This PDF file contains the front matter associated with SPIE Proceedings Volume 9229, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Future satellite instruments measuring urban NO₂ will need to have high spatio-temporal resolution in order to improve air quality model forecasts. However, the likely cost and data telemetry requirements for such instruments will be high with current techniques. In this work we propose a new retrieval algorithm for deriving tropospheric NO₂ slant column densities (SCDs) by DOAS fitting an earthshine reference spectrum measured over the Pacific to account for stratospheric NO₂, which would eliminate the need for a solar reference and simplify instrument and retrieval design. The retrieval is tested by fitting earthshine radiance spectra measured by the Ozone Measuring Instrument (OMI) during its spatial-zoom mode (nadir pixel size: 13 x 12 km²) and super-zoom mode (nadir pixel size: 13 x 3 km²) using a Pacific reference spectrum. Transects taken over urban areas showed that the retrieval appears to retrieve tropospheric NO₂ SCDs with good agreement with the operational L2 DOMINO product over regions with high NO_x emissions. The retrieval also appeared to supress across-track striping without the need for a posteriori correction and showed sensitivity to absorption due to sand and liquid water over deserts and oceans. Comparisons with operational-scale retrievals also showed improved SCD precision, if random noise is expected to be the cause of retrieval uncertainty.

The existing 2D cadastral systems worldwide cannot provide a proper registration and representation of the land ownership rights, restrictions and responsibilities in a 3D context, which appear in our complex urban environment. Ιn such instances, it may be necessary to consider the development of a 3D Cadastre in which proprietary rights acquire appropriate three-dimensional space both above and below conventional ground level. Such a system should contain the topology and the coordinates of the buildings' outlines and infrastructure. The augmented model can be formed as a full 3D Cadastre, a hybrid Cadastre or a 2D Cadastre with 3D tags. Each country has to contemplate which alternative is appropriate, depending on the specific situation, the legal framework and the available technical means. In order to generate a 3D model for cadastral purposes, a system is required which should be able to exploit and represent 3D data such as LiDAR, a remote sensing technology which acquires three-dimensional point clouds that describe the earth’s surface and the objects on it. LiDAR gives a direct representation of objects on the ground surface and measures their coordinates by analyzing the reflecting light. Moreover, it provides very accurate position and height information, although direct information about the objects’ geometrical shape is not conveyed. In this study, an experimental implementation of 3D Cadastre using LiDAR data is developed, in order to investigate if this information can satisfy the specifications that are set for the purposes of the Hellenic Cadastre. GIS tools have been used for analyzing DSM and true orthophotos of the study area. The results of this study are presented and evaluated in terms of usability and efficiency.

The present study investigates cloud microphysics properties using aircraft and satellite measurements. Cloud properties were drawn from data acquired both from in situ measurements with state of the art airborne instrumentation and from satellite products of the MODIS06 System. The used aircraft was ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research, property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania, which is specially equipped for this kind of research. The main tool of the airborne laboratory is a Cloud, Aerosol and Precipitation Spectrometer - CAPS (30 bins, 0.51- 50 μm). The data was recorded during two flights during the winter 2013-2014, over a flat region in the south-eastern part of Romania (between Bucharest and Constanta). The analysis of cloud particle size variations and cloud liquid water content provided by CAPS can explain cloud processes, and can also indicate the extent of aerosols effects on clouds. The results, such as cloud coverage and/or cloud types, microphysical parameters of aerosols on the one side and the cloud microphysics parameters obtained from aircraft flights on the other side, was used to illustrate the importance of microphysics cloud properties for including the radiative effects of clouds in the regional climate models.

The Joint Research Centre of the European Commission has developed Interpolated Meteorological Datasets available on a regular 25x25km grid both to the scientific community and the general public. Among others, the Interpolated Meteorological Datasets include daily maximum/minimum temperature, cumulated daily precipitation, evapotranspiration and wind speed. These datasets can be accessed through a web interface after a simple registration procedure. The Interpolated Meteorological Datasets also serve the Crop Growth Monitoring System (CGMS) at European level. The temporal coverage of the datasets is more than 30 years and the spatial coverage includes EU Member States, neighboring European countries, and the Mediterranean countries. The meteorological data are highly relevant for the development, implementation and assessment of a number of European Union (EU) policy areas: agriculture, soil protection, environment, agriculture, food security, energy, climate change. An online user survey has been carried out in order to assess the impact of the Interpolated Meteorological Datasets on research developments. More than 70% of the users have used the meteorological datasets for research purposes and more than 50% of the users have used those sources as main input for their models. The usefulness of the data scored more than 70% and it is interesting to note that around 25% of the users have published their scientific outputs based on the Interpolated Meteorological Datasets. Finally, the user feedback focuses mostly on improving the data distribution process as well as the visibility of the web platform.

Land consolidation is considered to be the most effective land management planning approach for controlling land fragmentation and hence improving agricultural efficiency. Land partitioning is a basic process of land consolidation that involves the subdivision of land into smaller sub-spaces subject to a number of constraints. This paper explains the development of a module called LandParcelS (Land Parcelling System) that integrates geographical information systems and a genetic algorithm to automate the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. This new module has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is carried out by guiding a Thiessen polygon process within ArcGIS and it is treated as a multiobjective problem. The results suggest that a step forward has been made in solving this complex spatial problem, although further research is needed to improve the algorithm. The contribution of this research extends land partitioning and space partitioning in general, since these approaches may have relevance to other spatial processes that involve single or multi-objective problems that could be solved in the future by spatial evolutionary algorithms.

Spatial data has become a critical issue in recent years. In the past years, nearly more than three quarters of databases, were related directly or indirectly to locations referring to physical features, which constitute the relevant aspects. Spatial data is necessary to identify or calculate the relationships between spatial objects when using spatial operators in programs or portals. Originally, calculations were conducted using Geographic Information System (GIS) programs on local computers. Subsequently, through the Internet, they formed a geospatial web, which is integrated into a discoverable collection of geographically related web standards and key features, and constitutes a global network of geospatial data that employs the World Wide Web to process textual data. In addition, the geospatial web is used to gather spatial data producers, resources, and users. Standards also constitute a critical dimension in further globalizing the idea of the geospatial web. The sensor web is an example of the real time service that the geospatial web can provide. Sensors around the world collect numerous types of data. The sensor web is a type of sensor network that is used for visualizing, calculating, and analyzing collected sensor data. Today, people use smart devices and systems more frequently because of the evolution of technology and have more than one mobile device. The considerable number of sensors and different types of data that are positioned around the world have driven the production of interoperable and platform-independent sensor web portals. The focus of such production has been on further developing the idea of an interoperable and interdependent sensor web of all devices that share and collect information. The other pivotal idea consists of encouraging people to use and send data voluntarily for numerous purposes with the some level of credibility. The principal goal is to connect mobile and non-mobile device in the sensor web platform together to operate for serving and collecting information from people.

In our time, the Geographic Information Systems (GIS) have become important tools, not only in the geosciences and environmental sciences, as well as virtually for all researches that require monitoring, planning or land management. The purpose of this paper was to develop a planning tool and decision making tool using AutoCAD Map software, ArcGIS and Google Earth with emphasis on the investigation of the suitability of forest roads’ mapping and the range of its implementation in Greece in prefecture level. Integrating spatial information into a database makes data available throughout the organization; improving quality, productivity, and data management. Also working in such an environment, you can: Access and edit information, integrate and analyze data and communicate effectively. To select desirable information such as forest road network in a very early stage in the planning of silviculture operations, for example before the planning of the harvest is carried out. The software programs that were used were AutoCAD Map for the export in shape files for the GPS data, and ArcGIS in shape files (ArcGlobe), while Google Earth with KML files (Keyhole Markup Language) in order to better visualize and evaluate existing conditions, design in a real-world context and exchange information with government agencies, utilities, and contractors in both CAD and GIS data formats. The automation of the updating procedure and transfer of any files between agencies-departments is one of the main tasks of the integrated GIS-tool among the others should be addressed.

Landslide phenomena constitute a major geological hazard in Greece and especially in the western part of the country as a result of anthropogenic activities, growing urbanization and uncontrolled land – use. More frequent triggering events and increased susceptibility of the ground surface to instabilities as consequence of climate change impacts (continued deforestation mainly due to the devastating forest wildfires and extreme meteorological events) have also increased the landslide risk. The studied landslide occurrence named “Platanos” has been selected within the framework of “Landslide Vulnerability Model – LAVMO” project that aims at creating a persistently updated electronic platform assessing risks related with landslides. It is a coastal area situated between Korinthos and Patras at the northwestern part of the elongated graben of the Corinth Gulf. The paper presents the combined use of geological-geotechnical insitu data, remote sensing data and GIS techniques for the evaluation of a subsurface geological model. High accuracy Digital Surface Model (DSM), airphotos mosaic and satellite data, with a spatial resolution of 0.5m were used for an othophoto base map compilation of the study area. Geological – geotechnical data obtained from exploratory boreholes were digitized and implemented in a GIS platform with engineering geological maps for a three – dimensional subsurface model evaluation. This model is provided for being combined with inclinometer measurements for sliding surface location through the instability zone.

The Rethymnon Prefecture in the Crete Island, Greece, suffers from severe landslide phenomena due to its complicated geological structure with intensive tectonic fragmentation. This research applies the analytical hierarchy process (AHP) method for landslide susceptibility analysis in the Potamon watershed located inside the Rethymnon Prefecture. The following landslide conditioning factors were selected: geological formations, slope angle, aspect, curvature, distance to faults, distance to roads, distance to rivers, land use types and normalized difference vegetation index (NDVI) extracted from a Landsat-ETM satellite image. A landslide susceptibility map is prepared on the basis of available digital data. The landslide susceptibility map is validated through the comparison of the results with the already documented landslides occurring in the study area. The results indicate that the predicted susceptibility map is in good agreement with the past landslide occurrences, and, therefore, the map is trustworthy for future land-use planning of the study watershed.

Although high resolution orthoimages have been the most popular photogrammetric derivative, the cost of orthoimaging production remains high for areas where access is difficult. This paper presents a procedure for a cost effective orthoimage production, from data (digital images, GCPs and DTMs) derived solely from Airborne Laser Scanner systems. ALS systems are designed to produce a highly accurate 3D point cloud, which can be easily rasterized in an accurate, high resolution and dense DEM. Applying a hillshade effect on that dense DEM, one can visualize the objects with great detail and thus measure 3D coordinates for points to be used as GCPs. Modern ALS systems incorporate medium format digital cameras with high resolution imaging abilities. As no ground surveying is needed, the production of high end orthoimages may be performed even in regions that are inaccessible or difficult to access, such as remote islets and mountain tops. A workflow is proposed for the production of orthoimages from low density (2.5 points/m²) laser data using an ALS II-50 system and its medium format RCD105 digital camera. The area of the case study is the northern section of the Greek island Milos. Utilizing automated processes, a series of quality control tasks and a preprocessing of the data is performed. During the data processing, an interpolation of the LiDAR data’s first returns is performed, in order to rasterize a high resolution (1m) DEM. The orthorectification process is been performed with the same DEM, leading to an orthoimage with a planimetric accuracy of 1m and minimum geometric distortions. The cost analysis of the applied procedure has proved that the method is less cost demanding compared to the usual orhoimage production methods.

The LUCAS (Land Use/Cover Area frame Statistical Survey) database currently contains about 20,000 topsoil samples of 15 soil properties. It is the largest harmonised soil survey field database currently available for Europe. Soil Organic Carbon (SOC) levels have been successfully determined using both proximal and airborne/spaceborne reflectance spectroscopy. In this paper, Cyprus was selected as a study area for estimating SOC content from multispectral remotely sensed data. The estimation of SOC was derived by comparing field measurements with a set of spatially exhaustive covariates, including DEM-derived terrain features, MODIS Vegetation indices (16 days) and Landsat ETM+ data. In particular, the SOC levels in the LUCAS database were compared with the covariate values in the collocated pixels and their eight surrounding neighbours. The regression model adopted made use of Support Vector Machines (SVM) regression analysis. The SVM regression proved to be very efficient in mapping SOC with an R² fitting of 0.81 and an R² k-fold cross-validation of 0.68. This study proves that the inference of SOC levels is possible at regional or continental scales using available remote sensing and Earth observation data.

Land subsidence is a major worldwide hazard, and causes many problems including: damage to public facilities such as bridges, roads, railways, electric power lines, underground pipes; damage to private and public buildings; and in some cases of low-lying land, can increase the risk of coastal flooding from storm surges and rising sea-levels. The island of Cyprus is famous for its complex geology, particularly in the southwest part of the island. Deposits of massive breccias (melange) are widely exposed in the Paphos District situated between the Troodos Mountains and the sea. These deposits are rich in clay minerals that are prone to landslide phenomena. With its global coverage and all-weather imaging capability, Interferometric SAR (InSAR) is revolutionizing our ability to image the Earth’s surface and the evolution of its shape over time. In this paper, an advanced InSAR time series technique, InSAR TS + AEM, has been employed to analysed C-band ERS and Envisat data collected over southwest Cyprus during the period from 1992 to 2010. Our InSAR time series results suggest that: (1) a total number of 274,619 coherent pixels with a density of 46 points per squared km were detected in the area of interest; and (2) clear surface displacements can be observed in several areas. The combination of archived ESA SAR datasets allows a long record (~18 years) of historic deformation to be measured over a large region. Ultimately this should help inform land managers in assessing land subsidence and planning appropriate remedial measures.

Continuous advances in unmanned aerial vehicles (UAV) and the increased complexity of their applications raise the demand for improved data acquisition systems (DAQ). These improvements may comprise low power consumption, low volume and weight, robustness, modularity and capability to interface with various sensors and peripherals while maintaining the high sampling rates and processing speeds. Such a system has been designed and developed and is currently integrated on the Autonomous Flying Platforms for Atmospheric and Earth Surface Observations (APAESO/NEA-YΠOΔOMH/NEKΠ/0308/09); however, it can be easily adapted to any UAV or any other mobile vehicle. The system consists of a single-board computer with a dual-core processor, rugged surface-mount memory and storage device, analog and digital input-output ports and many other peripherals that enhance its connectivity with various sensors, imagers and on-board devices. The system is powered by a high efficiency power supply board. Additional boards such as frame-grabbers, differential global positioning system (DGPS) satellite receivers, general packet radio service (3G-4G-GPRS) modems for communication redundancy have been interfaced to the core system and are used whenever there is a mission need. The onboard DAQ system can be preprogrammed for automatic data acquisition or it can be remotely operated during the flight from the ground control station (GCS) using a graphical user interface (GUI) which has been developed and will also be presented in this paper. The unique design of the GUI and the DAQ system enables the synchronized acquisition of a variety of scientific and UAV flight data in a single core location. The new DAQ system and the GUI have been successfully utilized in several scientific UAV missions. In conclusion, the novel DAQ system provides the UAV and the remote-sensing community with a new tool capable of reliably acquiring, processing, storing and transmitting data from any sensor integrated on an UAV.

Under the European Union’s Thematic Strategy for Soil Protection, the European Commission’s Directorate-General for the Environment (DG Environment) has identified the mitigation of soil losses by erosion as a priority area. Policy makers call for an overall assessment of soil erosion in their geographical area of interest. They have asked that risk areas for soil erosion be mapped under present land use and climate conditions, and that appropriate measures be taken to control erosion within the legal and social context of natural resource management. Remote sensing data help to better assessment of factors that control erosion, such as vegetation coverage, slope length and slope angle. In this context, the data availability of remote sensing data during the past decade facilitates the more precise estimation of soil erosion risk. Following the principles of the Universal Soil Loss Equation (USLE), various options to calculate vegetative cover management (C-factor) have been investigated. The use of the CORINE Land Cover dataset in combination with lookup table values taken from the literature is presented as an option that has the advantage of a coherent input dataset but with the drawback of static input. Recent developments in the Copernicus programme have made detailed datasets available on land cover, leaf area index and base soil characteristics. These dynamic datasets allow for seasonal estimates of vegetation coverage, and their application in the G2 soil erosion model which represents a recent approach to the seasonal monitoring of soil erosion. The use of phenological datasets and the LUCAS land use/cover survey are proposed as auxiliary information in the selection of the best methodology.

The objective of this work is the investigation of the specific relationships between actual evapotranspiration based crop coefficients and vegetation indices adapted to Karla Watershed, central Greece. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) and ET_rF values during the growing season of 2012. The methodology was developed using medium resolution Landsat 7 ETM+ images. Meteorological data from the archive of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) have also been used. Fields with cotton, wheat, alfalfa, corn and sugar beets are utilized. During the same period, in-situ radiometric measurements were generated with the use of the field spectro-radiometer GER1500 giving specific spectral signatures for each crop. Filtering of reflectance values with the use of relative spectral responses (RSR) gives the opportunity to match the spectral measurements with Landsat ETM+ bands and compute VI like NDVI, SAVI, EVI and EVI2 using the same remote sensing formulas as the ETM+ conventional procedures. New relationships are derived and NDVI, SAVI, EVI and EVI2 are tested separately for each crop. Special attention is given to the constant L inside the SAVI relationship. The main advantage of the new approach is that is more crop specific and it less time consuming because there is no need for atmospheric correction.

Satellite remote sensing techniques play an important role in crop identification, acreage and production estimation, disease and stress detection, and soil and water resources characterization because they provide spatially explicit information and access to remote locations. The main objective of the study is to highlight the potential of using remote sensing techniques in the research field of water management, especially for “water footprint” assessment. In this paper, several vegetation indices (NDVI, NDWI, etc) and biophysical variables (LAI, fAPAR) are key variables to potentially be estimated by remote sensing and used in water footprint studies. The combination of these input parameters brings several limitations regarding the discrepancies in temporal and spatial resolution and data availability, which are described and discussed in detail. MODIS, Landsat, SPOT Vegetation and Meteosat data were used in order to estimate evapotranspiration and vegetation indices. The results of this study show the usefulness of satellite data for water footprint assessment and were obtained by the Remote Sensing Working Group in the framework of the ESSEM COST Action ES1106, “Assessment of EUROpean AGRIculture WATer use and trade under climate change” (EUROAGRIWAT).

Water allocation to crops has always been of great importance in agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). The methodology set in this paper refers to COST action ES1106 (Agri-Wat) for determining crop water requirements as part of the water footprint and virtual water-trade.

It is estimated that more than 20,000 natural lakes are found across China. Most of these lakes are undergoing eutrophication or other severe environmental nuisances owing to natural and/or anthropogenic processes. In order to prevent or to minimize such damaging impacts, and to ascertain a proper quality management of the lake water and the associated fish resources, it is required to have access to up-to-date, accurate, and relevant data and information on the aquatic ecosystem in a timely manner. The “Dragon 3” project, supported by the European Space Agency, is focusing on Xin’an river watershed and investigates the impact of water quality and land cover/use change on the spatio-temporal distribution of the fishing grounds in Qiandao Lake. In this paper, the land use changes derived from satellite images is presented. Initially, Landsat 5 TM and Landsat 8 LDCM have been analyzed for the last 20 years in the vicinity of the Xin’an river watershed. Following the radiometric calibration of the images, several pixel-base classification algorithms have been evaluated including Spectral Angle Mapper (SAM), Support Vector Machine (SVM) as well Neural Network (NN). As it was found using the multi-temporal satellite imagery, the SVM algorithm was able to give high kappa accuracy estimated at around 0.90. In addition EO-Hyperion images over the western part of the Xin’an River were evaluated using hyperspectral vegetation indices as well using linear spectral un-mixing techniques. In addition, ENVISAT radar images have been evaluated in terms of land use change. The final outcomes indicate a significant urban expansion in the surrounding area of the Xin’an River which impacts the water quality investigation. Finally, a Landsat image was processed in order to estimate the Trophic State Index (TSI) values over the water bodies and the highest values were observed over the Xin’an river watershed and more specifically for the urban sites.

This paper aims to examine how CAMA, GIS and Remote Sensing are integrated to assist property taxation. Real property tax apart from its fiscal dimension is directly linked to geographic location. The value of the land and other immovable features such as buildings and structures is determined from specific parameters. All these immovable assets are visible and have specific geographic location & coordinates, materials, occupied area, land-use & utility, ownership & occupancy status and finally a specific value (ad valorem property taxation system) according to which the property tax is levied to taxpayers. Of high importance in the tax imposing procedure is that the use of CAMA, GIS and Remote Sensing tools is capable of providing effective and efficient collection of this property value determining data. Furthermore, these tools can track changes during a property’s lifecycle such parcel subdivision into plots, demolition of a building and development of a new one or track a change in the planning zone. The integration of these systems also supports a full range of business processes on revenue mobilization ranging from billing to taxpayers objections management.

Efficient management of the territory requires today the availability of comprehensive geographical data, accurate and up to date, supported by powerful databases. In this context, remote sensing data are used for a variety of applications related to urban areas; some examples are land use/cover mapping, urban growth and soil sealing evaluation, detection of green areas, updating of existing maps, energy applications and detection and characterization of buildings. This work aims to highlight how different geomatic techniques and data acquired from heterogeneous surveys can be today used together for producing or updating a digital cartography inside a GIS. The study has been conducted in the urban area of Bologna, Emilia-Romagna region, located in the North of Italy. A high resolution WorldView-2 satellite image and the DSM/DTM, obtained by airborne LiDAR, have been used to obtain a vector layer of the buildings. In particular, to distinguish the buildings among all the elements present in the study area, such as roads, trees, vegetated areas, etc., an object-oriented classification has been performed. This approach, working on groups of pixels (image objects), allows to expand the information content of the basic unit of classification. Therefore, features such as shape, texture and contextual information, coupled with spectral characteristics, potentially allow cartographers to generate products that are competitive, in terms of thematic contents, with those derived from the photo-interpretation. A first application described in this work is to perform a quick change analysis procedure based on the results of the classification compared to an existing numerical cartographic base or a previous classification.

Since 1960 most of the coastal area cites across the Mediterranean Sea concentrates people due mass immigration of people from the rural to urban areas. The extensive tourism development especially across the coastal areas, create demand of infrastructures and new work positions and intensive pressure to the environment. The new spirit of the globalization creates movability of people and goods around the word. The free transfer of people from countries with big population and low economical wealth, which are moved to areas where they can work. All the above generate demands of labor and Paphos is one of these areas where during the last decades was transformed from a small agriculture village in one excellent tourist destination. Across the coastal areas big tourist infrastructure was built and lot of different people travel from all areas around the word especially during the summer months. All these generate continuous changes to the environment, to the people and the society. The globalization of the universe commerce and the free transfer of goods and people modify the community stratification. The inflow of agricultures products from third countries reduces the local production and generates degradation and desertification of the rural areas. The periodical variation of the population of the area during the summer and winter periods affect to the environment. The increment demand of sources (water, energy and food) during the summer months pressurize the coastal strip area. By estimating a ratio of inflows by the outflows of goods, people and services of the study area and a ratio of the tourists by the local population, a general index can by arise which will clarify the effects on the environment on the study area. This paper presents the results obtained by this study by examining the effects of tourism on land cover and effects on quality of life for the Paphos area in Cyprus. The authors explores the potential of blending in the sustainability study the use of remote sensing especially on the land-cover effects.

Urban areas can be considered as complex and dynamic systems, the study of which requires broad and reliable information. The required information must be improved and updated and can be collected by different sources, including photogrammetry and remote sensing. The continuous advances of these scientific disciplines in acquisition and processing of their data, but also their synergy with other modern methods and technologies (as laser scanning), make their contribution on urban areas studies (including axes of urban wide surroundings) particularly interesting. This paper refers to the above and includes a relevant example of the city of Thessaloniki, using high resolution satellite data.

The use of cost-effective Unmanned Aerial Vehicles (UAVs) are becoming common tools for researchers for numerous applications. Since UAVs vary in size and payload capacity, various sensors can be installed onto the platform. UAVs can be a efficient and low cost resource for remote sensing applications. Different remote sensing techniques can be used with UAVs, such as field spectroscopy, multi-spectral cameras, infrared cameras and thermal cameras. This paper examines several UAV platforms that were used by the Cyprus University of Technology for remote sensing applications in Cyprus. Using these UAV systems for different applications, the advantages and disadvantages were examined and discussed.

This paper presents a Geodesign tool supporting collaborative decision-making in Strategic Environmental Assessment of Local Land-use Planning. The tool consists of a Planning Support Systems implementing a spatial DPSIR model, which allows the real time interaction among plan alternatives design, impact evaluation and documentation. The Planning Support System demonstrates the opportunity for innovation in spatial planning, design and governance given by the availability of Spatial Data Infrastructures. The study proposed in this paper concerns the Sardinia (Italy) case study, but the results can be generalized to other regions in Europe and worldwide.

During the last decades most of the coastal zones across the Mediterranean Sea concentrates population around polescities owing to the mass movement of people from the rural areas to urban areas. The extensive tourism development across the coast generates demand of new work positions and pressurizes the environment. The economic development increase the natural capital of the study areas increase the covered with buildings and infrastructures areas and as a consequence reduce the quality of life. All the above effects modify the density of the buildings and infrastructures, push and eliminate the free green covered areas and other open spaces. In order to measure the effects on the environment and the quality of life a composite index is developed which arises using combined indices using economical, social and environmental criteria. The above components give a realistic indicator of the effects on the environment. This unique index arises as a function of the ratios of a per capital income a ratio of cover area by the uncovered area and the density of people per unit area. Usually when the wealth is increased the demand of energy and goods also increased and the damage on environment becomes bigger. This paper explores how the application of sustainability indices can be used as a tool to assess the quality of life. The use of GIS and remote sensing is highlighted to support the application of the existing sustainability indices.

Landsat archives (made accessible by USGS at no charge since 2011) have made available to the scientific community a large amount of satellite multispectral images, providing new opportunities for environmental information, such as the analysis of land use/cover changes, which represent important tools for planning and sustainable land management. Processing a time series images, the creation of land cover maps has been improved in order to analyze phenomena such as the soil sealing. The main topic of this work is in fact the detection of roads and buildings construction or everything that involve soil removing. This subject is highly relevant, given the impact of the phenomenon on land use planning, environmental sustainability, agricultural policies and urban runoff. The analysis, still in progress, has been applied to Bologna Province (Emilia-Romagna Region, Italy) that covers 3703 Km². This area is strongly urbanized: 8,9% of the total surface is sealed against a national value of 6,7%, with the soil sealing rate which has been defined from recent studies as the fourth Italian value in the 2001/2011 period. Other information available for this territory derive from CORINE Land Cover and Copernicus Projects. In the first one, the minimum mapping unit is 25 ha and the one for change is 5 ha; these values are too large for an accurate detection of the soil sealing dynamics. On the other hand, the Copernicus Project provides an imperviousness layer with a better resolution (20x20 m²), but its maps start from 2006. Therefore, the potential of multispectral remote sensing analysis over large areas and the multitemporal Landsat availability have been combined for a better knowledge about land cover changes. For this work, Landsat 5 and Landsat 8 images have been acquired between 1987 and 2013, according to basic requirements as low cloud cover and a common acquisition season (summer). A supervised pixel-based classification has been performed, with maximum likelihood algorithm. Due to landscape heterogeneity, classification has been improved with auxiliary data, such as NDVI. Therefore, the obtained maps have been compared with a post-classification change detection procedure in order to quantify land use changes, with particular attention to the soil sealing increase.

To develop an efficient system for tea production management, the first and foremost requirement is quick availability of accurate data. Manual decision making takes unusually long time even with the most sophisticated analytical techniques. Moreover, as geographical spread of tea gardens are huge and sometimes exceeds few hundred hectares, getting information about the entire garden through conventional methods would be time consuming. Quick decision making based on quality data at section (a garden unit varying in area) level in a tea garden can enhance tea production. Geoinformatics and spatial analysis algorithms provide a great opportunity to gather information of unknown locations in a tea plantation based on some known locations. The present work demonstrates the application of an integrated Wireless Sensors Network (WSN) system associated with GPS and GIS to achieve the goal of Smart Agriculture. In this study a portable WSN system has been developed for instant data generation on soil physico-chemical properties and provide decision support for tea plantation management. Soil pH, soil moisture and soil temperature were collected in selected locations in a tea garden and plotted on digital garden maps based on their GPS locations. Suitable interpolation algorithms were applied on the collected soil data to generate information about the soil properties in entire plantation. An empirical equation is being developed for each soil parameter to compensate the errors in their predicted values based on values in the sample locations. The present system is an attempt towards achieving the goal of implementation of precision agriculture in tea plantation management.

The Department of Meteorology is the organization designated by the Civil Aviation Department and by the National Supervisory Authority of the Republic of Cyprus, as an air navigation service provider, based on the regulations of the Single European Sky. Department of Meteorology holds and maintains also an ISO: 9001/2008, Quality System, for the provision of meteorological and climatological services to aeronautic and maritime community, but also to the general public. In order to fulfill its obligations the Department of Meteorology customs the rather dense meteorological stations network, with long historical data series, installed and maintained by the Department, in parallel with modelling and Numerical Weather Prediction (NWP), along with training and gaining of expertise. Among the available instruments in the community of meteorologists is the meteorological radar, a basic tool for the needs of very short/short range forecasting (nowcasting). The Department of Meteorology installed in the mid 90’s a C-band radar over «Throni» location and expanded its horizons in nowcasting, aviation safety and warnings issuance. The radar has undergone several upgrades but today technology has over passed its rather old technology. At the present the Department of Meteorology is in the process of buying Meteorological Radar Services as a result of a public procurement procedure. Two networked X-band meteorological radar will be installed (the project now is in the phase of infrastructure establishment while the hardware is in the process of assemble), and maintained from Space Hellas (the contractor) for a 13 years’ time period. The present article must be faced as a review article of the efforts of the Department of Meteorology to support its weather forecasters with data from meteorological radar.

The deterioration of structures due to corrosion is probably the most significant factor for their damaging condition and the need for maintenance. Corrosion mechanisms depend on the environmental conditions and the geographic characteristics of the area. In this paper a condition assessment methodology is presented through an application on a deteriorated building in Cyprus. The methodology's starting point is the collection of information through Google Earth for classification of buildings in regions based on their environmental and geographic characteristics. Through this screening process, buildings in each defined region are selected for evaluation. The following steps of the methodology include testing on selected structural members for the estimation of the compression strength and the depth of carbonation. The results of the case study, are used from the responsible engineer to evaluate the current condition of the building regarding its structural integrity and the effect of corrosion. The testing data showed that the current building strength is lower than the code's requirements and that carbonation induced corrosion must be addressed to prevent further damage.

Remote sensing techniques development have provided the opportunity for optimizing yields in the agricultural procedure and moreover to predict the forthcoming yield. Yield prediction plays a vital role in Agricultural Policy and provides useful data to policy makers. In this context, crop and soil parameters along with NDVI index which are valuable sources of information have been elaborated statistically to test if a) Durum wheat yield can be predicted and b) when is the actual time-window to predict the yield in the district of Paphos, where Durum wheat is the basic cultivation and supports the rural economy of the area. 15 plots cultivated with Durum wheat from the Agricultural Research Institute of Cyprus for research purposes, in the area of interest, have been under observation for three years to derive the necessary data. Statistical and remote sensing techniques were then applied to derive and map a model that can predict yield of Durum wheat in this area. Indeed the semi-empirical model developed for this purpose, with very high correlation coefficient R2=0.886, has shown in practice that can predict yields very good. Students T test has revealed that predicted values and real values of yield have no statistically significant difference. The developed model can and will be further elaborated with more parameters and applied for other crops in the near future.

The Polyphyto Hydroelectric Project was constructed in 1974 and it has been operating since on the Aliakmonas River, Kozani prefecture, by the Greek Public Power Corporation. The construction of the Ilarion Hydroelectric Project, upstream from the Polyphyto Reservoir, has been recently completed and will start operating in the near future. Apart from hydroelectric power production, the Polyphyto reservoir provides flood control to the areas below the Polyphyto dam. It is also used to manage water provision to the city of Thessaloniki and adjacent agricultural plain, providing at the same time cooling water to the Thermo Electric Projects in Ptolemaida. The Polyphyto reservoir has potential for further development as an economic fulcrum to the region in which is located. The Kozani and Servia–Velvendos Municipalities have proceeded to the construction of several touristic, nautical – athletic and fishing projects. In order to promote such developments, while preserving the artificial wetland, flora and fauna of the Polyphyto Reservoir, it is important to reduce the fluctuation of the reservoir elevation which according to its technical characteristics is 21m. The aim of this paper is to propose the combined operation of the two Hydroelectric Project reservoirs to satisfy all the present Polyphyto Hydroelectric Project functions and to reduce the annual fluctuation of the Polyphyto Reservoir. The HEC-5, Version 8 / 1998 computer model was used in our calculations, as developed by the Hydrologic Engineering Center (HEC) of the US Army Corps of Engineers for reservoir operation simulation. Five possible operation scenarios are tested in this paper to show that the present fluctuation of the Polyphyto Reservoir can be reduced, with some limitations, except during dry weather periods.

Remote sensing technology has been widely used for monitoring water quality parameters such as suspended solids (turbidity), Secchi Disk, chlorophyll, and phosphorus. Suspended matter plays an important role in water quality management of several inland- (such as lakes and reservoirs) and coastal-water bodies and can be used to estimate the Trophic State Index of different water bodies. However synoptic information on water quality parameters at a systematic basis is difficult to be obtained from routine in situ monitoring programs since suspended matter, phosphorus, and chlorophyll are spatially inhomogeneous parameters. To meet this need, an integrated use of Landsat satellite images, in situ data and water quality models can be used. Several algorithms were developed at a previous stage using water quality data collected during the in situ sampling campaigns taken place in 2010 and 2011 over Asprokremmos Reservoir (Paphos District) for the assessment of turbidity, Secchi Disk, and Trophic State Index fluctuations using spectroradiometric data. Remotely sensed data were atmospherically corrected and water quality models for the estimation of both the turbidity- and Secchi Disk- concentrations were further calibrated using in situ data for the case of Asprokremmos Reservoir and several coastal over Cyprus coastline (Limassol and Paphos District Areas). This methodology can be used as a supporting monitoring tool for water management authorities “gaining” additional information regarding the spatial and temporal alterations of the turbidity- and Secchi Disk- concentrations and the Trophic State Index values over several Case II water bodies.

Accurate assessment of water use is an important issue in a globally changing climate and environment, where water is becoming a scarce but essential resource. The concept ‘Water Footprint’ (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. This indicator provides valuable information for a global assessment of how water resources are used. Remote sensing (RS) provides physically-based, worldwide, and consistent spatial information over space and time, and has been used in hydrological applications in order to estimate relevant variables at different temporal and spatial scales. The paper focuses on exploring and exploiting the potential of using RS techniques and data for WF assessment in agriculture. Based on recent papers initiated in this research topic the investigation focuses on how variables needed in the calculation of water footprint are obtained (based on non RS and on RS approaches), on identifying the inputs required for estimating the WF of crops and whether it is feasible to integrate various RS approaches. The results of this study demonstrate the usefulness of satellite data for water footprint assessment, which were obtained by the Remote Sensing Working Group in the framework of the ESSEM COST Action ES1106, “Assessment of EUROpean AGRIculture WATer use and trade under climate change” (EURO-AGRIWAT).

One of the main scientific goals of the COST Action ES1106 (“Assessment of European Agriculture Water use and Trade under Climate Change” EURO-AGRIWAT) is the analysis of the global water footprint (WF) in agriculture and virtual water trade (VWT). The starting point for further activities is analyses and inventory of data and tools which could be helpful for WF and WFT assessments. Evaporation values (ET) are crucial for agriculture where estimates of water reserves available for crops are the basis for scheduling the time and intensity of irrigation, yield prognoses, etc. Detail evapotranspiration data are, therefore, of essential value. However, stations performing direct measurements of evapotranspiration are very scarcely distributed in Poland for which reason the interpolation of the data is necessarily biased. Hence, evapotranspiration values are calculated using indirect methods (usually empirical formulas). Data from geostationary meteorological satellites are used operationally for determination of evapotranspiration with good spatial and temporal resolution (e.g. Land-SAF product). Study of relation between evapotranspiration values determined with use of satellite data and calculated using Penman-Monteith formula was performed for the study area in Poland. Daily values and cumulated (i.e. decadal, monthly and yearly) values were analyzed to determine quality and possible added value of the satellite product. Relation between reference ET and actual ET in two consecutive years was discussed, both for whole test area and individual stations, taking into account land use and possible water deficit in the root region, represented by H-SAF soil wetness index product. The differences were presented and discussed.

The traditional archaeological surveys have been shifted through time from single to multi-disciplinary studies of material remains based on the advantages of new technologies. Remote Sensing (RS) techniques in the last years have been proven to be an essential tool for the detection of un-excavated sites as well an important tool for the better understanding of the landscape of a site. Although the use of such technologies is widely accepted by the archaeological community, the practical use of these RS is not equally adopted. This phenomenon has been dramatically increased though the last years, and therefore “two-speed archaeology” is more evidence than before: Archaeologists in technologically developed countries may fully exploit RS technologies while in following countries this is still limited due to the lack of funding or equipment (e.g. special RS airplanes). Despite the fact that the above phenomenon is also frequently observed in other scientific fields, when this comes to archaeology then the problem is of paramount importance for the science itself: how can we better understand human past and old civilizations –which goes beyond the geographical limits of modern countries- when the data quality is fragmental though out the world? Extensive field spectroscopy measurements contacted in simulated archaeological environments have identified spectral regions suitable for the detection of buried archaeological research. Such characteristics can be implemented into a specially designed satellite sensor in order to support archaeological research. The potential use of such sensor will be a break though for the science of archaeology. The sensor can fully exploit the advantages of space technology and therefore can be used to support archaeological surveys in pan-European level as well outside Europe. The sensor will be able to provide a better inside look to lost landscapes and archaeological remains and therefore providing to archaeologists new windows to their research. It is a time to design a full experimental study by combining field spectroscopy, UAV and other auxiliary tools such as sun-photometers for suggesting an ideal new space sensor for archaeology applications.

One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.

Curating boats can be difficult. They are complex structures, often demanding to conserve whether in or out of the water; they are usually large, difficult to move on land, and demanding of gallery space. Communicating life on board to a visiting public in the terra firma context of a museum can be difficult. Boats in their native environment are inherently dynamic artifacts. In a museum they can be static and divorced from the maritime context that might inspire engagement. New technologies offer new approaches to these problems. 3D laser scanning and digital modeling offers museums a multifaceted means of recording, monitoring, studying and communicating watercraft in their care. In this paper we describe the application of 3D laser scanning and subsequent digital modeling. Laser scans were further developed using computer-generated imagery (CGI) modeling techniques to produce photorealistic 3D digital models for development into interactive, media-based museum displays. The scans were also used to generate 2D naval lines and orthographic drawings as a lasting curatorial record of the dhows held by the National Museum of Qatar.

Semi-distributed physically-based models are well established and widely used for hydrological modeling due to their ability to capture the spatial variability of the watershed among land use, soil types and topographic characteristics; and to characterize distributed inputs in different areas within the watershed. They offer a more realistic watershed representation, allowing for better predictions of the behavior of a hydrologic system, based on novel climatic inputs. Watershed subdivision and the question of an optimum discretization level is an important issue in distributed hydrological modeling as it affects the setup of hydrologic models and has the potential to affect model output. Soil and Water Assessment Tool (SWAT), a semi-distributed physically-based hydrologic model, divides the watershed into smaller subwatersheds which are further subdivided into HRUs consisting of homogeneous land use, soil, slope and management characteristics. The number and size of HRUs is calculated based on user-specified land use, soil and slope thresholds. This study investigates the impact of the slope threshold in the HRU definition on flow predictions and hydrologic mass balance, applied on three subwatersheds of the Evrotas River Basin (1348km²), a mountainous catchment in Peloponnesus, Greece. The catchment is delineated using a 90m DEM and then divided into 150 subwatersheds. The model was calibrated, and simulations were performed on three subwatersheds using a range of 5%- 30% slope thresholds for the HRU definition while land use and soil thresholds remained the same. Results showed that the coarser delineation (13 HRUs) produced a very accurate hydrologic mass balance and satisfactory flow predictions (RSR, PBIAS, NSE) while, finer delineations (21 HRUs) produces inaccurate hydrologic mass balance (54.49% lower surface runoff) but more accurate flow predictions (RSR, PBIAS, NSE).

ArcGIS^® is a well known standard on Geographical Information Systems, used over the years for various remote sensing procedures. During the last decade, Rixen (2003) and Azcarate (2011) presented the DINEOF (Data Interpolating Empirical Orthogonal Functions) method, a EOF-based technique to reconstruct missing data in satellite images. The recent results of the DINEOF method in various experimental trials (Wang and Liu, 2013; Nikolaidis et al., 2013;2014) showed that this computationally affordable method leads to effective reconstruction of missing data from geophysical fields, such as chlorophyll-a, sea surface temperatures or salinities and geophysical fields derived from satellite data. Implementing the method in a GIS system will lead to a complete and integrated approach, enhancing its applicability. The inclusion of statistical tools within the GIS, will multiply the effectiveness, providing interoperability with other sources in the same application environment. This may be especially useful in studies where various different kinds of data are of interest. For this purpose, we have implemented a new GIS toolbox that aims at automating the usage of the algorithm, incorporating the DINEOF codes provided by GHER (GeoHydrodynamics and Environment Research Group of University of Liege) into the ArcGIS^® as an example for the effectiveness and simplicity of the toolbox. A case-study of filling the chlorophyll-a missing data in the Mediterranean Sea area, for a 16-day period is considered. More specifically, we focus on chlorophyll-a MODIS satellite data collected by CNR-ISAC (Italian National Research Council, Institute of Atmospheric Sciences and Climate), from the respective products of MyOcean2 organization, that provides free online access to Level 3, with 1 km resolution. All the daily products with an initial level of only 27% data coverage were successfully reconstructed over the Mediterranean Sea.

Ocean mesoscale spiral eddies is a phenomenon that came apparent in the last 50 years but until today there are many questions yet to be answered about their formation, distribution and correlation to the dynamical processes on the sea surface. Main objective of the present paper is to provide an extensive analysis on the occurrence and statistics of smallmesoscale eddies over the Aegean Sea using synthetic aperture radar (SAR) images. The study area is characterized from unique hydro-dynamical and topographical conditions that give another aspect on the phenomenon. Present study based on 169 medium resolution (WSM) ENVISAT ASAR images acquired in 2011. As a result of the analysis 192 eddies formations were detected. The majority of those eddies were visualized due to the presence of surfactant films (black eddies) on sea surface and majority of them were cyclonically rotating. The diameter of the observed formations of eddies was within 1 to 16 km. The detected eddies were classified by categories depending on their shape and their generation mechanism. Seasonal and spatial distribution is presented, in order to understand their variability compared with the upper surface circulation. The value of the baroclinic Rossby radius of deformation was used for the discrimination of wind driven or geostrophic balanced spiral eddies. Though most of the observed formations seem to be wind driven, an important correlation with the upper circulation of the Aegean Sea is shown.

This research designs and presents the development and application of the GAVOS algorithm. The algorithm is designed under the framework of visibility research, to calculate the probability of seeing from a ViewPoint to a TargetPoint, taking into account the uncertainty existing in the elevations of Digital Elevation Models (DEMs), that is used. The algorithm is a Decision Support tool, that will help specialists of visibility analysis, not to take “hard” decision, but to take “soft” probabilistic ones, accompanied by their confidence level. It can be embodied within a Decision Support System.

Climatic changes cause temperature rise and thus increase the risk of forest fires. In Greece the forests with the greatest risk to fire are usually those located near residential and tourist areas where there are major pressures on land use changes, while there are no currently guaranteed cadastral maps and defined title deeds because of the lack of National and Forest Cadastre. In these areas the deliberate causes of forest fires are at a percentage more than 50%. This study focuses on the forest opening up model concerning both the prevention and suppression of forest fires. The most urgent interventions that can be done after the fire destructions is also studied in relation to soil protection constructions, in order to minimize the erosion and the torrential conditions. Digital orthophotos were used in order to produce and analyze spatial data using Geographical Information Systems (GIS). Initially, Digital Elevation Models were generated, based on photogrammetry and forest areas as well as the forest road network were mapped. Road density, road distance, skidding distance and the opening up percentage were accurately measured for a forest complex. Finally, conclusions and suggestions have been drawn about the environmental compatibility of forest protection and wood harvesting works. In particular the contribution of modern technologies such as digital photogrammetry, remote sensing and Geographical Information Systems is very important, allowing reliable, effective and fast process of spatial analysis contributing to a successful planning of opening up works and fire protection.

The possibilities of airborne laser scanning as a tool for visualisation of micro topology have been known for some decades. Indeed, in the archaeological field a lot of new features have been detected or reconfirmed. However, the task to map manually the enormous amount of features is time consuming and costly. Therefore, there is a need for automation. In this paper four workflows of visualisation and (semi) automatic extraction of (historical) roads and paths are compared. It proved that the concept of openness is preferred over the break line concept for visualisation. Regarding the extraction the software plug in Feature Analyst showed the best results. Openness and Feature Analyst stand also out when costs and processing time were considered. Therefore, we suggest the workflow which combines openness, for visualisation, and Feature Analyst for extraction. The results of this study contribute to the development of automatic extraction techniques in general. In this regard software packages like eCognition look promising to improve extraction methods.

Secondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the “volumetric scattering” (Pv) and “anisotropy” (A) attributes were important to explain the biomass content of the successional chronosequence (R²_adjusted = 0.67; RMSE = 32.29 Mg.ha^-1). By adding the TanDEM-derived interferometric coherence (Υi) into the regression modeling, better results were obtained (R²_adjusted = 0.75; RMSE = 28.78Mg.ha-¹). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands.

The rise in the living standards of the Greeks created, especially since 1970, along with other needs and the need for second or holiday home since 1990 after finding the first house on the outskirts of large urban centers. Trying to find land for the creation of new resorts or new type of permanent residences (maisonettes with or without garden, depending on the financial position of each) had the painful consequence of wasteful and uncontrolled use of land, without a program, without the fundamental rules of land planning and the final creation was usually unsightly buildings. The costs were to pay as usually the forest rural lands. The national spatial planning of land use requires that we know the existing land uses in this country, and based on that we can design and decide their land uses on the future in a rational way. On final practical level, this planning leads to mark the boundaries of specific areas of land that are permitted and may change uses. For this reason, one of the most valuable “tools” of that final marking the boundaries is also the forest maps. The paper aims the investigation to determine the modern views on the issues of Cadastre and Land Management with an ulterior view to placing the bases for creating a building plan of an immediate completion of forest maps. Sustainable development as a term denoting a policy of continued economic and social development that does not involve the destruction of the environment and natural resources, but rather guarantees their rational viability.

Forest fires are an ancient phenomenon. Appear, however, with devastating frequency and intensity over the last 30 years. In our country, the climatic conditions in combination with the intense relief, favor their rapid spread. Considering the fact that environmental conditions provided for decades even worse (increased temperature, drought and vegetation), then the problem of forest fires in our country, is expected to become more intense. The work focuses on the optimization model of the opening up of the forest mountain areas taking into account the prevention and suppression of forest fires. Research area is the mountain forest complex of W. Nestos of Drama Prefecture. The percentage of forest protection area is examined under the light whether the total hose length corresponds to the actual operational capacity to reach a fire source. For this reason are decided to present a three case study concerning area of the forest being protected by fire extinguishing vehicles. The first one corresponds to a fire suppression bandwidth (buffer zone) with a capacity radius of 150m uphill and 250m downhill from the origin point where the fire extinguishing vehicle stands. The second one corresponds to a fire suppression capacity of 200m uphill and 400m downhill and the third one corresponds to a fire suppression capacity of 300m uphill and 500m downhill. The most important forest technical infrastructures to prevent fire are roads network (opening up) for fire protection and buffer zones. Patrols of small and agile 4 × 4 appropriately equipped (pipe length of 500 meters and putting pressure on uphill to 300 meters) for the first attack of the fire in the summer months coupled with early warning of fire observatories adequately cover the forest protection of W. Nestos complex. But spatial distribution needed improvements to a road density of the optimum economic Dec, both forest protection and for better management (skidding) of woody capital.

The problem of predicting the occurrence of earthquakes is threefold. On one hand it is necessary to predict the date and magnitude of an earthquake, and on the other hand the location of the epicenter. In this work after a brief review of the state of earthquake prediction research, we report on a new leading time precursor for determining time onset of earthquake occurrence. We report the linking between earthquakes of the past with those which happen in the future via Fibonacci, Dual and Lucas numbers (FDL) numbers. We demonstrate it here with two example seed earthquakes at least 100 years old. Using this leading indicator method we can predict significant earthquake events >6.5R, with good accuracy approximately +- 1 day somewhere in the world. From a single seed we produce at least 100 trials simultaneously of which 50% are correct to +- 1day. The indicator is based on Fibonacci, Dual and Lucas numbers (FDL). This result hints that the log periodic FDL numbers are at the root of the understanding of the earthquake mechanism. The theory is based on the assumption that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series. (The mechanism could well be linked to planetary orbits). When future dates are derived from clustering and convergence from previous strong earthquake dates at an FDL time distance, then we have a high probability for an earthquake to occur on that date. We set up a real time system which generates FDL time series from each previous significant earthquake (>7R) and we produce a year to year calendar of high probability earthquake dates. We have tested this over a number of years with considerable success. We have applied this technique for strong (>7R) earthquakes across the globe as well as on a restricted region such as the Greek geographic region where the magnitude is small (>4R-6.5R). In both cases the success of the method is impressive. It is our belief that supplementing this method with other precursors will enhance significantly the prediction of significant earthquakes.

The aims of the bridge management authorities are to ensure that bridges fulfil their purpose and functionality during their design life. So, it is important to identify and quantify the deterioration of the structural condition early so that a timely application of an intervention will avoid more serious problems and increased costs at a later stage. A measure to enhance the effectiveness of the existing structural evaluation by visual inspection is instrumental monitoring using sensors. The activities performed in this process belong to the field of Structural Health Monitoring (SHM). The SHM offers opportunities for continuous or periodic monitoring on bridges and technological advances allow nowadays the employment of wireless sensors networks (WSN) for this task. A SHM application using WSN was implemented on a multi-span reinforced concrete (RC) highway bridge in Limassol with the objective to study its dynamic characteristics and performance. Part of the specific bridge will be replaced and this offered a unique opportunity for measurements before and after construction so that apparent changes in the dynamic characteristics of the bridge will be identified after the repairing work. The measurements provided indications on the frequencies and mode shapes of the bridge and the response amplitude during the passing of traffic. The latter enabled the investigation of the dependency of the bridge’s structural damping to the amplitude of vibration induced by the passing of traffic. The results showed that as the excitation increases the magnitude of modal damping increases as well.

Natural hazards, such as earthquakes, can have a large destructive effect on cultural heritage sites conservation. This study aims to assess from a geospatial perspective the risk from natural hazards for the archaeological sites and monuments and evaluate the potential tectonic activity impact on the cultural and historic heritage. Geomorphometric data derivatives that can be extracted from Digital Elevation Models (DEMs) provide information relevant with active tectonics. The specific extracted tectonic information when being used on the basis of analytical hierarchy process and weighted linear combination approach can offer an important robust approach. The ranking of the derived information relatively to specific criteria of weights can enhance the interrelationships and assemblages over neotectonics aspects. The outcomes of that methodological framework can propose an assessment approach for the spatial distribution of neotectonic activity and can become a useful tool to assessing seismic hazard for disaster risk reduction. The risk assessment aspects of such a hazard are being interlinked with the archaeological sites in order to highlight and examine those that are exposed on ongoing tectonic activity and seismic hazard. Paphos area in Cyprus has been used as the test bed for the particular analysis. The results show an important number of archaeological sites being located within zones of high degree of neotectonic activity.

The phenological characteristics of the vegetation are key elements for understanding vegetation responses in different climate change scenarios, as well as indicators of ongoing processes of increasing aridity. Determination of phenological parameters for different types of vegetation in large areas help evaluate current and future impacts of climate change in ecosystems, specially in those more vulnerable. Moderate resolution remote sensing data, as provided by MODIS, has already been used to extract phenological characteristics from time series data of vegetation indices, most usually by data smoothing and fitting of polynomial models. In this work, we use hidden Markov models (HMMs) to define phenological parameters from MODIS derived NDVI time series data in a semiarid Mediterranean region. Different types of HMMs are applied in selected areas with well-defined vegetation communities, and their potentials for automatic phenological analysis at large scale are discussed.

The olive-oil industry is one of the most important sectors of agricultural production in Greece, which is the third in olive-oil production country worldwide. Olive oil mill wastes (OOMW) constitute a major factor in pollution in olivegrowing regions and an important problem to be solved for the agricultural industry. The olive-oil mill wastes are normally deposited at tanks, or directly in the soil or even on adjacent torrents, rivers and lakes posing a high risk to the environmental pollution and the community health. GEODIAMETRIS project aspires to develop integrated geoinformatic methodologies for performing monitoring of land pollution from the disposal of OOMW in the island of Crete -Greece. These methodologies integrate GPS surveys, satellite remote sensing and risk assessment analysis in GIS environment, application of in situ and laboratory geophysical methodologies as well as soil and water physicochemical analysis. Concerning project’s preliminary results, all the operating OOMW areas located in Crete have been already registered through extensive GPS field campaigns. Their spatial and attribute information has been stored in an integrated GIS database and an overall OOMW spectral signature database has been constructed through the analysis of multi-temporal Landsat-8 OLI satellite images. In addition, a specific OOMW area located in Alikianos village (Chania–Crete) has been selected as one of the main case study areas. Various geophysical methodologies, such as Electrical Resistivity Tomography, Induced Polarization, multifrequency electromagnetic, Self Potential measurements and Ground Penetrating Radar have been already implemented. Soil as well as liquid samples have been collected for performing physico-chemical analysis. The preliminary results have already contributed to the gradual development of an integrated environmental monitoring tool for studying and understanding environmental degradation from the disposal of OOMW.

Early warning for rockfall incidents occurring on slopes along highways and roads is a vital safety practice for both human lives and property loss. Monitoring systems mainly rely on laser scanners, distributed sensors and precision geodetic measurements. In this study, close range terrestrial photogrammetry is evaluated towards rockfall incident detection. Photogrammetry has been extensively used for 3D mapping and reconstruction of terrain and infrastructure mainly due to its relatively low implementation cost, compared to the above mentioned approaches, especially when using non-metric digital cameras. Yet, the underlying problems in terrestrial photogrammetry include processing time, precision, night capturing limitations, and various errors, including occlusion, camera geometry, lighting, etc. In the present paper, an experimental setup along with preliminary results of the terrain photogrammetry integration into an operational slope monitoring scheme are presented. More specifically, assessment of the detection limitations are provided in order to evaluate whether photogrammetry can constitute a cost-effective alternative for rapid surface and change detection processes. In addition, since false alarm incidents cause extensive resource draining, their magnitude and occurrence are also reported.

Droughts on the island of Cyprus are more frequently occurring during the last decades. This has and will have major impacts on natural resources, particularly on semi-aquatic and aquatic ecosystems. Wetlands are very important aquatic ecosystems with many functions and values, especially in semi-arid regions. The study area is the Wetland of the Larnanca Salt Lake that belongs to the Natura 2000 Network and the Ramsar Convention. It hosts thousands of migratory birds every year. Forecasting accurately the future climatic conditions of an area can greatly enhance the ability to provide the best possible managerial practices regarding a natural resource (e.g. wetland). These climate forecasts can provide significant information on future conditions of the Wetland of Larnaca Salt Lake, particularly when forecasting when and how long the drying conditions could last. In this study, an Artificial Neural Networks (ANN) was used as a tool for short term prediction of the precipitation in the study area. The methodology used two time series (temperature and precipitation) in order to train the ANN. Temperatures were used as the input variable to the ANN while precipitation was used as the output variables. The forecast was based on data from the period between 1993 and 2013. In order to estimate the accuracy of the produced results the correlation coefficient, the Root Mean Square Error (RMSE) and the Mean Absolute Percentage Error (MAPE) was correlated. Overall, this tool can help the responsible authorities of the wetland to manage it more efficiently.

The predominant approach for conducting road condition surveys and analyses is still largely based on extensive field observations. However, visual assessment alone cannot identify the actual extent and severity of damage. New non-invasive and cost-effective non-destructive (NDT) remote sensing technologies can be used to monitor road pavements across their life cycle, including remotely sensed aerial and satellite visual and thermal image (AI) data, Unmanned Aerial Vehicles (UAVs), Spectroscopy and Ground Penetrating Radar (GRP). These non-contact techniques can be used to obtain surface and sub-surface information about damage in road pavements, including the crack depth, and in-depth structural failure. Thus, a smart and cost-effective methodology is required that integrates several of these non-destructive/ no-contact techniques for the damage assessment and monitoring at different levels. This paper presents an overview of how an integration of the above technologies can be used to conduct detailed road condition surveys. The proposed approach can also be used to predict the future needs for road maintenance; this information is proven to be valuable to a strategic decision making tools that optimizes maintenance based on resources and environmental issues.

Olive oil mills’ wastes (OOMW) are one of the byproducts of the oil production that can lead to serious environmental pollution when they are deposited in ponds dug on the ground surface. Electrical Resistivity Tomography (ERT) method can provide a valuable tool in order to monitor through time the physical flow of the wastes into the subsurface. ERT could potentially locate the electrical signature due to lower resistivity values resulting from the leakage of OOMW to the subsurface. For this purpose, two vertical boreholes were installed (12m depth, 9 m apart) in the vicinity of an existing pond which is filled with OOMW during the oil production period. The test site is situated in Saint Andreas village about 15km south of the city of Rethymno (Crete, Greece). Surface ERT measurements were collected along multiple lines in order to reconstruct the subsurface resistivity models. Data acquisition was performed with standard and optimized electrode configuration protocols. The monitoring survey includes the ERT data collection for a period of time. The study was initiated before the OOMW were deposited in the pond, so resistivity fluctuations are expected due to the flow of OOMW in the porous subsurface media through time. Preliminary results show the good correlation of the ERT images with the drilled geological formations and the identification of low resistivity subsurface zone that could be attributed to the flow of the wastes within the porous layers.

Concrete reinforced with steel rebars remains one of the most widely used construction materials. Despite its excellent mechanical performance and expected service life of at least 50 years, reinforced concrete is subjected to corrosion of the steel rebars which normally leads to concrete spalling, deterioration of the reinforced concrete’s (RC) mechanical properties and eventual reduction of the structural load capacity. In Cyprus, especially in coastal regions where almost 60% of the population resides, many structural problems have been identified in RC structures, which are mainly caused by the severe corrosion of steel rebars. Most RC buildings, located in coastal areas, show signs of corrosion within the first 15-20 years of their service life and this affects their structural integrity and reliability, especially against seismic loading. This paper presents the research undertaken as part of the STEELCOR project which aims to extensively evaluate the steel corrosion of RC buildings in coastal areas of Cyprus and conduct a risk assessment relating to steel corrosion. Non-destructive testing of corroded RC structures measurements were used to estimate the simplified index of structural damage. These indices were imported into a Geographical Information System to develop a digital structural integrity map of Cyprus which would show the areas with high risk of steel corrosion of RC buildings. In addition, archive optical remote sensing dataset was used to map the urban expansion footprint during the last 30 years in Cyprus with the aim of undertaking corrosion risk scenarios by utilizing the estimated indices.

The main advantage of using GIS is its ability to access and analyze spatially distributed data. The applications of GIS to transportation can be viewed as involving either on data retrieval; data integrator; or data analysis. The use of remote sensing can assist the retrieval of land use changes. Indeed, the integration of GIS and remote sensing will be used to fill the gap in the smart transport planning. A four step research is going to be done in order to try to integrate the usage of GIS and remote sensing to sustainable transport planning. The proposed research will be held in the city of Limassol, Cyprus. The data that are going to be used are data that are going to be collected through questionnaires, and other available data from the Cyprus Public Works Department and from the Remote Sensing Laboratory and Geo-Environment Research Lab of the Cyprus University of Technology. Overall, statistical analysis and market segmentation of data will be done, the land usage will be examined, and a scenario building on mode choice will be held. This paper presents an overview of the methodology that will be adopted.

Wetland features in seasonally semi-arid islands pose particular difficulties in identification, inventory and conservation assessment. Our survey presents an application of utilizing images of a newly launched sensor, Landsat 8, to rapidly identify inland water bodies and produce a screening-level island-wide inventory of wetlands for the first time in Cyprus. The method treats all lentic water bodies (artificial and natural) and areas holding semi-aquatic vegetation as wetland sites. The results show that 179 sites are delineated by the remote sensing application and when this is supplemented by expert-guided identification and ground surveys during favourable wet-season conditions the total number of inventoried wetland sites is 315. The number of wetland sites is surprisingly large since it does not include micro-wetlands (under 2000 m² or 0.2 ha) or widespread narrow lotic and riparian stream reaches. In Cyprus, a number of different wetland types occur and often in temporary or ephemerally flooded conditions and they are usually of very small areal extent. Many wetlands are artificial or semi-artificial water bodies, and numerous natural small wetland features are often degraded by anthropogenic changes or exist as remnant patches and are therefore heavily modified compared to their original natural state. The study proves that there is an urgent need for integrated and multidisciplinary study and monitoring of wetlands cover due to either climate change effects and/or anthropogenic interventions. Small wetlands are particularly vulnerable while many artificial wetlands are not managed for biodiversity values. The remote sensing and GIS application are efficient tools for this initial screening-level inventory. The need for baseline inventory information collection in support of wetland conservation is multi-scalar and requires an adaptive protocol to guide effective conservation planning.

This paper provides the results obtained by using satellite imagery and UAV data for managing a degraded system over Randi Forest in Cyprus. Landsat TM/ETM+ and GeoEye images have been used to retrieve several indices with the main aim to managing the overgrazed area. Aerial photographs were acquired in order to document and monitor the overgrazed areas, which also include seasonal changes in vegetation and soil. UAVs were used to create ortho-photos and DEMS. Satellite images were used to conduct NDVIs of the study area. The resulting findings provide a detailed image of the specific location of overgrazed areas. The results of the study can be used for decision makers to establish effective strategies to avoid similar scenarios of overgrazing in other parts of Cyprus.This study was funded by the FP7 programme CASCADE Project on sudden and catastrophic shifts in dryland Mediterranean ecosystems (2012-2017).

Agricultural robots can tackle harsh working conditions and hardness of work, as well as the shortage of laborers that is a bottleneck to agricultural production. Such robots exist, but they are not yet widespread. We believe that the limited usage of robotics in agriculture could be related to the fact that the mainstream direction for robotics in agriculture is full automation. The teleoperation of an agricultural robotic system can enable improved performance overcoming the complexity that current autonomous robots face due to the dynamic and unstructured agricultural environment. A field study was conducted to evaluate eight different user interfaces aiming to determine the factors that should be taken into consideration by designers while developing user interfaces for robot teleoperation in agriculture. Thirty participants, including farmers and agricultural engineers, were asked to use different teleoperation interaction modes in order to navigate the robot along vineyard rows and spray grape clusters. Based on our findings, additional views for target identification and peripheral vision improved both robot navigation (fewer collisions) and target identification (sprayed grape clusters). In this paper, we discuss aspects of user interface design related to remote operation of an agricultural robot.

The Project focuses on the resolution of decreased water supply as a result of continued water shortage. The water loss is the result of several causes, notably water losses in the water supply network pipes, the ineffective operation of pumping stations and design of the networks are some of the most important problems which need to be addressed to optimize the performance of the water networks and save both water and the energy consumed. The Project is innovative as it is the first time that several, state-of-the-art technologies, including Global Positioning System (GPS), Radar Scanners and Satellite Remote Sensing (SRS) will be combined to map the water networks. The data produced will be entered into a Geographic Information System (GIS), with the objective of developing a digital imprint and mapping of the network. Following, a representative section of the network will be selected and modeled in the new upgraded laboratory in order to conduct detailed experimental studies, which will be correlated with computational/mathematical studies. The main scientific challenge of the Project, which also characterizes its broader innovative aspect, lies in the possibility to optimize the design and also the operation of all the components of the network, through the combined use of hydraulic simulation models and multi-criteria evolution algorithms.

We present a methodology for ship extraction and categorization from relatively low resolution multispectral ASTER imagery, corresponding to the sea region south east of Athens in Greece. At a first level, in the radiometrically corrected image, quad tree decomposition and bounding rectangular extraction automatically outline location of objects - possible ships, by statistically evaluating spectral responses throughout the segmented image. Subsequently, the object borders within the rectangular regions are extracted, while connected component labelling combined by size and shape filtering allows ship characterization. The ships’ spectral signature is determined in green, red and infrared bands while cluster analysis allows the identification of ship categories on the basis of their size and reflectance. Additional pixel- based measures reveal estimated ship orientation, direction, movement, stability and turning. The results are complemented with additional geographic information and inference tools are formed towards the determination of probable ship type and its destination.