically annotating objects contributed by citizens, uncertainty increases. During the H2020 GroundTruth 2.0 project two land-cover products derived from OSM were analyzed; one created by the University of Heidelberg (http://osmlanduse.org) and another elaborated by University of Coimbra (https://vgi.uc.pt/vgi/osm/osm2lulc/). To be able to assess the quality of both maps, a third product derived from remote sensing was introduced as a reference map. In GroundTruth 2.0 a tool to show and compare maps as part of the MiraMon Map Browser was developed. The objective was to allow final users to auto-evaluate the quality of their region of interest. The confusion matrix has been used as a method to derive overall commission and omission estimators as well as the Kappa coefficient. Most of the discrepancies between OSM and remote sensing (RS) derived maps are related to different approaches used during data capturing. The data quality tool assesses the quality of individual observations exposed using the OGC standard and describes the quality in an interoperable approach based on QualityML.

Phenology monitoring observations have been traditionally linked to citizen science (CS) practices and limited to common species closely located to an observer’s residence. This is a modest approximation to cover the strong variability of the vegetation phenology across biomes and to improve the knowledge of vegetation changes as climate change impacts. Thankfully, remote sensing imagery (RS), especially data from high spatial and temporal resolution satellites such as Sentinel-2A and 2B, has the potential to become an essential dataset for in-situ approaches by guiding volunteers in achieving this aim. This study presents the methodological design carried out in Catalunya to harmonize phenological vegetation monitoring protocol between RS and CS making data acquired from both approaches interoperable. First, an Earth Observation Open Data Cube (ODC) containing Sentinel-2 radiometrically corrected data was created. The ODC offers a solution for storing big data products in an efficient way with low-cost hardware and provides easy access to data by indexing it. A selection of ~40 000 areas presenting a homogeneous cover common species of interest has been extracted from existing vegetation cartography. A time-series analysis of vegetation indices (greening and flowering) derived from the ODC has been performed for each area. A final subset of ~5 000 areas presenting a flowering amplitude signal > 10% and a greening-up amplitude signal > 20% was extracted and included in an interactive map browser available to CS observers so they are guided to interesting areas to report their phenophase and evaluate their correlation with RS data. This protocol, resulting from the PhenoTandem project (CSEOL - ESA) provides an innovative approach making in-situ observations interoperable with RS products and confirms a promising partnership for phenology monitoring.

Super-resolution remote sensing data fusion aims to compose the output image with the higher spatial and spectral resolution from the lower resolution input ones captured for the same territory. The images used for fusion are usually multi-temporal. However, existing multi-temporal image fusion methods exploit only cloud-free images that might be difficult to obtain for some territories where the weather conditions are moderately cloudy during the observation period. In this paper, the clouds and their shadows are considered as scene distortions i.e. significant local changes in brightness caused by some opaque objects or their shadows partially overlapping the scene at the moment of image registration. Here, we propose a multi-temporal remote sensing data fusion method adapted to the dataset containing images partially occupied by scene distortions. The method is based on gradient descent optimization procedure with scene distortion elimination in each iteration. The experiments with the modeled data revealed that our method provides spatial and spectral super-resolution even for datasets including images with scene distortions. In comparison with the scenedistortion free case, the proposed method reduces a root mean square error of the resulting image from 2 to 4% on average in the case of the mixed data sets with few undistorted images (from two to six). The overall research has shown that in the case of lack of the data without scene distortions, additional partially distorted images can be used to obtain better fusion results.

This paper focuses results obtained from a field spectroscopy campaigns for detecting underground structures. A number of vegetation indices such as the Modified Simple Ratio (MSR), Renormalized Difference Vegetation Index (RDVI), Optimized Soil Adjusted Vegetation Index (OSAVI) and Red Green Ratio Index (IRG) were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices. The measurements were taken at the following test areas such as: Area (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure and Area (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure. For this purpose was using histograms to obtain useful information about Vegetation Indices spectral behaviors and to compare the two testing areas.

In March 2018 the Reina del Cisne (Cuenca) landslide was triggered by a hillslope cut for the construction of a small access road to a house. The landslide is conditioned by the lithology of the slope (mainly sands) and its high slope (up to 40°). From March to June 2018, the period analyzed in this work, the landslide has caused partial to total structural damages in some houses, scarps in a crop field and the total blockage of the road that triggered it. Field visits since March’18 and the comparison of the point clouds obtained with terrestrial laser scanner in May and June 2018, carried out with CloudCompare, have revealed the high activity of this slip. An affected house has been analyzed in 3D and it has experienced downhill sinking and tilting with local displacements of up to 91 cm in 20 days.

The Corona spy programme was a series of reconnaissance satellites which delivered more than 860000 images between 1960 and 1972. Since 1995, the data are declassified and a large historic earth observation archive is made accessible to the scientific community. Despite the large volume of information and the high spatial resolution of the satellite imagery, little has been done in the last 25 years in the context of image processing of this data source, a fact which perhaps can be attributed to the technical difficulties of these primitive images such as the lack of metadata, intense spatial and radiometric distortions, low Signal-to-Noise Ratio (SNR) and a single panchromatic band. Hence, the photogrammetric challenges to extract useful information are paramount. In this study, we present recent developments arising from our efforts to map settlements and agricultural parcels over the Plovdiv region, Bulgaria from a Corona image acquired in 1968. We, overall, present initial findings from the integration of earth observation into the ERC-StG project UrbanOccupationsOETR and evaluate the usability of such primitive images in feature extraction. We compare the areas corresponding to settlements and correlate them with concurrent population census. Based on the findings, we suggest that settlements and agricultural parcels can be mapped from a Corona KH-4B image with fine radiometric quality.

The aim of this research is to investigate the potential pollution similarity of the coastal areas using Hierarchical Cluster Analysis method. Furthermore, it is possible to monitor the evolution of tourist facilities in order to identify whether or not potential environmental distortions on the island. So, can be formulated a tourism policy that is in harmony with the island's natural environment. Lefkada is one of the small islands in the Ionian Sea. Geographically the island is situated off the western coast of Greece. Lefkada is often an especially attractive tourist destination with benefits of tourism and ecological costs for two decades. The quality of the environment, both natural and man-made, is essential to tourism especially the coastal areas. Those areas are transitional areas between the land and sea, and they include fragile ecosystems. At the same time, coasts are under very high local and tourism population pressure due to rapid urbanization processes. Massive influxes of tourists, often to a relatively small area, maybe have a huge impact on the environment. Eleven surveyed coastal areas were processed and grouped using the Hierarchical Cluster Analysis. This method is an exploratory technique that evaluates the similarities of potential pollution levels between coastal areas of Lefkada.

This paper aims to investigate the influences of urban growth and green land cover decrease on land surface radiative properties and metropolitan climate of Bucharest in Romania. Remote sensing data from Landsat TM/ETM/OLI, Sentinel 2 and time series MODIS Terra/Aqua thermal infrared sensors as well as in-situ meteorological data have been used to assess urban land cover– air and land surface temperature interactions over period between 2000 and 2019 years. The air (Ta) and land surface temperature (Ts), key parameters for urban climate research, were analyzed in relation with variables land surface albedo and Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, Urban Heat Island (UHI) effect and the relationships of Ts to other biogeophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ta and Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. Was also analyzed UHI phenomenon during extreme heat waves events. Our results suggest that monthly mean UHI intensity is between 1°C and 6°C, and the most intense UHI occurs in day-time in the summer period during heat waves periods. The analysis shows that different urban/periurban zones and landscapes bring diurnally and seasonally different contributions to the local and regional thermal environment. City land cover was the most important contributor to increases in regional Ts. Vegetation had a clear cooling effect as the normalized vegetation difference index (NDVI) increased during summer periods.

Global soil moisture products retrieved from various sensors onboard satellites are becoming readily available. However, validation of such products is a crucial step to ensure their reliability. In-situ measurements, which provide the most accurate soil moisture estimates, are often used as reference dataset, but they are limited in number. The GROW Observatory (GROW) was initiated to demonstrate that a 'Citizens' Observatory' (CO) can provide and utilise unprecedented amounts of data. We present GROW as a case study and demonstrate, for the first time, the use of crowdsourced observations to assess the temporal and spatial consistency of various satellite-derived soil moisture products. In particular, we provide evidence of the added value to Earth Observation, thanks to (i) the high number of sensors deployed, covering a wide range of land use, environmental, and climatic conditions, and (ii) the unique spatial density in GROW. Our results confirmed that SMAP and ESA CCI SM can better capture the temporal dynamics compared to the other products investigated. We found high uncertainties due to the spatial mismatch between in-situ and satellite observations, not only for coarse scale but also for high-resolution soil moisture products. This finding highlights the importance of crowdsourced observations, which have the potential to reduce representativeness errors. Finally, a preliminary analysis of the spatial consistency of Sentinel-1 soil moisture showed a poor agreement against GROW data. We conclude presenting the challenges and the steps that will follow this preliminary analysis, as well as design guidelines for COs to meaningfully contribute to Earth Observation.

Understanding how urban forest land cover responds to climate change requires knowledge of land-surface interaction processes, which control the degree to which interannual variability and mean trends in climatic variables affect the surface energy budget and by this forest vegetation. Urban forest represents unique areas for the detection of climatic change and the assessment of climate-related impacts. Effects of climate extremes and anthropogenic changes on urban/periurban forest systems in Romania can have both short-term and long-term implications for standing biomass, tree health and species composition. This paper used time series of normalized difference of vegetation index (NDVI) and enhanced vegetation index (EVI) as well as leaf area index (LAI) as a measurement indicators of forest dynamics at metropolitan scale in order to assess impacts of climate changes on forest ecosystem phenology in metropolitan area of Bucharest. Use of satellite remote sensing to monitor the forest changes due to climatic stressors is an excellent example of the value of multispectral, multiresolution and multitemporal observations. Fusion technique was applied to time series satellite imagery data (Landsat TM/ETM/OLI, Sentinel 2 and MODIS Terra/Aqua satellite data) for urban/periurban forest ecosystem of Bucharest metropolitan area in Romania over 2000-2019 period. Also, this paper addresses a number of issues related to changes in land surface temperature (LST), and analyses correlations between NDVI/EVI time series and climatic variables under different scenarios for summer heat waves, windstorms and heavy precipitation.

Relief as basic element of the natural complex significantly affects its components. Providing of the operational monitoring of the coastal zone relief is one of the important tasks of coastal investigations. This paper presents the adaptation of the methodology of digital aerial photography using drone and building a digital elevation model for high abrasion coast. It is shown, that unlike space and aerial photography from an airplane, drone surveys make it possible to monitoring of coastal areas with high surface slopes. This is necessary for the studying of abrasion coasts with pronounced cliff and complex relief. Aerial photographs of coastal cliffs are recommended to make by prepared flight routes using the vertical and inclined positions of the camera’s optical axis. Analysis of the obtained digital images and created digital elevation models showed that this type of survey is optimal for the considered natural object, but has a number of limitations. Low cost and speed of data acquisition are the advantages of the method.

Ground monitoring of soil massifs takes a lot of time, labor force and material resources, yet is the most accurate and detailed method. When implementing complex methods for monitoring the soil cover, inclusion of space technologies is necessary. Remote sensing data carry objective information over large areas, obtained in various spectral ranges. The article discusses the possibility of using remote sensing data for mapping and monitoring changes in the soil cover of Northern Kazakhstan. Based on thematic processing of remote sensing data of domestic satellites, spatial analysis of the content of main nutrients was executed in the sowing layer of soils, the relationship was revealed between fertility indicators and the value of vegetation indices for testing ground on the territory of Northern Kazakhstan.

The alpine terrain with its exposed georelief and climatic conditions supports a wide range of natural processes with various morphodynamic phenomenons. The National Park of High Tatras is probably the most visited park in Slovakia and the instability of talus cones during times of of torrential rains thus may present a significant danger to the tourists in their vicinity. In this paper we present a procedure for documenting and monitoring the talus cone stability, which is a typical geological phenomenon in alpine areas, using the SfM (Structure from Motion) method based on UAS imaging. A significant problem of documentation in the alpine environment is posed by the character of the terrain, which is inclined with a slope usually between 20° and 60°, often very rugged, consisting essentially of larger or smaller boulders ranging in sizes from 10 cm to 1 m (often with the occurrence of isolated stone blocks of several meters). In our study, we have shown that in difficult mountain conditions, UAS photogrammetry is capable of providing models of comparable quality with those acquired by TLS for monitoring movement of the talus cones. Mean absolute deviation of 0.028 m and a standard deviation at an absolute distance of 0.029 m. A mean difference of 0.008 m is practically negligible in the altitude component, and the standard deviation is 0.032 m we can conclude that with the exception of vegetation-covered areas, the terrain model obtained from low-cost UAS photogrammetry achieves qualitative (precision) parameters comparable to those obtained by terrestrial laser scanning and is thus suitable as a basis for systematic monitoring that will form a basis for identification of surface changes at the centimeter level.

Main subject of this paper is to investigate and evaluate methodologies for photogrammetric applications in geosciences, theoretically and practically, mainly focusing on systematic monitoring of surface mining areas. Its objective is to develop a technique adaptable to the particular characteristics of each application in order to efficiently meet the criteria of short time and low cost, but also of the required high frequency of application, as well as those of accuracy of the end products. Several methods for surface monitoring in mines have been developed. In particular, key aspects of the whole process to be studied in detail are, the following: a) Regarding data collection, UAVs with integrated RGB cameras will be used for data capture, b) Careful flight planning and geometric configuration of image acquisition, depending on the morphology of the object of interest and accuracy requirements will be under consideration, c) SfM applications and the bundle adjustment method with self-calibration will be used in order to process the collected data, d) GCPs (ground control points), check points and GPS/IMU information will be used for evaluating the results and e) Volume calculation differences between areas of interest will be practically evaluated. The main need for aerial mapping applications in mines environment besides accuracy standards, cost minimization and speed of work is of course public safety and prevent the loss of life.

Verbenaya Kosa is accumulative form of the barrier type. It is located on the southeast coast of the Sea of Azov. It is part of the marine edge of the Kuban River Delta and has been formed over the past 200 years under the influence of the simultaneous action of natural and anthropogenic processes. A study of the coastline dynamics of the Verbenaya Kosa has been conducted since the middle of XXth century. The coastline has shifted 80-400 m from 1973 to 2006 in different sections of Verbenaya Kosa. Complex of coastal protection structures (9 km long) was created in 2007. During the construction of the shore protection structure and subsequent period, lithomorphodynamic monitoring of Verbenaya Kosa was carried out. It has included annual topographic-bathymetric measurements of the surface and underwater slope of the accumulative form. The analysis of literature data, engineering survey materials, monitoring data, supplemented by remote sensing data allowed summarize information on the structure and dynamics of the Verbenaya Kosa relief. Historical topographic maps (since 1877) and satellite images of the 1960-1970s, made by the US Geological Survey, were used to evaluate of the long-period dynamics of the studied area. Since 2015, shoreline and submarine bars configuration monitoring has been conducted using Sentinel-2 satellite data. Studies have shown that the development of Verbenaya Kosa was determined by the rate of Kuban Delta extension into the sea water area, sea level fluctuations and changes of the wind-wave regime. Since the middle of XXth century, anthropogenic factor has become determining factor for the Verbenaya Kosa development. Currently, the coastline of it has stabilized.

Recently, the application of the multibeam echosounder systems in Bulgaria has become a standard method of studying the seabed. Nowadays, our task is to combine archival bathymetric data from single-beam echo sounding and contemporary multibeam echo sounding scanning. In this work, we present our initial activity in our primary scientific goal to create a composite digital model of the Broad Burgas Bay that will allow us to the future geospatial interpretation and identification of present-day seabed morphological forms and processes on the seafloor. For this study, a geo base database was created with bathymetric surveys from different years and equipment. The used data combine sonar mosaics, single beam, and multibeam bathymetric data and raster satellite images, processed in PDS 2000, SonarWiz, and GIS environment. The data is equated in a Baltic elevation system, which allows the construction of a digital relief model accurately. The density and coverage of the bathymetric data allowed the generation of a digital bathymetric model of the seafloor relief with a horizontal resolution of 14 m. A bathymetric map with an interval of 1 m was created with high accuracy. Such a high-resolution model is a significant advance in the high-resolution mapping of the Bulgarian Black Sea seafloor.

Varna and Beloslav Lakes represent the largest inland water body along the Bulgarian coast. The shores of typical firth have been transformed into highly developed industrial areas. In another point of view, in the last 50 years, the bottom of lakes has been significantly anthropogenized. The Lack of regular monitoring of morphological changes and processes on the bottom does not allow a correct assessment of lakes' status. This work presents our initial activity to create a composite digital model of the Varna - Beloslav Lake complex, with a comprehensive analysis and identification of contemporary morphological bedforms. For creating a digital terrain model of the lakes, a geo based database was created with bathymetric surveys from different years and equipment, combined with high-resolution orthophoto mosaic of the shores. The data combine sonar mosaics, single beam, and multibeam bathymetric data, and UAV images. This provides accurate (vertical accuracy of less than 0.5% of water depth), full-bottom coverage of the bathymetric data allowing the generation of a digital model of the seafloor relief with a horizontal resolution of 3 m and creation a bathymetric map with an interval of 0.5 m. The lakes' bottom forms are divided into natural and anthropogenic types. The conducted morphometric analysis gave us reason to localize specific bedforms of a coastal sloop, slightly sloping accumulative bottom, lake plains, channels, and other features of anthropogenic nature.

Tide gauges remain the fundamental instrument used to measure water level in the coastal environment. Issues surrounding the calibration and vertical datum control of tide gauges are therefore fundamental in studies involving the determination of absolute sea level and its variation over time. In this article, we collected and analyzed data from five tide gauge stations, located in strategic positions around the Cyprus island. During the analysis the following tidal datums were determined: Mean Sea Level (MSL), Mean Tide Level (MTL), Mean High Water (MHW), Mean Higher High Water (MHHW), Mean Low Water (MLW) and Mean Lower Low Water (MLLW). These were calculated temporarily using the available data observed since December 2019. Using the Doodson X0 filter for suppressing the effect of the astronomical tide on the MSL, this preliminary methodology provides some insight regarding the Absolute Mean Sea Level and Mean Tide Level of Cyprus.

The societal benefits of satellite ocean colour include aiding the management of the marine ecosystem, helping understand the role of the ocean ecosystem in climate change, aquaculture, fisheries, coastal zone water quality, and the mapping and monitoring of harmful algal blooms. Ocean colour is also designated as an essential climate variable by the Global Climate Observing System (GCOS). However, in order to have confidence in earth observation data, measurements made at the surface of the Earth, with the intention of providing verification or validation of satellite mounted sensor measurements, should be trustworthy and of the same high quality as those taken with the satellite sensors themselves. In order to be trustworthy, in situ validation measurements should include an unbroken chain of SI traceable calibrations and comparisons and full uncertainty budgets for each of the in situ sensors used. This metrological traceability is beginning to be demanded by the space agencies for satellite validation measurements and, for ocean colour, should follow the guidelines and protocols of the ESA Fiducial Reference Measurements for Satellite Ocean Colour (FRM4SOC) project (www.frm4soc.org). Until now, this has not been the case for most measurements used for validation, including those taken in the Aegean and Eastern Mediterranean. Subsequently, the Hellenic Centre for Marine Research (HCMR), in cooperation with the Laboratory of Optical Metrology (LOM), has started to follow the FRM direction by ensuring that the radiometers of its optical suite underwent SI-traceable absolute radiometric calibration. This included an estimate of the radiometry calibration uncertainty budget and was performed at the marine optical laboratory of the European Commission’s Joint Research Centre prior to their deployment on the recent PERLE-2 oceanographic cruise in the Eastern Mediterranean (Feb-Mar 2019). As well as irradiance and radiance sensors, the HCMR optical suite also houses instruments for measuring inherent optical properties (IOP) of the water column. Therefore, this paper presents the in-water radiometry matchups from PERLE-2 with Sentinel-3 Ocean and Land Colour Instrument (OLCI) measurements, and investigates their validation potential. It also presents the PERLE-2 cruise profile chlorophyll and backscatter measurements that aid this effort through characterizing the light scattering and absorbing constituents that contribute to the signal detected by satellite ocean colour sensors during validation matchups.

Pocket beaches are small beaches within headlands or structures, with practically zero longshore transport. These beaches often have a high environmental and tourist value, so knowledge of the relative dynamics is very important. The paper describes, through a case study relating to the pocket beach of Scilla, a methodology for analyzing the shoreline changes. Scilla is a town located about 20 km north of Reggio Calabria (Italy). The beach overlooks the Tyrrhenian Sea and extends for about 700 m, with an average width of about 50 m. Also, Scilla is subject to frequent coastal floods, which reach the inhabited center with almost annual frequency. The methodology is divided into two phases, one concerning the analysis of the shoreline changes and the other concerning the analysis of the wave climate. Regarding the first phase, the analysis was carried out on QGIS by tracing some transepts and by implementing a function to calculate the distances between the different shorelines. About the second phase, the data from the last 40 years present in the MeteOcean database have been used to evaluate the wave climate. This phase analyzes the main factors influencing the coastal dynamics in order to identify possible correlation between these factors and the shoreline changes. This paper shows a useful methodology to estimate the evolutionary trends of pocket beaches. This methodology takes into account the solid transport, is easily replicable in other similar contexts and is applicable in the field of planning and management of coastal territories.

Beach-dune systems host sensitive habitats subject to protection in compliance with the EU and national legislation. Along the Bulgarian coast, the substrata for the formation of depositional landforms are of predominantly terrigenous origin. Once eroded from the source provinces, they are transported as solid runoff and accumulated in the littoral zone. Consequently, the spatial distribution of depositional landforms is primarily related to the occurrence of gullies and ravines, estuaries and lagoons. Geomorphological mapping and classification, alongside vegetation mapping, represents the backbone of habitats identification in the case of coastal environments. Depositional landforms along the Bulgarian coast correspond to a number of sensitive habitats, enlisted in the national Red Data Book, and subject to protection pursuant to the country’s Biodiversity Act transposing the EU Council Directive 92/43/EEC (Habitats Directive). Three representative coastal segments along the North Bulgarian coast, hosting several sensitive habitat types, were surveyed in 2019 with a DJI Phantom 4 Pro quadcopter. All three are parts of the Bulgarian national nature conservation network. Accordingly, three sets of high-resolution orthoimages, digital surface models (DSMs) and 3D tiled models were generated in order to facilitate the GIS interpretations. The UAS-acquired imagery, DSMs and 3D models proved to be extremely useful geospatial data, greatly facilitating the process of coastal landforms and habitats identification. Nevertheless, as monitoring requires repetitive surveys, we should emphasize that the year 2019 marked the very first season when the approach was applied by our team. Therefore, deductions regarding long-term trends in the landform/habitat dynamics would be yet inappropriate.

The advent of satellite altimetry brought a revolution in monitoring sea level height in ocean and offshore areas. Satellite altimetry missions are constantly evolving over time and provide valuable products that assist, among others, in the precise estimation of Mean Sea Level (MSL) and its periodic update. Over the recent years, MSL has seen a rapid rise, mainly due to climate change and the increase of global temperature, which accelerates the melting of onshore snow and ice reserves, along with the thermal expansion of the oceans. Concordantly, several islands and coastal regions face the danger of 'drowning' or flooding. Therefore, Cyprus, being an island in the Southeastern region of the Mediterranean Sea mandates the continuous monitoring of sea level to determine the risk of flooding, especially in coastal zones. This paper presents a first endeavor to estimate MSL in Cyprus using Copernicus Sentinel-3 altimetric data from 2016 to date. The results were validated against MSL observations from the Cyprus national tide gauge network and a discussion on the use of Sentinel- 3 data as an indispensable monitoring tool is carried out.

Nowadays, the acquisition of very high resolution (VHR) imagery guarantees an excellent quality of coastal topographic surveys and monitoring. Alongside the rapid progress of remote sensing, digital photogrammetry and image processing of data obtained by unmanned aerial vehicles (UAVs) provides outstanding opportunities for VHR mapping of the coastal zone, including the coverage of difficult-to-access areas. Till the previous two years, the Bulgarian coast was “intact” for this modern technology and was regularly surveyed to detect and analyze the ongoing shoreline dynamics and trends of morphological changes. Both spatial planning and integrated coastal zone management, however, require highly accurate and up-to-date geodata, being among the main reasons for the wide application of drones worldwide in shoreline surveying, along with the low cost of the related mapping campaigns. This work aims to demonstrate the capabilities of UAV-based coastal landform mapping at Shabla Municipality case study site, Bulgaria. The above coastal segment was surveyed from a flight altitude of 200 m and at 5.8 cm ground sampling distance (GSD). In addition, erosion-prone areas were photographed from 50 m altitude and at 1.5 cm GSD. A digital surface model with a resolution of 20 cm for the whole coast of the Shabla Municipality was created. A finer one, with 6 cm cell size was derived after Structure for Motion data processing (SfM) for the area of Krapets Village together with the contiguous sector between Cape Shabla and Shablenska Tuzla Lagoon. A set of ground control points (GCPs) was used for georeferencing purposes. The shore was divided into erosional, erosional-depositional, and depositional segments, along with accompanying geomorphological classification of the identified landforms.