This PDF file contains the front matter associated with SPIE Proceedings Volume 11534, including the Title Page, Copyright information and Table of Contents.

Welcome to volume 11534 Earth Resources and Environmental Remote Sensing/GIS Applications XI

Tree surveys with the objective of establishing a tree cadastre or communal tree inventory is a time-consuming and expensive work.¹ As cadastres are commonly acquired in laborious eld surveys and updating involves regular site inspection, the effort of keeping a cadastre up-to-date is often either too high^,2 or a tree inventory is created only once or updated in a coarse temporal resolution. In the underlying study, we present a hybrid approach of merging data from different sources, to update a cadastre (shapefile) containing tree data. A classification of the four most frequent tree species in a study domain in Melville, Western Australia, was carried out. The considered tree species were Jacaranda Mimosifolia, Agonis Flexuosa, Callistemon KP Special, and Ulmus Parvifolia. The classification was performed on high-resolution airborne imagery, using Random Forests, and achieved outstanding results with an overall model accuracy of 93:44% and Cohen's of 89:93 %. This is a considerable step towards automated generation of communal tree cadastres in the contemplated geopgraphic domain. The proposed method demonstrates that (1) high-resolution aerial imagery has great potential in being a precise and efficient alternative for updating or creating communal tree cadastres, (2) updating requires minimal user interaction and can potentially be performed in a fully automated process, and (3) based on the excellent classification results, the considered tree species can now be detected and accurately mapped at scale.

This paper presents a one-dimensional scanning algorithm that allows improving the quality of images that were using aerial photography to monitor minerals and the state of the subsurface. Also, a software module was developed that implements the presented algorithm, the main advantages of which are the simplicity of the mathematical apparatus, the required number of low-resolution images, equal to two, to obtain a high-resolution image, and resistance to interference and noise.

Monitoring of the Earth land covers is one of the most important areas in applying remote sensing data. In-situ measurements are necessary to confirm the performance of remote sensing devices through evaluation of data quality. These measurements are performed in established space test sites and serve as datasets presented in open database for referencing remotely sensed data to ground-truth spectral ones, for enhancement of data accuracy and for verification of information extraction techniques. This paper describes the creation of standard experimental data set as a part of a project financed by Bulgarian National Science Fund. This local thematic spectral library is going to allow direct comparability of data from various sources including from available spectral databases. The deliverables are summarized in chapters including information about the used spectrometers and the methodology of measurements; the description of studied land covers in the points of measurements; the additional information such as GPS coordinates and atmospheric conditions for the monitored land covers in appropriated format. It should be noted that the spectral measurements are made with different instruments with proper calibration sources. The final result is creating of a thematic spectral library in local scale as an open access database. For user friendly access to the library without specific programs, simple text versions of the spectral data, their visualizations, and text files in HyperText Markup Language (HTML) format with the metadata and the additional information is used. The authors intended to propose the possibility for exploiting the spectral data from specialists working in different areas following the procedures for accessing the thematic spectral database and downloading the spectral data. This work is supported by “National Science Fund” in Bulgaria under Contract number KP-06-M27/2.

It is well known that in order to study the shoreline evolution in an accurate way, successive time series of high-resolution images are needed. However, the availability of historical high-resolution data is limited to analogue air photos while the more recent high-resolution satellite images are quite expensive. Thus, many researchers have based their coastal evolution studies on low-resolution images like Sentinel and Landsat data. As a result, a main question is raised about the accuracy of the results of such studies. As the Landsat program has started in 1972, there is archival data spanning almost 50 years. This is a great tool for longterm shoreline change monitoring in researchers’ hands. Another advantage of the specific data set is the existence of diverse multispectral bands and the opportunity to extract band ratios sensitive to existence or not of water. The biggest challenge for using this archive for shoreline monitoring is its limited spatial resolution (30m). In the current study, the accuracy of low-resolution satellite data such as Sentinel-2 MSI and Landsat ΤΜ, ΕΤΜ+ and 8 OLI for coastal monitoring is under control. Many low-resolution images were digitally processed, and Normalized Difference Vegetation Index (NDVI) as well as on-screen digitizing are used in order to automatically and manually separate the sea from the land respectively and extract the coastline in different periods. Then, the shoreline vectors derived from the Landsat and Sentinel-2 data were compared to the respective shorelines derived from high resolution satellite data such as Worldview-2 (0.5 m resolution) and orthomosaics created from digital airphotos with 1m spatial resolution. The study area is located in the Gulf of Patras in the North Peloponnese, Greece. The accuracy control covered three different periods from 1996 to 2018 and in every case, shorelines extracted from low resolution data sets were compared to shorelines created from high resolution data sets. Statistical analysis was performed, and the results are presented and discussed in the current paper.

Increasing awareness of the adverse impacts of human-induced environmental change have prompted the need for more sustainable development and proactive planetary restoration. An essential component is to equip stakeholders with timely and reliable data that provide informed understanding of landscape change across varying spatial and temporal scales. The Earth Observation Data for Ecosystem Monitoring (EODESM), which is based on the Food and Agriculture Organisation’s (FAO) Land Cover Classification System (LCCS), is an open source system allowing routine and automatic generation of land cover and change maps from Earth Observation (EO) data. It is currently being developed and implemented at national scales through the Living Wales project (https://wales.livingearth.online) using multi-source freely available EO data, including those provided by the Sentinel-1 and Sentinel-2 sensors. Airborne LiDAR, Open Street Map, Copernicus High Resolution Layers, and National Forest Inventory data have also been integrated. These EO data are transformed into Environmental Descriptors (EDs) which are then combined in EODESM to generate land cover maps. From those maps, changes are detected in the landscape using the evidence-based change module. The system allowed generation of nationally consistent land cover maps for Wales (UK) at 10 m spatial resolution. Using the evidence-based change module, 2017-2019 multi-year forest clearcutting as well as daily changes in water extent associated with flooding were identified and described. As the system is independent of temporal and spatial scale, EODESM has the capacity to classify diverse landscape changes across multiple time frames (e.g., localised episodic events or decadal processes) and provides robust, consistent and interpretable classifications. Furthermore, additional EDs can be ingested, which provides a logical and simple approach to tailoring user requirements. EODESM shows considerable promise for directing short to long-term restoration and enhancing natural resource management in support of greater ecosystem resilience.

The presence of plastic litters in the environment (both onshore and offshore) has long been identified as a threat for the ecosystems. Remote sensing provides an efficient and quick access to concentration areas of plastic litters. Due to composition similarities between plastics and hydrocarbons, absorption wavelengths are expected for plastics around 1730 and 2310 nm. Kuhn’s Hydrocarbon Index can be used for the detection of plastic targets on a hyperspectral aerial product. Spectral comparison algorithms (Spectral Angle Mapper and Spectral Information Divergence) as well as a spectral unmixing algorithm are used. J. Bioucas-Dias SISAL and MVSA algorithms are adapted for the automation of endmembers selection. Those previous results obtained in a controlled environment were expanded upon by using previous plastic detection algorithms as well as an index-based method (Flooding Debris Index; Biermann et al., 2020) on Sentinel 2 multispectral products. Using a cut-off value on the results of the FDI in southern Spain, onshore greenhouses and offshore plastic debris were detected. A supervised classification complemented the method, based on optical properties of five hundred greenhouses roof and five hundred non-plastic targets. In addition to plastic detection on land, we assessed temporal distribution of threadlike film presence at the sea surface on radar images in the North Atlantic. Wind conditions derived from Sentinel-1 images also help to understand the detection conditions. Spectral band configurations of free constellation of Earth observation satellites are not covering plastic absorption peaks which represent a significant limitation for their detection. The spatial resolution of commercial satellites (i.e Worldview-3) may be better adapted to plastic waste detection that have size distributions lower than open access satellite constellations. Even if offshore plastic detection with open access constellations remain challenging, image processing techniques may improve the detection

Over the last decade, Dubai emirate witnessed a vast, rapidly growing population, that doubled since 2008. Nowadays, Dubai considers as the most populated emirate within the United Arab Emirates (UAE). With such an increasing population and new urban developments, sustainable urban planning procedures play an essential role in Dubai's environmental quality such as air quality, and pollution. Therefore, this study will utilize the Remote Sensing and Geographic Information system (GIS) to investigate Dubai's environmental quality by addressing and locating green areas and pollution percentages within each district. The study methodology is divided into three steps. First, Landsat Satellite medium spatial resolution and multi-spectral imagery will be used as an input for segmentation and object-based analysis. Considering the spectral and spatial signatures for green areas machine learning techniques will be adopted to select the most significant features to classify and extract green areas. Second, using environmental relational indices, green areas percentages will be quantitatively compared to Sentinel air quality data, such as NO2 and SO2, as well as the population density maps. Finally, GIS techniques will be used to create Dubai Environmental Critical Map (DECM), to locate districts with limited green areas and high pollution to improve environmental standards. The study results can be used as a measure for the municipality policymakers to ensure sustainable urban development for a healthy living.

We have developed a framework for crisis response and management that incorporates the latest technologies in computer vision (CV), inland flood prediction, damage assessment and data visualization. The framework uses data collected before, during, and after the crisis to enable rapid and informed decision making during all phases of disaster response. Our computer-vision model analyzes spaceborne and airborne imagery to detect relevant features during and after a natural disaster and creates metadata that is transformed into actionable information through web-accessible mapping tools. In particular, we have designed an ensemble of models to identify features including water, roads, buildings, and vegetation from the imagery. We have investigated techniques to bootstrap and reduce dependency on large data annotation efforts by adding use of open source labels including OpenStreetMaps and adding complementary data sources including Height Above Nearest Drainage (HAND) as a side channel to the network's input to encourage it to learn other features orthogonal to visual characteristics. Modeling efforts include modification of connected U-Nets for (1) semantic segmentation, (2) flood line detection, and (3) for damage assessment. In particular for the case of damage assessment, we added a second encoder to U-Net so that it could learn pre-event and post-event image features simultaneously. Through this method, the network is able to learn the difference between the pre- and post-disaster images, and therefore more effectively classify the level of damage. We have validated our approaches using publicly available data from the National Oceanic and Atmospheric Administration (NOAA)'s Remote Sensing Division, which displays the city and street-level details as mosaic tile images as well as data released as part of the Xview2 challenge. In addition, we have integrated the CV-generated artifacts and results in a collection of analytic tools including routing, damage assessment, and response prioritization, to assist with response management and strategic decision. The routing tool allows users to plan optimal alternate routes given automatically detected flood lines from the latest imagery. Response prioritization estimators look for critical areas, e.g., homes surrounded by water, flooded roads, and other anomalies detected in the impacted area. Finally, the damage assessment tool includes a pixel-based financial model capable of outputting estimated financial damage costs projected according to the United States National Grid (USNG) coordinate system. In conclusion, we are working towards an emergency response system that provides stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate, and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations.

Fires, floods, water pollution and landfills are among some of the core environmental problems today. In the present work we consider the processes related to temperature pollution from landfills for municipal waste storage. Landfills where a temperature anomaly occurred as a result of a fire are also considered. Optical images from the multispectral instrument (MSI) of the Sentinel 2 platform and radar (SAR) data from the Sentinel 1 platform of the Copernicus program of the European Space Agency were used. The heat channel of the Landsat 5 - 7 (ETM) and Landsat 8 (OLI / TIRS) sensors was used to calculate the surface temperature from the landfill. By using orthogonation of satellite images, the dynamics of the individual components of the earth's surface - vegetation, soil and moisture - was traced. A combination of optical and radar imaging has been used to showcase the potential of this method by which landfills can be identified. Disturbance index was used as a quantitative indicator of the studied areas. Satellite data from different seasons and years have been selected to monitor the dynamics of thermal pollution from the landfills.

The satellite PSI Interferometry is a radar-based remote-sensing technique, which is capable of monitoring and measuring displacements with a high precision of the Earth’s surfaces by means of multi-temporal acquisitions. These are collected without interfering in any way with the operating conditions of the transport infrastructure as opposed to the common non-destructive survey methodologies (e.g. GPS, accelerometer, total stations). Nowadays, the use of medium ground-resolution SAR-datasets, acquired by C-Band sensors (operating at a frequency of 5.4 GHz), allow to conduct computationally affordable analyses, detecting displacements with a centimeter accuracy of the measurement. Furthermore, the use of images acquired by the new generation of high-resolution X-Band radar sensors (operating at a frequency of 9.6 GHz), allow to increase the ground-resolution and achieve a millimeter displacement-resolution This study aims at demonstrating the potential of the PSI remote-sensing technique to develop and formulate an innovative health-monitoring methodology and approach for structural assets such as bridges, using a multi-frequency satellite resolution. For this purpose, in this study C‐Band Sentinel‐1A SAR products provided by the European Space Agency (ESA), and X‐Band COSMO‐Skymed products provided by the Italian Space Agency (ASI) were acquired and processed. Furthermore, a PSI analysis was developed to monitor and detect structural displacements of a bridge of historical values. Outcomes of this investigation outlined the presence of various PS over the inspected bridge, which were proven useful to achieve a more comprehensive health monitoring and the assessment of the structural integrity of the bridge. This research paves the way for the development of a novel interpretation approach relying on the integration between remote-sensing data and non-destructive information collected on-site (e.g., GPR surveys and Laser Scanner), to improve and optimize current maintenance process of transport assets.

Dams are engineering structures with significant social and economic benefits as well as risks. A structural or operating failure of the dam poses a threat to nearby industrial sites, human settlements, and the environment. Usually, the consequence is an immense economic loss for the region. Therefore, it is of great importance to ensure dam health and functionality. The dead load of the dam body itself and the impounded water, among other things, can cause horizontal and vertical displacements of the dam body. If these displacements surpass a critical limit, the structural integrity of the dam is threatened. Therefore, the surface deformations need to be monitored. In this study, we discuss the different mechanisms, which lead to the deformation of a dam and how they can be monitored. First, an overview of the different construction types of dams currently in use is given. Whereby the focus is on embankment dams, since our main observation target, the Parapeiros-Peiros Dam, is an embankment dam. Second, the deformation processes an embankment dam may be subject to during its lifetime are described. Additionally, the conventionally used instruments and methods to measure these deformations, such as geodetic triangulation or optical leveling networks, are discussed. Based on the deformation processes known from the literature, we outlined what characteristics of an embankment dam need to be taken into account when setting up a deformation monitoring system. The monitoring system, we propose, works continuously and semi-automatically. The main task is to accurately map the surface deformations of the dam body and the surrounding area using SAR images and GPS positions of several control points. Afterward, changes in the behavior of the dam need to be identified and analyzed.

The acquisition of field data plays an important role in the calibration of the remotely sensed data, especially when combined with reflectance spectroscopy studies. The study area of this work is the Fregeneda-Almendra pegmatite field (spreading from Portugal to Spain) where different lithium (Li)-pegmatites are known. Several image processing techniques were applied to satellite images for Li exploration in the region, including machine learning classifiers. However, these algorithms identified several zones as Li-pegmatites false positives. Taking this into account, the following objectives were delineated: (i) validate the training areas used in previous studies and collect field data for training area refinement; (ii) assess the reason for the false positives previously obtained through field surveys. For that, various outcropping lithologies (Li-pegmatite, metasediments, granite) were sampled for laboratory spectral analysis. The spectral signature of Li-pegmatite was compared with the remaining outcropping lithologies. Also, the spectral signature of the sampled false positive areas was confronted with the spectra of Li-minerals. It was possible to conclude that these two classes present similar water/hydroxide and Al–OH-related features. The sampled granitic and metasedimentary rocks also presented water and/or hydroxide absorption features that can lead to some spectral confusion. However, Li-pegmatites can be discriminated from the remaining lithologies either in the training areas and the false positive areas due to the absence of iron-related absorption features and to the distinct reflectance magnitudes.

Although several lithium (Li) bearing minerals have already been spectrally characterized, there are no current reference spectra for petalite in large and public access spectral libraries. This fact is aggravated by the difficulty in the identification of petalite’s diagnostic features. The study area of this work is the Fregeneda (Spain) – Almendra (Portugal) region, where distinct Li bearing minerals occur in several types of enriched pegmatite dikes. Accordingly, the objectives delineated for this work were: (i) improve the existing knowledge on the spectral signatures of Li bearing minerals (lepidolite, spodumene, petalite); (ii) compare the spectra obtained for petalite and spodumene in the study area; (iii) and compare the spectra of the Li bearing minerals from the Fregeneda-Almendra area with the reference spectra from the United States Geological Survey (USGS), the ECOSTRESS and the Geological Survey of Brazil (CPRM) spectral libraries. For that, spectral measurements were conducted in the laboratory using the SR-6500A (Spectral Evolution, Inc.) spectrometer. The results only allowed to discriminate lepidolite, since that, both, petalite and spodumene, present absorption features typical of montmorillonite and illite, or a combination between these two minerals. This is also verified in samples of corresponding minerals in other spectral libraries. No diagnostic features of these two Li bearing minerals were identified, highlighting the difficulty to spectrally discriminate them from each other and from clay minerals.

The São Pedro da Cova coal mine, in Gondomar (Portugal), left a substantial ecological footprint in the form of a 28,000 m² waste pile. This waste pile has been undergoing continuous self-combustion since 2005, leading to the mobilization of pollutants. As a result, it is of vital importance to monitor the condition and evolution of the waste pile, to assess the current and potential risks posed to the inhabitants and to propose adequate mitigation measures. To evaluate and monitor the waste pile surface soil movements, a comparison between different digital elevation models (DEM) was performed. The DEMs were obtained from photogrammetric processing of data collected by different sensors onboard of an unmanned aerial vehicle (UAV). As preliminary results, the waste pile seems to be suffering a generalized topographic recession, verified by the elevation decrease on multiple monitoring points, this effect may be caused by soil erosion or subsidence, potentially caused by the coal fires that have been active in this waste pile. As part of a larger evaluation of the study area within the CoalMine Project, which includes geochemical soil and water analysis, as well as, monitoring of the surface temperatures, the current assessment of soil movement provides crucial insight into the movement and deposit of soil in addition to the potential contaminants present in its composition.

West Java is in the five line on the list of provinces in Indonesia with the most COVID-19 cases, as Bandung Metropolitan Area (BMA) is the second most densely populated showing the highest number after Jakarta Greater Area. Bandung Metropolitan Area consist of Bandung City, Cimahi City, Bandung Regency, and West Bandung Regency. Then, an intense movement of people created between the connected city and regency. Bandung City became the epicenter of movement BMA, since it is the province capital city, business, and education center. This fact, putting BMA at the highest risk not only for the pandemic but also socioeconomic issues. The spatial time series risk forecasting information is an essential for the decision-maker to develop a day by day policy aimed for combating the COVID-19 pandemic issue. In this study, the pandemic risk is calculated by combining vulnerability, hazard, and geodemography information. Infimap provides the People in Pixels geodemographic data, added not only the exposure of population distribution to COVID-19 but also the ratio of age. Beside those data, the daily distribution of COVID-19 cases, network data, business point, health facility point, residentials area, geodemographic (People in Pixels), and daily COVID-19 Community Mobility Reports is also been used in this study. The daily vulnerability and hazard data created since the first case on March 4th until August 21st. The hazard area is create based on the expected travel area of positive COVID- 19 patient. While the vulnerability area is create using Spatial Multi Criteria Analysis (SMCA) of following data: service area of hospital, groceries (local market), and workspace. Further, the time series data of hazard and vulnerability area was inputted to develop the forecasting model based on the machine learning pipeline of Gaussian algorithm. As a result, this study shows the possibility to predict the future risk area of COVID-19 until the next 100 days condition, based on spatial timeseries forecasting model.

Landslides or rockfalls in mountainous areas in Western Greece are a continuous hazard and thus, observation either in situ or through satellite data is of great necessity. In order to study landslides or rockfalls a very accurate representation of the relief is a prerequisite. In now days diverse remote sensing satellites provides digital surface elevation models (DSMs) with global coverage. The specific data sets present the advantages of covering large areas in a very low cost in comparison with the surveys in the field. In addition, high resolution DSMs enable the analysis of topography with high levels of detail and consequently geomorphometric approach becomes more accurate for studying landlsides or rockfall events. Information which can be extracted from geological and topographic maps in GIS format such as the slope angle distribution, deduced from high resolution DSMs, are substantial in rockfalls survey. In the present work, the accuracy of freely available DSMs are under control for landslides areas in Achaia prefecture in NW Peloponnese. The accuracy of the DSMs in the broader area is investigated using reference points of certified elevation while for the landslide area ground control collected with differential GNSS receiver are used. More specifically, free available DSMs as TanDEMX, ASTER GDEM, SRTM DEM with 30m and 90m spatial resolution, ALOS AW3D30 DEM, DSM from photogrammetric airphoto processing and DSM produced by Interferometric processing of radar images, are under examination in the current study. Furthermore, diverse statistical parameters such as the 2D Root Mean Square Error or the percentile value are computed and presented. The purpose of the aforementioned procedure is to detect the most accurate DSMs which are appropriate for landslide of rockfall monitoring.

The main objective of this research is monitoring of landslide areas by integrating results from interferometric images, and GNSS data from permanent and local geodetic networks. This study is providing reliable information with regard to the hazard geo-processes taking place in the region of the landslide area Thracian Rocks. To accomplish the aforesaid the first step was to create a local archive of about 400 SLC images from ESA operated mission Sentinel-1 starting from the beginning of 2015. In this archive data from ascending and descending satellite orbits were included in order to increase the reliability of the information derived from SAR data. Due to considerable occurrence of vegetation in the studied area, which is recognized as one of the factors increasing the decorrelation during DInSAR processing, the authors processed mainly scenes with minimum availability of leaves on the trees and shrubs – autumn and spring. The geological setting of the landslide region reveals a narrow strip formed by old landslides that have an average width of 400–500 m and steep slopes of 40–50 m at certain locations. From this setting it was established that the landslide bodies have been formed by 3–4 visible linearly oriented steps and landslide packages with different heights creating negative ground forms with permanent or temporary swamps. Besides the ancient landslides a recent active local landslide processes occur forming recent landslides. In the framework of this study a control geodynamic network covering the landslide area located in the surroundings of Thracian Cliffs golf club was established. In it included are 10 points stabilized with metal pipes which are used to monitor deformations in this area. An advantage of the approach should be pointed out the possibility to map areas that are inaccessible by other means.

Mass movements and therefore rockfalls are common natural hazards that require the development of new methodologies and techniques for an effective research, which could help governments, communities or policy makers in the adoption of the most appropriate practices. In that context different remote sensing data have been used and several methodologies have been tested. In the present study, we initially map a rockfall occurred on the settlement Myloi, which is located near the village of Andritsaina in Western Greece, while later we estimated the volume of rock fragments. The data sets consist of repeated GNSS measurements, laser scanning surveys and UAV campaigns over the study area. The precise mapping of the rockfall was carried out through the processing of GNSS measurements. However, mapping was also performed using orthophotos derived from UAV data and 3D images of laser scanning campaigns. Regarding the volume estimation, three methodologies were applied -two of them were photogrammetric and one was geophysical- using ArcGIS, Cloud Compare and Oasis Montaj from Geosoft respectively. The selection of different types of data and processing methodologies took place within the framework of the comparison of their results in terms of accuracy as well as the achievement of their synergy in the direction of a more detailed research.

This study aimed to evaluate the landslide risk map in the Algerian Western coasts. This evaluation was based on three steps. The first step requires evaluating the landslide hazard. To reach this, a field surveys data, combined with Geographical Information System (GIS) analysis and Remote Sensing (RS) image processing were carried out. Seven controlling factors were considered: lithology, geomorphology, slope, land use, distance to stream, rainfall and distance to fault. A topographic map of 1/ 25 000 was used to generate a Digital Elevation Model (DEM) with 15 × 15 m of resolution. From this DEM, the slope was extracted. Based on knowledge approach, the different factors were weighted according a scale value ranging from 1 to 9. The lowest values were assigned to the factors which have a minor influence on landslide triggering, and the highest values were given to the important parameters for landslide occurrence. These factors were combined using weighted linear combination (WLC). The landslide hazard map was classified into five levels: very low, low, moderate, high and very high. The landslide vulnerability was evaluated through the identification of the elements at risk. Three vulnerabilities aspects were considered: physical, environmental and socio-economic. The weights of each factor were given depending on the magnitude and the rate of landslide. Landslide Vulnerability Map (LVM) for Algerian western coasts was generated by the combination of the physical, environment and socio-economic vulnerability maps. Landslide risk was evaluated by combining the hazard map and the vulnerability map, and it was divided into four classes: very low, low, moderate and high.

The monitoring of archaeological sites declared World Heritage Sites is a fundamental activity to protect and safeguard cultural heritage. In this context, monitoring with sensors mounted on a satellite platform represents a valuable tool. The availability of satellite images at high temporal frequency allows a continuous monitoring of the areas to be protected. The images acquired with the Sentinel-2 constellation are available free of charge and with a high temporal frequency; this mean that it is possible a continuous monitoring of the areas to be protected. In addition, the change-detection techniques and, in particular, the "Image Differencing" technique may be used, thanks to its simplicity and speed of application, in the monitoring activity. This technique provides that to each radiance value of an image acquired on a given date, the corresponding values of another image dating back to a high date are subtracted; in other words, to each pixel of an image is subtracted the value of the corresponding pixel of a second image acquired on a different date from the first one. The investigation was conducted on the archaeological site of the Temple of "Ain Dara" located in Syria, which is recognized in 2011 as a UNESCO World Heritage Site. The temple was destroyed in January 2018.

Innovative digital applications are invaluable for the documentation and conservation of cultural heritage monuments. Digital techniques can provide data on cultural heritage sites to enhance understanding of their changes over time. Due to the age and conditions of cultural heritage monuments in Cyprus, especially churches, there is a great demand to develop a methodology that is capable of digitizing both the internal and external church using a variety of non-invasive techniques as a means of storing and managing documentation data and metadata for providing comprehensive culturally digital and documentation evidence. In this paper, the integration of various technologies was used to document the 12th century St. Efstathios Chapel in Kolossi, Cyprus. The methodologies included data acquired by close-range images from Unmanned Aerial Vehicles (UAVs) and hand-held cameras, coordinates from ground control points using Total Stations etc., to document both the internal and external facades and relics of selected religious monuments. Thousands of images from the monument were taken using a UAV with a high-resolution camera. The images were processed using photogrammetry to provide a digital model of the church. The use of the HSV color model was used to examine potential anomalies in the structure. The combination of the technologies will provide a 3D model to document and identify ecclesiastical cultural heritage sites, which can be incorporated into a dynamic database and valuable resource to better understand the cultural heritage monument. In this way, the end-users will be able to access the information from the digital platform at any time. This research is supported by the project entitled: “Navigators of Cultural Heritage Digitization of Churches of Cyprus and Crete” referred as “Digital unblocking of holy islands” 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 digital twin is among the Top 10 of the strategic technological trends for the period 2007-2019, and it represents a powerful tool for the conservation and enhancement of cultural heritage. It reproduces with "precision" a physical asset, thus allowing to investigate its structure and to analyze the deformations that occur over the years. Various techniques have been introduced to obtain high-resolution 3D models. Among these, the Terrestrial Laser Scanner (TLS) is widely recognized as the gold standard to generate accurate 3D metric reconstructions. TLS allows acquiring a lot of data (point cloud) in a fast way, being not in physical contact with the objects of investigation. By integrating the point cloud coming from the TLS with the one coming from the photogrammetric processes based on the Structure from Motion (SfM) and Multi View Stereo (MVS) techniques, it is possible to obtain a complete model of the object under investigation. The Unmanned Aerial Vehicles (UAV) photogrammetric technique allows to investigate possible elements not detectable by TLS. Both techniques, if well performed, can show comparable accuracies. Data fusion approach, based on multi-sensor and multi-scale integration, was proposed in the present work as the optimal solution to exploit the potential of the various techniques. A high-quality virtual twin from the All Saints' Monastery of Cuti (Puglia) was produced. The resulting detailed 3D textured model was generated by integrating digital photogrammetry with laser scanning data. A discussion on data acquisition procedures, modeling approaches and accuracy of results is provided.

The ERATOSTHENES Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment (ECoE) 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. One of the main focus areas of the newly established ERATOSTHENES Centre of Excellence (ECoE) is using remote sensing and space-based techniques for effective, efficient and timely cultural heritage monitoring. Such monitoring can offer tremendous benefits to Cyprus governmental institutions and policy implementation bodies, towards the protection of cultural heritage sites, including cost- and time-effective control of cultural heritage sites/monuments, raising awareness on the preservation and protection of cultural heritage from anthropogenic and environmental pressures, early warning systems and systematic monitoring of cultural heritage. Satellite Earth Observation technologies provide the ideal resource of information to undertake a wide range of effective, cost-efficient and non-invasive activities, which cannot be so easily acquired with other tools. As a result of the Copernicus Program, Sentinel 1 and 2 missions provide free satellite imagery that is accessible, provides global coverage, a high temporal resolution enabling image time series analysis and temporal characteristics, allowing for the consistent and timely monitoring of cultural heritage monuments and landscapes. The efficient exploitation of high resolution dense time-series of multi-spectral and radar imagery for large scale applications introduces new important considerations including cost-effective and systematic monitoring service of cultural landscape sites with archaeological remains, monitoring significant risks that cultural landscapes face, as well as aiding archaeological mapping and interpretation. Further-on exploiting high spatial and temporal resolution (i.e. from other satellites beyond Copernicus) improves modelling and data assimilation solutions and integration of space based remote sensing techniques with advanced ground and aerial based ones. Both data allows to develop more efficient and effective tools of investigation and monitoring, able to ensure mapping and monitoring of buried and exposed archaeological structures. This paper was developed under the auspices of the activities of the ‘ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment’- ‘EXCELSIOR’ project that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510 and from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development. From 1st of October 2019, the ERC group (Department of Civil Engineering and Geomatics) at the Cyprus University of Technology is on the way to be upgraded to ERATOSTHENES Centre of Excellence (ECoE) through ‘EXCELSIOR’ H 2020 Widespread Teaming project (www.excelsior2020.eu).

Anthropic changes resulting from urbanization contribute to the modification of surface materials, originating the suppression of vegetation, waterproofing of the soil and the variation of albedo, which can contribute to the formation of Heat Islands (HI). This phenomenon results from the higher absorption of electromagnetic energy by the buildings, when compared to vegetation, corroborating both the increase of surface temperature and the minimization of the relative humidity of the air. This effect is potentiated at night, when urbanized regions maintain higher average temperatures for a longer time, when compared to vegetation areas. Some impacts of this effect are: (i) thermal discomfort and influence on the local microclimate and; (ii) displacement of water bodies. This work aimed to analyze the relationship between the Land Surface Temperature (LST) and the Vegetation Proportion (Pv), derived from Normalized Difference Vegetation Index (NDVI), in the densely built area of Brasília (Brazil), in order to evaluate if its characteristics confirm the micro-scale climate change. Several images from Landsat 5 and 8 thermal sensors were processed between 1989 and 2019 and the results obtained point out that the LST is inversely proportional to Pv, i.e., the highest temperatures were observed in classified areas with scarce or no Pv, which corroborates with the hypothesis that anthropic altered regions can influence the local climate. Despite the phenomenon observed and the 50% increase in maximum temperature in 2019 when compared to the 1989 and the decrease in maximum Pv by 36% in the same years, it is mandatory additional studies to confirm these findings.

A coccolithophore Emiliania huxleyi is the most abundant calcifying algal species throughout the world’s oceans. As it is capable of significantly affect the marine surface biogeochemistry and carbon cycling between the atmosphere and ocean, its importance has both climatic and aquatic ecology dimensions. Blooms of this alga exhibit remarkable spatiotemporal variations and proved to be aquatic environment specific. Here we present our hypothesis regarding the origination of the intense blooms of this alga that occurred in the Bering Sea during 1997-2001, and further on in 2018- 2019. Our hypothesis relies on (a) the salient transport anomalies in the Bering Sea Slope Current, and the Alaska Stream, and the Near Strait throughflow that were documented elsewhere for the above period, (b) the retrieved spaceborne time series of statistical occurrences of NE&E horizontal directions of the geostrophic current at the east passes in the Aleutian arc, and the timings of the two latest El Niño events.

The chaotic signal is a relatively new field in communication systems. Motivation derives from the advantages offered by chaotic signals, such as spread spectrum, robustness in multipath environments and resistance to jamming. Chaotic signals are non-periodic, broadband, and difficult to predict and to reconstruct; they may be generated by mathematical map functions, electronic circuits or laser optics. Their properties coincide with requirements for signals used in communication systems, in particular for secure communication systems. The study in this paper is focused on one of the methods, proposed to send binary messages by chaotic signals- the chaos shift keying (CSK) approach. Each symbol to be transmitted is coded as a discrete chaotic signal, which is generated by a chaotic map. The symbols are detected at the receiver by coherent detection technique. The purpose in this paper is to present the error probability of a coherent CSK digital system under the influence of additive white Gaussian noise (AWGN), assuming ideal synchronization at the receiver. The solution for the error probability has been derived, in terms of the signal-to-noise power ratio.

One of the most important criterion of forest fire occurrence probability is the ratio of coniferous vegetation area to total area of the forestry. The work develops method of automated analysis of dynamic of coniferous forest area on the basis of NDVI index received from the temporal ranges of Landsat images, as well as tests it on the example of a forestry in Baikal Region. Maps of summary results of carried out spatio-temporal analysis of the forestry area are shown. Developed method and algorithm of processing Landsat images allow assessing condition and dynamics of spatiotemporal changes in vegetation (forest) cover in the area of study.

Spatial thinking can be defined as the knowledge about spatial concepts (e.g. location, direction, and scale) applicable on the description, analysis and problems solving in several contexts, such as Geographical Information System (GIS). Students from two Curricular Units (CU) and from 6 different background areas solved a test, named Spatial Thinking Ability Test (STAT), composed by questions about logic, spatial thinking, and geographical reasoning, regarding the GIS context. The aim of this study is to evaluate: i) the differences in knowledge, logical and geographical reasoning of the students and, (ii) the spatial thinking of students in the different areas. The test was applied to 83 students at the beginning and at the end of the semester (that is, respectively before and after students' contact with the concepts taught in the referred CUs). This study presents itself as a support methodology to pedagogical didactics that have been implemented in the CUs where it is intended to provide the domain of computer tools for manipulation and analysis of geographical information. Also, it will contribute to improve the learning of students, and will help teachers in a more effective, interdisciplinary and targeted management of knowledge within the scope of CUs, and to guide the syllabus and didactics for learning that must be guaranteed to all students. The responses were analyzed in the Statistical Package for the Social Sciences (SPSS) software. The analysis of the test results will allow to direct the contents considering the level of students in spatial and geographical reasoning.

This paper presents the significance and importance of promoting the benefits of Earth Observation when implemented in ‘secondary’ and ‘higher education’ in Cyprus schools. Firstly, examples of how Earth observation is used in other countries for the secondary education such as Germany and China and how ESA through Earth Observation education materials are used to promote STEM education are presented. Secondly, ‘EXCELSIOR for Schools’ & ‘SOFIA ESA’ initiatives for promoting earth observation education in Cyprus are also presented. Indeed. examples of how earth observation is presented through seminars, workshops, science cafes, researcher's night, from earth observation experts into schools in Cyprus is also described and analysed. Examples of how earth observation is used in the existing curriculum for undergraduate, postgraduate courses for surveying and civil engineers is demonstrated for monitoring and providing solutions for civil and geomatics engineering aspects at the Cyprus University of Technology through the EXCELSIOR H2020 Teaming project.

High-resolution satellite imagery permits verification of land clearance violations across borders due to unstable regimes or socio-economic upheaval. Without access to such areas to validate allegations remote sensing tools and techniques use are very important. Imagery-based assessment can quantify radiometrically calibrated normalised difference vegetation index (NDVI) and temporal changes evaluating displacement in the 2005 Porta Farm Zimbabwe clearances. Future near real time space-based monitoring would benefit human rights observers and networks.