This PDF file contains the front matter associated with SPIE Proceedings Volume 9535, including the Title Page, Copyright information, Table of Contents, Introduction, Authors, and Conference Committee listing.

This paper presents a new method for automatically determining the optimum regression model, which enable the estimation of a parameter. The concept lies on the combination of k spectral pre-processing algorithms (SPPAs) that enhance spectral features correlated to the desired parameter. Initially a pre-processing algorithm uses as input a single spectral signature and transforms it according to the SPPA function. A k-step combination of SPPAs uses k preprocessing algorithms serially. The result of each SPPA is used as input to the next SPPA, and so on until the k desired pre-processed signatures are reached. These signatures are then used as input to three different regression methods: the Normalized band Difference Regression (NDR), the Multiple Linear Regression (MLR) and the Partial Least Squares Regression (PLSR). Three Simple Genetic Algorithms (SGAs) are used, one for each regression method, for the selection of the optimum combination of k SPPAs. The performance of the SGAs is evaluated based on the RMS error of the regression models. The evaluation not only indicates the selection of the optimum SPPA combination but also the regression method that produces the optimum prediction model. The proposed method was applied on soil spectral measurements in order to predict Soil Organic Matter (SOM). In this study, the maximum value assigned to k was 3. PLSR yielded the highest accuracy while NDR’s accuracy was satisfactory compared to its complexity. MLR method showed severe drawbacks due to the presence of noise in terms of collinearity at the spectral bands. Most of the regression methods required a 3-step combination of SPPAs for achieving the highest performance. The selected preprocessing algorithms were different for each regression method since each regression method handles with a different way the explanatory variables.

Land surface temperature (LST) is a key parameter in the physics of the earth surface through the process of energy and water exchange with the atmosphere, which plays an important role in a wide variety of scientific studies, such as ecology, hydrology, and global change studies. Thermal infrared (TIR) remote sensing provides a unique method for obtaining LST information at the regional and global scales since most of the energy detected by the sensor in this spectral region is directly emitted by the land surface. Landsat 8 Thermal Infrared Sensor (TIRS), because of two adjacent thermal bands, band 10 between 10.30-11.30 μm and band 11 between 11.30-12.30 μm, and availability of its images is a good source for retrieving LST. In this study, we compared two different methods for LST inversions from TIRS including the Split Window method and the SEBAL method for Tehran , Iran.. Results show that the LST inverted from the Split Window method has the accuracy with RMSE lower than 1.17 ˚ C, while the SEBAL method has the accuracy with 3.27 ˚ C, so the Split Window algorithm is appropriate method for this study area.

Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L’Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

Following its application in Northern Europe, Landscape Character Assessment has also been implemented in Euro-Mediterranean countries as a tool for classifying, describing and assessing landscapes. Many landscape classifications employed in the Euro-Mediterranean area are similar in philosophy and application to the ones developed in Northern Europe. However, many aspects of landform, climate, land-use and ecology, as well as socio-economic context are distinctive of Mediterranean landscapes. The paper discusses the conceptual and methodological issues faced during landscape mapping and characterisation in four East-Mediterranean countries (within the MEDSCAPES project): Cyprus, Greece, Jordan and Lebanon. The major hurdles to overcome during the first phase of methodology development include variation in availability, quality, scale and coverage of spatial datasets between countries and also terminology semantics around landscapes. For example, the concept of landscape - a well-defined term in Greek and English - did not exist in Arabic. Another issue is the use of relative terms like 'high mountains,' ‘uplands’ ‘lowlands’ or ' hills'. Such terms, which are regularly used in landscape description, were perceived slightly differently in the four participating countries. In addition differences exist in nomenclature and classification systems used by each country for the dominant landscape-forming factors i.e. geology, soils and land use- but also in the cultural processes shaping the landscapes - compared both to each other and to the Northern-European norms. This paper argues for the development of consistent, regionally adapted, relevant and standardised methodologies if the results and application of LCA in the eastern Mediterranean region are to be transferable and comparable between countries.

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

Land cover dynamics information plays an important role in environmental research and related studies. We use the 500m NASA MODIS land cover dataset for the European Union (EU28) to calculate (a) land cover share trends on an annual temporal increment from 2001 to 2011 and (b) land cover accounts from 2001 to 2011. Raster products are firstly mosaicked to produce a single image per year, covering the study area. Reclassification for each final annual product follows to convert the original 17 IGBP MODIS classes into 7 simpler classes of broader interest. Zonal statistics are used to calculate the number of land cover pixels per class, per country, per year. Further calculations create land account tables revealing land cover trends during 2001 through 2011. Results show that for the 2001 through 2011 period forests and cropland dominated EU28, covering almost 70% of the total area. Forest has an increasing trend, with an annual change rate of 0,60%, while cropland has a negative rate of annual change (-0, 46%). On average, grassland covers approximately 21% of EU28. A closer look reveals that despite the relatively stable overall counts, grassland has experienced high turnover. Almost half (40%) of grassland original stock changed to other land cover classes during 2001 through 2011. At the same time, there was a large conversion to grassland from other land cover classes thus keeping a balance in the overall share. Our analysis provides useful information for environmental assessments in order to better frame policies for a sustainable future.

Charles Tiebout (1956), in his work “A Pure Theory of Local Expenditures”, provides a vision of the workings of the local public sector, acknowledging many similarities to the features of a competitive market, however omitting any references to local taxation. Contrary to other researchers’ claim that the Tiebout model and the theory of fiscal decentralization are by no means synonymous, this paper aims to expand Tiebout’s theory, by adding the local property tax in the context, introducing a fair, ad valorem property taxation system based on the automated assessment of the value of real estate properties within the boundaries of local authorities. Computer Assisted Mass Appraisal methodology integrated with Remote Sensing technology and GIS analysis is applied to local authorities’ property registries and cadastral data, building a spatial relational database and providing data to be statistically processed through Multiple Regression Analysis modeling. The proposed scheme accomplishes economy of scale using CAMA procedures on one hand, but also succeeds in making local authorities self-sufficient through a decentralized, fair, locally calibrated property taxation model, providing rational income administration.

Contemporary urban environment is characterized by complexity and mixed use of space, in which overlapping land parcels and different RRRs (Rights, Restrictions and Responsibilities) are frequent phenomena. Internationally, real property legislation either focuses on surface property or has introduced individual 3D real property units. The former approach merely accommodates issues related to subdivision, expropriation and transactions on part of the real property above or below surface, while the latter provides for defining and registering 3D real property units. National laws require two-dimensional real property descriptions and only a limited number of jurisdictions provide for threedimensional data presentation and recording. International awareness on 3D Cadastre may be apparent through the proposals for transition of existing cadastral systems to 3D along with legal amendments improving national 3D Cadastre legislation. Concurrently the use of appropriate data sources and the correct depiction of 3D property units’ boundaries and spatial relationships need to be addressed. Spatial relations and constraints amongst real world objects could be modeled geometrically and topologically utilizing numerous modeling tools, e.g. CityGML, BIM and further sophisticated 3D software or by adapting international standards, e.g. LADM. A direct correlation between legal and physical property should be based on consistent geometry between physical and legal space, improving the accuracy that legal spaces’ volumes or locations are defined. To address these issues, this paper investigates correlation possibilities and constraints between legal and physical space of typical 3D property cases. These cases comprise buildings or their interior spaces with mixed use, as well as complex structures described by explicit facade patterns, generated by procedural or by BIM ready 3D models. The 3D models presented are evaluated, regarding compliancy to physical or legal reality.

Land consolidation is a very effective land management planning approach that aims towards rural/agricultural sustainable development. Land reallocation which involves land tenure restructuring is the most important, complex and time consuming component of land consolidation. Land reallocation relies on land valuation since its fundamental principle provides that after consolidation, each landowner shall be granted a property of an aggregate value that is approximately the same as the value of the property owned prior to consolidation. Therefore, land value is the crucial factor for the land reallocation process and hence for the success and acceptance of the final land consolidation plan. Land valuation is a process of assigning values to all parcels (and its contents) and it is usually carried out by an ad-hoc committee. However, the process faces some problems such as it is time consuming hence costly, outcomes may present inconsistency since it is carried out manually and empirically without employing systematic analytical tools and in particular spatial analysis tools and techniques such as statistical/mathematical. A solution to these problems can be the employment of mass appraisal land valuation methods using automated valuation models (AVM) based on international standards. In this context, this paper presents a spatial based linear hedonic price model which has been developed and tested in a case study land consolidation area in Cyprus. Results showed that the AVM is capable to produce acceptable in terms of accuracy and reliability land values and to reduce time hence cost required by around 80%.

Time in infrastructure construction projects has always been a fundamental issue as early as from the inception of a project, during the construction process and often after the completion and delivery. In a typical construction contract time related matters such as the completion date and possible delays are among the most important issues that are dealt with by the contract provisions. In the event of delay there are usually provisions for extension of time award to the contractor with possible reimbursement for the extra cost and expenses caused by this extension of time to the contract duration. In the case the contractor is not entitled to extension of time, the owner will be possibly entitled to amounts as compensation for the time prohibited from using his development. Even in the event of completion within the time agreed, under certain circumstances a contractor may have claims for reimbursement for extra costs incurred due to induced acceleration measures he had to take in order to mitigate disruption effects caused to the progress of the works by the owner or his representatives. Depending on the size of the project and the agreement amount, these reimbursement sums may be extremely high. Therefore innovative methods with the exploitation of new technologies for effective project management for the avoidance of delays, delay analysis and mitigation measures are essential; moreover, methods for collecting efficiently information during the construction process so that disputes regarding time are avoided or resolved in a quick and fair manner are required. This paper explores the state of art for existing use of Building Information Modelling (BIM) and Unmanned Aerial Vehicles (UAV) technologies in the construction industry in general. Moreover the paper considers the prospect of using BIM technology in conjunction with the use of UAV technology for efficient and accurate as-built data collection and illustration of the works progress during an infrastructure construction project in order to achieve more effective project management, record keeping and delay analysis.

The Iran plateau is located on the earth dust belt. It always has been subject to different dust activities and dust storms that mostly had been originated from dust sources which are located outside of the plateau. Recently we reported that the Mesopotamian region is responsible for more than 80 percent of observed dust events in Northwest Iran. In this work we have used the available aerosol optical dept (AOD) on the MODIS deep blue and the surface soil moisture data (SM) extracted from GLDAS version-1 data set, to look over the evolutions of dust activities and variations of soil moisture in the Mesopotamian region during 2001 to 2012. Recorded monthly values of AOD indicate that most of the annual dust activities had been occurred during April to July but the soil moisture had had its maximum values during December to March. During the considered period of time in this study, dust activities in Northern Mesopotamian area (centered about 35 E, 42 N) have been strengthened considerably and the center of dust activities has been moved about 0.5 degrees to North and the same amount to East. Looking to the annual trend of the AOD (SM) averaged over the months April, May, Jun and July (December, January, February and March), a trend of ~0.030 ± 0.004 (~0.033 ± 0.002 kg/m²) per year has been observed for the mentioned time span. Also temporal correlation between annual values of obtained AOD and SM has been investigated in this work. It is found that a strong negative correlation exist between these two parameters and its minimum value (-0.7) occurs when both AOD and soil moisture have been measured in the same year.

A number of methods have been proposed for the atmospheric correction of the multispectral satellite images, based on either atmosphere modelling or images themselves. Full radiative transfer models require a lot of ancillary information about the atmospheric conditions at the acquisition time. Whereas, image based methods cannot account for all the involved phenomena. Therefore, the aim of this paper is the comparison of different atmospheric correction methods for multispectral satellite images. The experimentation was carried out on a study area located in the catchment area of Yialias river, 20 km South of Nicosia, the Cyprus capital. The following models were tested, both empirical and physically based: Dark object subtraction, QUAC, Empirical line, 6SV, and FLAASH. They were applied on a Landsat 8 multispectral image. The spectral signatures of ten different land cover types were measured during a field campaign in 2013 and 15 samples were collected for laboratory measurements in a second campaign in 2014. GER 1500 spectroradiometer was used; this instrument can record electromagnetic radiation from 350 up to 1050 nm, includes 512 different channels and each channel covers about 1.5 nm. The spectral signatures measured were used to simulate the reflectance values for the multispectral sensor bands by applying relative spectral response filters. These data were considered as ground truth to assess the accuracy of the different image correction models. Results do not allow to establish which method is the most accurate. The physics-based methods describe better the shape of the signatures, whereas the image-based models perform better regarding the overall albedo.

The number of rainy days per year in calculated to follow a negative trend in Nicosia and for that an analysis of drought using the Standardized Precipitation Index SPI-n and the BMDI drought index has been made. The calculations have been made using daily rainfall total amounts for the station of Nicosia for a long enough period in order to extract save conclusions about the drought trend. BMDI index has been specifically calculated for the case of Cyprus. The results show that throughout the years, Nicosia has experienced the results of drought, with extremely low precipitation amounts for some years and thus severe drought events.

In recent years, many efforts have been made in order to assess forest stand parameters from remote sensing data, as a mean to estimate the above-ground carbon stock of forests in the context of the Kyoto protocol. Synthetic aperture radar interferometry (InSAR) techniques have gained traction in last decade as a viable technology for vegetation parameter estimation. Many works have shown that forest canopy height, which is a critical parameter for quantifying the terrestrial carbon cycle, can be estimated with InSAR. However, research is still needed to understand further the interaction of SAR signals with forest canopy and to develop an operational method for forestry applications. This work discusses the use of repeat pass interferometry with ALOS PALSAR (L band) HH polarized and COSMO Skymed (X band) HH polarized acquisitions over the Taxiarchis forest (Chalkidiki, Greece), in order to produce accurate digital elevation models (DEMs) and estimate canopy height with interferometric processing. The effect of wavelength-dependent penetration depth into the canopy is known to be strong, and could potentially lead to forest canopy height mapping using dual-wavelength SAR interferometry at X- and L-band. The method is based on scattering phase center separation at different wavelengths. It involves the generation of a terrain elevation model underneath the forest canopy from repeat-pass L-band InSAR data as well as the generation of a canopy surface elevation model from repeat pass X-band InSAR data. The terrain model is then used to remove the terrain component from the repeat pass interferometric X-band elevation model, so as to enable the forest canopy height estimation. The canopy height results were compared to a field survey with 6.9 m root mean square error (RMSE). The effects of vegetation characteristics, SAR incidence angle and view geometry, and terrain slope on the accuracy of the results have also been studied in this work.

Space-borne SAR sensors are capable to measure ground elevation using interferometric (InSAR) or radargrammetric techniques. In the first case, the phase content is used while in the second case the amplitude values of SAR image are exploited. This work is focused on the analysis of potentialities of the Interferometric and radargrammetric DSMs generation using high resolution SAR imagery acquired by two of the newer satellite platforms (Sentinel -1 and COSMO-SkyMed). Eleven Sentinel-1 and two COSMO-SkyMed scenes have been processed. A full comparison and analysis has been carried for Myconos Island where a high accuracy DSM from the Greek cadastral and other DEM from digitized contours from the 1/50.000 topographic maps are available. After a first control for random or systematic errors a statistical analysis was done. Points of known elevation have been used to estimate the accuracy of the DSMs. 2D RMSE, correlation and the percentile value were computed and the results are presented.

This paper studies the use of high resolution satellite optical and SAR images for 1:5,000 mapping production, which is essential for public work and environmental impact assessment studies. The images were used for the extraction of DEMs and their “fit for purpose” use was investigated, through the examination of parameters like accuracy, reliability and performance of morphological features. Orthoimages from satellite optical images using the produced DEMs with or without breaklines were produced. An application was developed on Antiparos island, a Greek island with irregular terrain. The data includes: (a) a triplet of Pleiades (1A, tri-stereo) satellite images, with a resolution of 0.5m, (b) a TanDEM-X Intermediate DEM, a preliminary version of the forthcoming TanDEM-X global DEM, and (c) an accurate DEM produced from the Greek National Cadastre & Mapping Agency S.A. was used as the reference DEM. The georeferencing of the optical images was computed using GCPs which were measured with GNSS. DEMs were extracted using all the possible combinations of the images triplet using automated image matching without any filtering or editing and were evaluated using the reference DEM. The combination of images which yielded the best DEM was then used to manually editing 3D points and collecting breaklines in order to produce a better DEM, which was also evaluated using various statistical measures and geo-morphological features. Orthoimages were created and evaluated using DEMs from optical and SAR data. A discussion about the use of the computed mapping products for the various stages of the public work studies is included.

The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) carried by the Advanced Land-Observing Satellite (ALOS) was designed to generate worldwide topographic data with its high-resolution and stereoscopic observation. PRISM performs along-track (AT) triplet stereo observations using independent forward (FWD), nadir (NDR), and backward (BWD) panchromatic optical line sensors of 2.5m ground resolution in swaths 35 km wide. The FWD and BWD sensors are arranged at an inclination of ±23.8° from NDR. In this paper, PRISM images are used under a new perspective, in security domain for sea surveillance, based on the sequence of the triplet which is acquired in a time interval of 90 sec (45 sec between images). An automated motion detection algorithm is developed allowing the combination of encompassed information at each instant and therefore the identification of patterns and trajectories of moving objects on sea; including the extraction of geometric characteristics along with the speed of movement and direction. The developed methodology combines well established image segmentation and morphological operation techniques for the detection of objects. Each object in the scene is represented by dimensionless measure properties and maintained in a database to allow the generation of trajectories as these arise over time, while the location of moving objects is updated based on the result of neighbourhood calculations. Most importantly, the developed methodology can be deployed in any air borne (optionally piloted) sensor system with along the track stereo capability enabling the provision of near real time automatic detection of targets; a task that cannot be achieved with satellite imagery due to the very intermittent coverage.

In the framework of ERMES project (FP7 66983), an algorithm for mapping rice cultivation extents using mediumhigh resolution satellite data was developed. ERMES (An Earth obseRvation Model based RicE information Service) aims to develop a prototype of downstream service for rice yield modelling based on a combination of Earth Observation and in situ data. The algorithm was designed as a set of rules applied on a time series of Landsat 8 images, acquired throughout the rice cultivation season of 2014 from the plain of Thessaloniki, Greece. The rules rely on the use of spectral indices, such as the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), and the Normalized Seasonal Wetness Index (NSWI), extracted from the Landsat 8 dataset. The algorithm is subdivided into two phases: a) a hard classification phase, resulting in a binary map (rice/no-rice), where pixels are judged according to their performance in all the images of the time series, while index thresholds were defined after a trial and error approach; b) a soft classification phase, resulting in a fuzzy map, by assigning scores to the pixels which passed (as ‘rice’) the first phase. Finally, a user-defined threshold of the fuzzy score will discriminate rice from no-rice pixels in the output map. The algorithm was tested in a subset of Thessaloniki plain against a set of selected field data. The results indicated an overall accuracy of the algorithm higher than 97%. The algorithm was also applied in a study are in Spain (Valencia) and a preliminary test indicated a similar performance, i.e. about 98%. Currently, the algorithm is being modified, so as to map rice extents early in the cultivation season (by the end of June), with a view to contribute more substantially to the rice yield prediction service of ERMES. Both algorithm modes (late and early) are planned to be tested in extra Mediterranean study areas, in Greece, Italy, and Spain.

In the last decade, reducing urban pollution and improving quality of public spaces became a more and more important issue for public administration authorities in Romania. The paper describes the development of a web-GIS solution dedicated to monitoring of the green infrastructure in Bucharest, Romania. Thus, the system allows the urban residents (citizens) to collect themselves and directly report relevant information regarding the current status of the green infrastructure of the city. Consequently, the citizens become an active component of the decision-support process within the public administration. Besides the usual technical characteristics of such geo-information processing systems, due to the complex legal and organizational problems that arise in collecting information directly from the citizens, additional analysis was required concerning, for example, local government involvement, environmental protection agencies regulations or public entities requirements. Designing and implementing the whole information exchange process, based on the active interaction between the citizens and public administration bodies, required the use of the “citizen-sensor” concept deployed with GIS tools. The information collected and reported from the field is related to a lot of factors, which are not always limited to the city level, providing the possibility to consider the green infrastructure as a whole. The “citizen-request” web-GIS for green infrastructure monitoring solution is characterized by a very diverse urban information, due to the fact that the green infrastructure itself is conditioned by a lot of urban elements, such as urban infrastructures, urban infrastructure works and construction density.

It is common sense that the possibility of a rockfall increases after an intense rainfall and it is well documented that rainfalls accelerate earth surface displacements such as landslides and rockfalls. This qualitative correlation is highly affected by the geology and climate condition of the area under consideration. The research project entitled "Development of an integrated system for rockfall identification in highways", funded by the Operational Program Competitiveness and Entrepreneurship (co-funded by the European Regional Development Fund (ERDF)) aims to develop an operational system for early warning of rockfalls that occur along transportation corridors. To accomplish this goal the influence and the time gap between triggering mechanisms and rockfall incidents is investigated. In this work, previous studies towards quantitative correlation of rainfall magnitude and earth surface displacements are briefly presented. Based on these works, and taking into account that rockfall incidents, in the majority of Mediterranean countries, are not well-documented, data obtained by a slope stability monitoring network are used to quantitatively determine the magnitude of the rainfall that caused the slope's movement.

Volcanic gases give information on magmatic processes. In particular, anomalous releases of carbon dioxide precede volcanic eruptions. Up to now, this gas has been measured in volcanic plumes with conventional measurements that imply the severe risks of local sampling and can last many hours. For these reasons and for the great advantages of laser sensing, the thorough development of volcanic lidar has been undertaken at the Diagnostics and Metrology Laboratory (UTAPRAD-DIM) of the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA). In fact, lidar profiling allows one to scan remotely volcanic plumes in a fast and continuous way, and with high spatial and temporal resolution. Two differential absorption lidar instruments will be presented in this paper: BILLI (BrIdge voLcanic LIdar), based on injection seeded Nd:YAG laser, double grating dye laser, difference frequency mixing (DFM) and optical parametric amplifier (OPA), and VULLI (VULcamed Lidar), based on injection seeded Nd:YAG laser and optical parametric oscillator (OPO). The first one is funded by the ERC (European Research Council) project BRIDGE and the second one by the ERDF (European Regional Development Fund) project VULCAMED. While VULLI has not yet been tested in a volcanic site, BILLI scanned the gas emitted by Pozzuoli Solfatara (Campi Flegrei volcanic area, Naples, Italy) during a field campaign carried out from 13 to 17 October 2014. Carbon dioxide concentration maps were retrieved remotely in few minutes in the crater area. Lidar measurements were in good agreement with well-established techniques, based on different operating principles. To our knowledge, it is the first time that carbon dioxide in a volcanic plume is retrieved by lidar, representing the first direct measurement of this kind ever performed on an active volcano and showing the high potential of laser remote sensing in geophysical research.

In this work we study the effect of solar flares on the ionosphere over Cyprus. Solar flares are impulsive solar activity events usually coupled with Coronal Mass Ejection (CME). The arrival and the subsequent impact of solar flares on geospace, following an eruption on the Sun’s surface is almost immediate (around 9 min) whereas the impact of CMEs is rather delayed (2-3 days) as the former is based on X-ray radiation whereas the latter phenomenon is related with particles and magnetic fields travelling at lower speeds via the Solar Wind. The penetration of X-rays down to the Dregion following such an event enhances the electron density. This increase can be monitored by ionosondes, which measure the electron density up to the maximum electron density N_mF2. The significance of this increase lies on the increase of signal absorption causing limited window of operating frequencies for HF communications. In this study the effect of enhanced X-ray flux on the ionosphere over Cyprus during solar flares has been investigated. To establish the correlation and extent of impact on different layers, data of X-ray intensity from Geostationary Operational Environmental Satellite (GOES) and ionospheric characteristics (D & F layer) over Nicosia station (35° N, 33° E) were examined for all solar flares during the period 2011-2014. The analysis revealed a positive and good correlation between frequency of minimum reflection, f_min and X-ray intensity for D layer demonstrating that X-rays play a dominant role in the ionization of lower ionosphere. Hence, X-ray flux can be used as a good proxy for studying the solar flare effects on lower ionosphere. The correlation coefficient between maximum electron density of F layer, N_mF2 and X-ray intensity was found to be poor.

Digital Elevation Models (DEMs) are developing and evolving at a fast pace, given the progress of computer science and technology. This development though, is not accompanied by an advancement of knowledge on the quality of the models and their indigenous inaccuracy. The user on most occasions is not aware of this quality thus in not aware of the correlating product uncertainty. Extensive research has been conducted – and still is – towards this direction. In the research presented in this paper there is an analysis of elevation errors behavior which are recorded in a DEM. The behavior of these elevation errors, is caused by altering the DEM resolution upon the application of the algorithm interpolation. Contour lines are used as entry data from a topographical map. Elevation errors are calculated in the positions of the initial entry data and wherever the elevation is known. The elevation errors that are recorded, are analyzed, in order to reach conclusions about their distribution and the way in which they occur.

The commercial market offers several software packages for the registration of remotely sensed data through standard one-to-one image matching. Although very rapid and simple, this strategy does not take into consideration all the interconnections among the images of a multi-temporal data set. This paper presents a new scientific software, called Satellite Automatic Multi-Image Registration (SAMIR), able to extend the traditional registration approach towards multi-image global processing. Tests carried out with high-resolution optical (IKONOS) and high-resolution radar (COSMO-SkyMed) data showed that SAMIR can improve the registration phase with a more rigorous and robust workflow without initial approximations, user’s interaction or limitation in spatial/spectral data size. The validation highlighted a sub-pixel accuracy in image co-registration for the considered imaging technologies, including optical and radar imagery.

Mobile device use has vastly increased in the last few years. Many people use many mobile devices in their daily lives. Context-aware computing is the main feature of pervasive and ubiquitous computing. Context awareness is also an important topic that becomes more available with ubiquitous computing. As the sensors increase, the data collected via mobile device sensors and sensor networks do not have much value because of the difficulty in analysis and understanding the data. Context-aware computing helps us store contextual information and use or search it by mobile devices when we want to see or analyze it. Contextual data can be made more meaningful by context-aware processing. There are different types of data and context information that must be considered. By combining spatial and contextual data, we obtain more meaningful data based on the entities. Contextual data is any information that can be used to characterize the situation of the entity. The entity is a person, place, or object considered relevant to the interaction between the user and an application, including the users and the applications. Using contextual data and good integration to mobile devices adds great value to this data, and combining these with our other data sets will allow us to obtain more useful information and analysis.

One of the main issues in the maintenance plans of road agencies or governmental organizations is the early detection of damaged asphalt pavements. The development of a smart and non-destructive systematic technique for monitoring damaged asphalt pavements is considered a main priority to fill this gap. During the 1970’s, remote sensing was used to map road surface distress, while during the last decade, remote sensing became more advanced, thereby assisting in the evolution of the identification and mapping of roads. Various techniques were used in order to explore condition, age, weaknesses and imperfections of asphalted pavements. These methods were fairly successful in the classification of asphalted surfaces and in the detection of some of their characteristics. This paper explores the state of the art of using remote sensing techniques for monitoring damaged pavements and some typical spectral profiles of various asphalt pavements in Cyprus area acquired using the SVC1024 field spectroradiometer.

The PoPaTERVA project is developing applied research regarding the comprehension of the multi-layered cultural background of the Terva Valley Archaeological Park, in Boticas, Portugal. One of the main aspects focused on the project is the appliance of remote sensing techniques to enhance non visible archaeological features. An earth resistance tomography (ERT) survey was carried out at the Sapelos hillfort, by the specialized SINERGEO geophysicist’s team, using a Wenner-Schlumberger array. The resulting data was analyzed by the authors in order to extract and verify valid archaeological features regarding the settlement’s structures. There are several adequate systems that can be used to visualize the surveyed data (x, y, z, Ω). However, the authors preferred the open source Visualization Toolkit (VTK) from Kitware Inc., since it supports several visualization and modelling techniques that are useful for interpretation purposes in archaeological contexts: for instance, it is possible to represent the archaeological site as a virtual scale model, which can be freely manipulated. For the Sapelos hillfort, two distinct visualizations were developed to represent the acquired electrical resistivity data. The first one is used to create a comprehensive volume from the surveyed data, which is imported as structured 3D points and mapped into a 3D volume. However, this representation does not provide the necessary insight for analysis purposes, so a second visualization is needed to cluster the relevant data for archaeological research. This visualization is based on contouring algorithms that generate isosurfaces from scalar resistivity values (Ω), therefore enhancing the features with potential archaeological interest.

The presented overview is a result of the first phase of ESA-funded ArchEO (Archaeological application of Earth Observation techniques) project which aims to identify conditions favourable for analysis of archaeological sites and landscapes with use of satellite-based techniques. The project focuses on the region of Central Europe that has highly anthropogenically transformed landscapes with a large percentage of agricultural lands, what under certain ground conditions (favourable crop type, moisture, soil depth, bedrock, agricultural treatments, local biological processes etc.) foster the development of marks allowing identification of archaeological remains. The most important factor determining the choice of satellite data sources and techniques of processing is the characteristics of archaeological sites typical for the analysed region. Relatively small size of archaeological features and significant dispersion of past human activity residues require the use on satellite data on the highest possible spatial resolution. Often the resolution of multispectral bands needs to be increased with pansharpening techniques to provide valuable information - it determines the choice of further processing techniques. Nevertheless, the ability for acquisition of data in NIR spectral range is still the most important added value offered by optical satellite remote sensing, it enables to analyse vegetation characteristics and thus to better identify cropmarks. The archival data from various satellite sensors, obtained under different vegetative, soil, seasonal and anthropogenic conditions enable comparative studies on conditions for distinguishing marks appearance. The conducted analysis of archaeological community requirements clearly indicates that their needs go further than archaeological features detection – delineation of an archaeological site protective border and threats monitoring is equally important.

Archaeologists have been applying remote sensing methods for over hundred years. New technological opportunities still appear and they may offer new data on remains from the Past. Effectiveness of remote sensing methods differs at scales. Aerial photographs play very important role at the regional scale of prospection. The question appears on usefulness of optical satellite imagery in the field dominated by aerial photography until now. Survey based on aerial recording of early farming settlements in Central Europe proofs the value and effectiveness of the method in this field. On the other hand whilst analyzing aerial photographs one might doubt about a spatial structure of the settlement, whether the whole space of the settlement has been recorded or not. Most of traces of houses can be recognized as cropmarks, however it applies only to specific geomorphological structures. It raises the question: did people in the past select those specific geomorphological structures for settling or whether existing soil and geomorphological conditions mask archaeological traces? An attempt to recognize the impact of local soils and geomorphological conditions on a possibility of identification of archaeological features is one of the tasks in the project ArchEO – archaeological applications of Earth Observation techniques. In the vicinity of Kaczkowo village in Kujawy Region (Poland) a cluster of traces of the early Neolithic farmers is located. This area has been a subject of aerial survey for several years. Yet the question on a completeness of recognition of the settlement pattern is still open. In the project we attempt to assess to what extent optical satellite imagery and a wide range of processing techniques (vegetation indices, color composites, spectral transformations, edge detection etc.) might allow an identification of the remains of settlements, especially in the neighborhood of already known clusters of Neolithic houses. It might help in defining the range of the whole settlement. On the other hand an analysis of the relations between specific characteristics of soils and geomorphologic structures and the presence of remains of settlement might be necessary.

Although ruins of palace in Radlin, localized in Wielkopolska Region (Poland), could have been a great inspiration for romantic landscape painters, they were hardly considered as the subject of artistic interest. Nevertheless they stand as a marker in a landscape as a romantic background for the village on one hand and a memento for the neighbouring graveyard on another. Small scale excavations carried out in late 1950s with historical maps and analysis of still standing remains gave a general idea about wings order, localisation of main entrance and communication routs inside courtyard. Those early research thereby were the first step to change the meaning of this place from romantic to more scientific. New remote sensing technology allows move even further into scientific direction. The ruins in Radlin have been included into project ArchEO – archaeological applications of Earth Observation techniques. The main aim of the project in case of Radlin is an attempt to answer the question to what extent very high resolution optical satellite imagery might allow better understanding the spatial structure of the place. The various processing techniques were applied to facilitate the detection of archaeological features’ impact on the vegetation condition. It enabled to assess the usefulness of satellite based data in recognizing specific archaeological remains. Thus, potential and limitations of satellite imagery versus other sources of spatial information like historic maps, excavation results, aerial photographs and Lidar will be discussed.

In our paper we would like to present a remote sensing perspective on damage assessment of a hill-fort from central Poland, which is a listed site. The lime stone from this hill is known for its quality and has been excavated from at least medieval time. Due to poorly performed walking prospections the extent of the site has been faultily drawn and the whole extent of the site has been detected. Although most of it is being protected by and natural-archaeological reserve, some part are still being quarried. The goal of our study was to assess the damage done to the landscape of the Chełmo Mount. In our research we will investigate two types of data: very high resolution satellite imagery and LiDAR data (and its derivatives). Supervised classification and thematic change detection applied on archival satellite imagery enabled us to evaluate the progression of quarry in time. The DTM derived from LiDAR data, brought us the possibility to mark the potential outline of the site and the area to be protected as well as a 3D insight in to the damage done to the landscape itself.

Hellenistic and Roman ancient cemeteries are spread all over the territory of the island of Cyprus, consisting one of the major archaeological data sites. Ancient necropoleis due to their tombs “manufacturing” nature, being almost exclusively underground and hewn out of the natural rock, are preserved in a great majority respect to their equivalent domestic and other kinds of architectural remains which are primarily constructed above the ground. Having that in mind, it’s understood that their thorough excavation and study could add significantly to recent archaeological research. Unfortunately, being usually neglected and mainly due to lack of economic resources, no planned excavation of tombs is usually undertaken. On the contrary, most of the tombs are to be found accidentally during infrastructural works or other modern development activities, such as roads, sewage systems and others. This reality of course deprives the archaeologists of a scrupulous study since damages are to be done to the tombs in combination to the tight time schedules that usually pushing towards the fast completion of an archaeological project, not permitting the necessary time for fully understanding in context. In this direction, remote sensing techniques are nowadays an extremely useful tool in the hands of archaeologists, for overlapping the above described modern reality. In the present paper will be briefly addressed the use of remote sensing techniques for monitoring the funerary archaeolandscape of Hellenistic and Roman Cyprus in an effort of sustainable planning, leading to its better preservation.

Conservation and restoration of traditional settlements are amongst the actions that international directives proclaim in order to protect our cultural heritage. Towards this end, a mandatory base step in all archaeological and historical practices includes the surveying and mapping of the study area. Often, new, unexplored or abandoned settlements are considered, where dense vegetation, damaged structures and ruins, incorporation of newer structures and renovation characteristics make the precise surveying procedure a labor intensive and time consuming procedure. Unmanned airborne vehicles (UAVs) have been effectively incorporated into several cultural heritage projects mainly for mapping archeological sites. However, the majority of relevant publications lack of quantitative evaluation of their results and when such a validation is provided it is rather a procedural error estimation readily available from the software used, without independent ground truth verification. In this study, a low-cost custom-built hexacopter prototype was employed to deliver accurate mapping of the traditional settlement of Kamariotis in east Crete, Greece. The case of Kamariotis settlement included highly dense urban structures with continuous building forms, curved walls and missing terraces, while wild vegetation made classic geodetic surveying unfeasible. The resulting maps were qualitatively compared against the ones derived using Google Earth and the Greek Cadastral Orthophoto Viewing platforms to evaluate their applicability for architectural mapping. Moreover, the overall precision of the photogrammetric procedure was compared against geodetic surveying.

As the affordability, reliability and ease-of-use of Unmanned Aerial Vehicles (UAV) advances, the use of aerial surveying for cultural heritage purposes becomes a popular choice, yielding an unprecedented volume of high-resolution, geo-tagged image-sets of historical sites from above. As well, recent developments in photogrammetry technology provide a simple and cost-effective method of generating relatively accurate 3D models from 2D images. These techniques provide a set of new tools for archaeologists and cultural heritage experts to capture, store, process, share, visualise and annotate 3D models in the field. This paper focuses on the methodology used to document the cultural heritage site of Asinou Church in Cyprus using various state of the art techniques, such as UAV, photogrammetry and 3D printing. Hundreds of images of the Asinou Church were taken by a UAV with an attached high resolution, low cost camera. These photographic images were then used to create a digital 3D model and a 3D printer was used to create a physical model of the church. Such a methodology provides archaeologists and cultural heritage experts a simple and cost-effective method of generating relatively accurate 3D models from 2D images of cultural heritage sites.

Marine Spatial Planning (MSP), which is in concept similar to land-use planning, is a public process by which the relevant Member State’s authorities analyse and organise human activities in marine areas to achieve ecological, economic and social objectives. MSP aims to promote sustainable growth of maritime economies, sustainable development of marine areas and sustainable use of marine resources. This paper highlights the importance of MSP and provides basic outcomes of the main European marine development. The already successful MSP plans can provide useful feedback and guidelines for other countries that are in the process of implementation of an integrated MSP, such as Cyprus. This paper presents part of the MSP project, of which 80% funded by the European Regional Development Fund (ERDF) and 20% from national contribution. An overview of the project is presented, including data acquisition, methodology and preliminary results for the implementation of MSP in Cyprus.

In remote sensing, linear transformation methods like the Tasselled Cap (TC) transform have the advantage of reducing the amount and redundancy of data, providing different information in derived components. The TC transform though, has never been specifically developed to perform the study of desert areas. This paper addresses this issue discussing the possible approaches and performing the calculation of a new set of TC transform parameters for SPOT4 and Landsat5 satellites for Top of Atmosphere Reflectance images of selected arid and semi-arid locations in the Middle East and the USA. Compared to previously calculated transforms, results show some differences explained by desert conditions and give the chance for a proper use of this technique in change detection for drylands.

It is well known that green spaces are vital for increasing the quality of life within the urban environment. World Health Organization states that it should be 9 square meters per person at least. European Environment Agency defines that 5000 square meters of green space should be accessible within 300 meters distance from households. Green structure in Northern Cyprus is not sufficient and effective in this manner. In Northern Cyprus, they have neglected the urban planning process and they have started to lose significance and importance. The present work analyzes the accessibility of green spaces in Northern Cyprus cities. Kioneli, Famagusta, Kyrenia and the northern part of Nicosia are analyzed in this manner. To do that, green space structure is analyzed by using digital data. Additionally, accessibility of the green space is measured by using 300-meter buffers for each city. Euclidean distance is used from each building and accessibility maps are generated. Kyrenia and Famagusta have shortage in green space per capita. The amount of green space in these cities is less than 4 square meters. The factors affecting the accessibility and utilization of public spaces are discussed to present better solutions to urban planning.

Traffic accidents are causing major deaths in urban environments, so analyzing locations of the traffic accidents and their reasons is crucial. In this manner, patterns of accidents and hotspot distribution are analyzed by using geographic information technology. Locations of the traffic accidents in the years 2011, 2012 and 2013 are combined to generate the kernel distribution map of Kyrenia City. This analysis aims to find high dense intersections and segments within the city. Additionally, spatial autocorrelation methods Local Morans I and Getis-Ord Gi are employed . The results are discussed in detail for further analysis. Finally, required changes for numerous intersections are suggested to decrease potential risks of high dense accident locations.

Forest fires greatly influence the stability and functions of the forest ecosystems. The ever increasing need for accurate and detailed information regarding post-fire effects (burn severity) has led to several studies on the matter. In this study the combined use of Very High Resolution (VHR) satellite data (GeoEye), Objectbased image analysis (OBIA) and Composite Burn Index (CBI) measurements in estimating burn severity, at two different time points (2011 and 2012) is assessed. The accuracy of the produced maps was assessed and changes in burn severity between the two dates were detected using the post classification comparison approach. It was found that the produced burn severity map for 2011 was approximately 10% more accurate than that of 2012. This was mainly attributed to the increased heterogeneity of the study area in the second year, which led to an increased number of mixed class objects and consequently made it more difficult to spectrally discriminate between the severity classes. Following the post-classification analysis, the severity class changes were mainly attributed to the trees’ ability to survive severe fire damage and sprout new leaves. Moreover, the results of the study suggest that when classifying CBI-based burn severity using VHR imagery it would be preferable to use images captured soon after the fire.

Land subsidence is a common natural hazard striking extensive areas worldwide that can be triggered by geological and/or anthropogenic factors. In many cases, subsidence affects urbanized areas and causes remarkable economic loss. Adopted policies and solutions for land subsidence management can be various, but despite this variability, where mitigation methods have to be put into practice, the detailed mapping, characterization and simulation of subsidence have to precede their design and implementation. In the framework of the Terrafirma Project (www.terrafirma.eu.com), the exploitation of Persistent Scatterer Interferometry (PSI) for subsidence analysis has been promoted. Satellite interferometry, thanks to its wide spatial coverage and its millimeter accuracy, is ideally suited for the measurement of the spatial extent and magnitude of surface deformations associated with subsidence phenomena. Three validated case studies, where subsidence is caused by different factors, are presented here: the wide area of Rome (Italy), the Gioia Tauro plain (Italy) and the Kalochori village (Greece). These case studies have been selected with the aim of showing the main activities that must be covered and performed when dealing with geohazard investigations, i.e., mapping, monitoring and modeling. Particularly, data from ERS1/2, Envisat and Radarsat satellites have been exploited to map ground deformation in the area of Rome and to monitor the ground subsidence in the Gioia Tauro plain. Due to the large availability of geological and geotechnical data, the area of Kalochori village has been selected to model the land subsidence by applying Finite Element simulation. Results of the simulation have been validated with PSI techniques.

PREFER is a Copernicus project of the EC-FP7 program which aims developing spatial information products that may support fire prevention and burned areas restoration decisions and establish a relevant web-based regional service for making these products available to fire management stakeholders. The service focuses to the Mediterranean region, where fire risk is high and damages from wildfires are quite important, and develop its products for pilot areas located in Spain, Portugal, Italy, France and Greece. PREFER aims to allow fire managers to have access to online resources, which shall facilitate fire prevention measures, fire hazard and risk assessment, estimation of fire impact and damages caused by wildfire as well as support monitoring of post-fire regeneration and vegetation recovery. It makes use of a variety of products delivered by space borne sensors and develop seasonal and daily products using multi-payload, multi-scale and multi-temporal analysis of EO data. The PREFER Service portfolio consists of two main suite of products. The first refers to mapping products for supporting decisions concerning the Preparedness/Prevention Phase (ISP Service). The service delivers Fuel, Hazard and Fire risk maps for this purpose. Furthermore the PREFER portfolio includes Post-fire vegetation recovery, burn scar maps, damage severity and 3D fire damage assessment products in order to support relative assessments required in context of the Recovery/Reconstruction Phase (ISR Service) of fire management.

In this paper a specific example of the synergistic use of geotechnical survey, remote sensing data and GIS for rockfall risk evaluation is presented. The study area is located in Western Greece. Extensive rockfalls have been recorded along Patras – Ioannina highway just after the cable-stayed bridge of Rio-Antirrio, at Klokova site. The rockfalls include medium- sized limestone boulders with volume up to 1.5m3. A detailed engineering geological survey was conducted including rockmass characterization, laboratory testing and geological - geotechnical mapping. Many Rockfall trajectory simulations were done. Rockfall risk along the road was estimated using spatial analysis in a GIS environment.

Several algorithms have been effectively used to identify the seismic signature of rockfall incidents, which constitute a significant threat for human lives and infrastructure especially when occurring along transportation networks. These algorithms have been mostly evaluated using data from large scale rockfall events that release a large amount of energy. However, low-energy rockfall events (< 100 Joules) triggered by small-sized individual rocks falling from small heights can be severely destructive. In this study, a three-parameter algorithm has been developed to identify low-energy rockfall events. An experimental setup was implemented to 1) validate the results obtained by this algorithm against visual inspection of seismic signals records, 2) define the optimal algorithm parameterization to minimize false alarms, and 3) investigate whether tri-axial vibration monitoring can be replaced by a uniaxial device in order to reduce the installation cost of a real-time rockfall monitoring system. It was found that the success rate of the proposed algorithm exceeds 80%independently of the parameters used, while event identification at a maximum distance with minimal false alarms was achieved when using mean± 3σ as the threshold criterion and 6 ms and 4 ms as the trigger and event window parameters respectively. Finally, it was found that for the specific experimental setup, a uniaxial device could be used for rockfall event identification.

The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with the earthquake date and in this case the FDL method coincides with the MFDL. Based on the MDFL method we present the prediction method capable of predicting global events or localized earthquakes and we will discuss the accuracy of the method in as far as the prediction and location parts of the method. We show example calendar style predictions for global events as well as for the Greek region using planetary alignment seeds.

An integrated modeling system, developed in the framework of “Hydromentor” research project, is applied to evaluate crop water requirements for operational water resources management at Lake Karla watershed, Greece. The framework includes coupled components for operation of hydrotechnical projects (reservoir operation and irrigation works) and estimation of agricultural water demands at several spatial scales using remote sensing. The study area was sub-divided into irrigation zones based on land use maps derived from Landsat 5 TM images for the year 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used to derive actual evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat TM imagery. Agricultural water needs were estimated using the FAO method for each zone and each control node of the system for a number of water resources management strategies. Two operational strategies of hydro-technical project development (present situation without operation of the reservoir and future situation with the operation of the reservoir) are coupled with three water demand strategies. In total, eight (8) water management strategies are evaluated and compared. The results show that, under the existing operational water resources management strategies, the crop water requirements are quite large. However, the operation of the proposed hydro-technical projects in Lake Karla watershed coupled with water demand management measures, like improvement of existing water distribution systems, change of irrigation methods, and changes of crop cultivation could alleviate the problem and lead to sustainable and ecological use of water resources in the study area.

The objective of this work is the development of a new approach for the estimation of water requirements for the most important crops located at Karla Watershed, central Greece. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used as a basis for the derivation of actual evapotranspiration (ET) and crop coefficient (ET_rF) values from Landsat ETM+ imagery. MODIS imagery has been also used, and a spatial downscaling procedure is followed between the two sensors for the derivation of a new NDVI product with a spatial resolution of 30 m x 30 m. GER 1500 spectro-radiometric measurements are additionally conducted during 2012 growing season. Cotton, alfalfa, corn and sugar beets fields are utilized, based on land use maps derived from previous Landsat 7 ETM+ images. A filtering process is then applied to derive NDVI values after acquiring Landsat ETM+ based reflectance values from the GER 1500 device. ETrF vs NDVI relationships are produced and then applied to the previous satellite based downscaled product in order to finally derive a 30 m x 30 m daily ET_rF map for the study area. CropWat model (FAO) is then applied, taking as an input the new crop coefficient values with a spatial resolution of 30 m x 30 m available for every crop. CropWat finally returns daily crop water requirements (mm) for every crop and the results are analyzed and discussed.

The aim of our study was to verify the accuracy and the usability of Moderate resolution imaging spectroradiometer (MODIS) 13Q1 product for corn yield estimation on a local level for 2014 year. Product 13Q1 consists of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) 16-day composites with 250 m spatial resolution. The estimation is based on ground truth data (sowing structures for 8 years) which was provided by local agricultural organization in Vojvodina, Serbia. The indices were used in linear regression, where the average yield for corn was the dependent variable, NDVI and EVI were independent variables. Average corn yield was estimated approximately 15 days before the beginning of the harvest and compared with official results. Depending on the used linear method, relative errors ranged from 0.6 % to 7.4 %. Overall, coefficients of determination (R²) ranged from 0.66 to 0.75 and were significant at 0.05. The smallest difference between official results for corn yield and our estimate when using NDVI was 0.59 t/ha, when using EVI the smallest difference was 0.07 t/ha. Paper showed that NDVI and EVI from MODIS follow linear relationship with average corn yield and can be used in estimation of crop yields in Serbia and also that EVI produces better prediction results than NDVI. The crop yield estimation can be used for similar cultivated plants in Serbia and for longer period dataset.

Plastic covering is a common practice in agricultural fields. From an agronomic point of view, plastic coverings offer many advantages against unfavourable growing conditions. This explains their widespread utilization with consequent positive impact on local economy. On the other hand, plasticulture raises both environmental and landscape issues. In the Apulia Region (Italy) the wide implementation of such practice generally relates to vineyard cultivation. Continuous vineyard protection has resulted in negative effects on the hydrogeological balance of soils, causing a deep modification of the traditional rural landscape and therefore affecting its quality. To guarantee both the protection of local economy as well as the preservation of local environment and landscape features, a detailed site mapping of the areas involved is necessary. Indeed, the quantification of this phenomenon is essential in the periodic updating of the existing land use database and in the development of local policies. In this study we evaluate the potential of the novel Thermal Infrared Sensor bands (TIRS) provided by the LANDSAT 8 mission in plasticulture discrimination. Using the evident anomaly retrieved in the study area on the Quality Assessment (QA) band, a fast procedure involving TIRS data was developed, proposing a new index (Plastic Surface Index- PSI) able to emphasize plasticulture. For the aim of this study, two different acquisition dates on a test area in the Apulia region (Italy) were analyzed, one in the growing season with high plastic covering density and one in the post-harvest period with low plastic cover density.

Remote sensing and space technologies are increasingly called to offer innovative solutions for current challenges induced by climatic and global change. One of the main priorities of the European Space Policy regards the economic independence of the old continent in this sector. In terms of research and innovation this inevitably leads to numerous attempts in having independent market of services that would tackle specific needs of the citizens. Agriculture, for example, is one of the sectors majorly subsidized by European funds on national, regional and local level, with the aim to foster a more productive and sustainable development. Due to a large territorial scale at which agricultural phenomena are observed, and thus the spatial resolution required, it is also one of the main sectors that has been monitored from space over the past 30 years. In fact, one of the main missions of USA Landsat satellites was to provide a continuous and systematic overview of the globe for the purposes of an effective monitoring of the environment. This paper represents an overview of the ongoing initiatives in Space research done for the field of agriculture and landscape monitoring. In particular, the paper looks into the future possibilities that will be offered by full, open and free-of-charge data arriving from ongoing Copernicus missions and the contribution of Sentinel satellites to the agricultural sector.

Remote sensing, as the tool for spatially continuous measurements has become a trend for estimating Crop Yield since economically efficient agricultural management is highly dependent on detailed temporal and spatial knowledge of the processes affecting physiological crop development. This paper aims at examining the use of field spectroscopy along with Landsat’s satellite imagery in order to test the accuracy of raw satellite data and the impact of atmospheric effects on determining crop yield derived from models using remotely sensed data. The spectroradiometric retrieved Vegetation Indices(VI) of Durum wheat, is directly compared to the corresponding VI of Landsat 7 ETM+ and 8 OLI, sourcing from both atmospherically corrected and not corrected satellite images in order to test the effects of atmosphere upon them. Vegetation Indices are vital in the procedure for estimating Crop Yield since they are used in stochastic or empirical models for describing or predicting crop yield. Leaf Area Index, which is also inferred using VI, is also compared to the real values of LAI that are measured using the SunScan instrument, during the satellite’s overpass. Crop Yield is finally determined using the Cyprus Agricultural Research Institute’s Crop Yield model for Durum wheat, adapted to satellite data, and is used to examine the impact of atmospheric effects. The results have prevailed that if crop yield models using remote sensing imagery, do not apply atmospheric effects algorithms, then there is statistically significant difference in the prediction from the real yield and hence a significant error regarding the model. The study’s goal is to illustrate the need of atmospheric effects removal on remotely sensed data especially for models using satellite images.

Adoption of precision agriculture techniques requires the development of specialized tools that provide spatially distributed information. Both flying platforms and airborne sensors are being continuously evolved to cover the needs of plant and soil sensing at affordable costs. Due to restrictions in payload, flying platforms are usually limited to carry a single sensor on board. The aim of this work is to present the development of a vertical take-off and landing autonomous unmanned aerial vehicle (VTOL UAV) system for the simultaneous acquisition of high resolution vertical images at the visible, near infrared (VNIR) and thermal infrared (TIR) wavelengths. A system was developed that has the ability to trigger two cameras simultaneously with a fully automated process and no pilot intervention. A commercial unmanned hexacopter UAV platform was optimized to increase reliability, ease of operation and automation. The designed systems communication platform is based on a reduced instruction set computing (RISC) processor running Linux OS with custom developed drivers in an efficient way, while keeping the cost and weight to a minimum. Special software was also developed for the automated image capture, data processing and on board data and metadata storage. The system was tested over a kiwifruit field in northern Greece, at flying heights of 70 and 100m above the ground. The acquired images were mosaicked and geo-corrected. Images from both flying heights were of good quality and revealed unprecedented detail within the field. The normalized difference vegetation index (NDVI) was calculated along with the thermal image in order to provide information on the accurate location of stressors and other parameters related to the crop productivity. Compared to other available sources of data, this system can provide low cost, high resolution and easily repeatable information to cover the requirements of precision agriculture.

In the Aegean Sea and Eastern Mediterranean there are large discrepancies between in situ and satellite ocean colour derived chlorophyll concentrations. The quantity that is monitored by ocean colour satellites and that can be used in the estimation of chlorophyll concentration is the remote sensing reflectance, defined as the ratio of the water leaving spectral radiance to the downwelling spectral irradiance. It can be determined in the field, with either above or in-water radiance and irradiance measurements. The complex optical properties of the North-East Aegean Sea, including radiance and irradiance, were studied during the AegeanMarTech project. Chlorophyll concentration estimates were derived from simultaneous above and in-water radiometric measurements. These were validated against chlorophyll concentration field data and compared against concurrent MODIS data from which chlorophyll was derived using two simple empirical algorithms. It was found that the MedOC3 algorithm outperforms the operational OC3M-547 algorithm and produces the least bias when compared against HPLC derived in situ chlorophyll. It is concluded that the greatest uncertainty in the inversion arises due to CDOM absorption below the 488 nm band. The reflectance ratios indicated that there is always an excess of yellow matter present in the study area and the water type could not be characterized optically as ‘’typical open ocean” Case 1.

Beaches are both sensitive and critical coastal system components as they: (i) are vulnerable to coastal erosion (due to e.g. wave regime changes and the short- and long-term sea level rise) and (ii) form valuable ecosystems and economic resources. In order to identify/understand the current and future beach morphodynamics, effective monitoring of the beach spatial characteristics (e.g. the shoreline position) at adequate spatio-temporal resolutions is required. In this contribution we present the results of a new, fully-automated detection method of the (2-D) shoreline positions using high resolution video imaging from a Greek island beach (Ammoudara, Crete). A fully-automated feature detection method was developed/used to monitor the shoreline position in geo-rectified coastal imagery obtained through a video system set to collect 10 min videos every daylight hour with a sampling rate of 5 Hz, from which snapshot, time-averaged (TIMEX) and variance images (SIGMA) were generated. The developed coastal feature detector is based on a very fast algorithm using a localised kernel that progressively grows along the SIGMA or TIMEX digital image, following the maximum backscatter intensity along the feature of interest; the detector results were found to compare very well with those obtained from a semi-automated ‘manual’ shoreline detection procedure. The automated procedure was tested on video imagery obtained from the eastern part of Ammoudara beach in two 5-day periods, a low wave energy period (6-10 April 2014) and a high wave energy period (1 -5 November 2014). The results showed that, during the high wave energy event, there have been much higher levels of shoreline variance which, however, appeared to be similarly unevenly distributed along the shoreline as that related to the low wave energy event, Shoreline variance ‘hot spots’ were found to be related to the presence/architecture of an offshore submerged shallow beachrock reef, found at a distance of 50-80 m from the shoreline. Hydrodynamic observations during the high wave energy period showed (a) that there is very significant wave energy attenuation by the offshore reef and (b) the generation of significant longshore and rip flows. The study results suggest that the developed methodology can provide a fast, powerful and efficient beach monitoring tool, particularly if combined with pertinent hydrodynamic observations.

We present the methods and results of investigation of the Anapa bay-bar shoreline dynamics, obtained from the analysis of historical and recent data of satellite imaging and aerial survey. It was revealed that several erosion regions exist along the Anapa bay-bar shore (the revealed retreat of the water edge is greater than 70 m over 50 years). A relatively stable region was also found there. In addition, the analysis of short-period dynamics of the water edge location revealed that the short-term displacement of the water edge relative to its mean position is as high as 30 m. These data clarified the dynamics of the Anapa bay-bar shoreline, which is important for the understanding of lithodynamic processes in the coastal zone and developing the forecast of the further evolution of the bay-bar geosystem.

The overall objective of this work is the development of a District Information System (DIS) which could be used by stakeholders for the purposes of a district day-to-day water management as well as for planning and strategic decisionmaking. The DIS was developed from a GIS-based modeling approach, which integrates a generic crop model and a hydraulic model of the transport/distribution system, using land use maps generated by Landsat TM imagery. The main sub-objectives are: (i) the development of an operational algorithm to retrieve crop evapotranspiration from remote sensing data, (ii) the development of an information system with friendly user interface for the data base, the crop module and the hydraulic module and (iii) the analysis and validation of management scenarios from model simulations predicting the respective behavior. The Lake Karla watershed is used in this study, but the overall methodology could be used as a basis for future analysis elsewhere. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) values from Landsat TM imagery. Meteorological data from the archives of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) has also been used. The methodology was developed using high quality Landsat TM images during 2007 growing season. Monthly ET values are used as an input to CROPWAT model. Outputs of CROPWAT model are then used as input for WEAP model. The developed scenario is based on the actual situation of the surface irrigation network of the Local Administration of Land Reclamation (LALR) of Pinios for the year of 2007. The DIS is calibrated with observed data of this year and the district parameterization is conducted based on the actual operation of the network. The operation of the surface irrigation network of Pinios LALR is simulated using Technologismiki Works, while the operation of closed pipe irrigation network of Lake Karla LALR is simulated using Watercad. Four alternative scenarios have been tested with the DIS: reduction of channel losses, alteration of irrigation methods, Introduction of greenhouse cultivation, and operation of the future Lake Karla network. The results of the simulation for the historical period indicate that the water pumped from Pinios LALR is not enough to serve irrigation requirements. The spatial and temporal variation of the unmet and unsatisfied water demand has been estimated. Simulation of the four alternative scenarios indicated that the alteration of irrigation methods scenario mainly increases the efficiency of the irrigation network.

In the area Verbyanaya bay-bar (Sea of Azov) in an attempt to create large-scale cartographic base and subsequent thematic mapping of the geographical environment components airborne laser scanning and aerial photography were conducted. Airborne laser scanning data formed the basis of a comprehensive study of the coastal zone components. Methodical research apparatus includes receiving and processing technology of laser reflection points, constructing highprecision digital elevation model and raster surfaces. Mosaic of aerial photography is converted into a format mosaic – a geometrically correct image of the terrain. Set of high-precision digital surface models and thematic raster images obtained for specific dates, allows to analyze the dynamic adjustment of components of the coastal zone (shoreline, beach, shore dam with surge prism).

This work analyzes the potentiality of WorldView-2 satellite data for retrieving the Leaf Area Index (LAI) area located in Apulia, the most Eastern region of Italy, overlooking the Adriatic and Ionian seas. Lacking contemporary in-situ measurements, the semi-empiric method of Clevers (1989) (CLAIR model) was chosen as a feasible image-based LAI retrieval method, which is based on an inverse exponential relationship between the LAI and the WDVI (Weighted Difference Vegetation Index) with relation to different land covers. Results were examined in homogeneous land cover classes and compared with values obtained in recent literature.

An abundance of GIS and Remote Sensing based spatial analysis studies result in various types of suitability maps, where selected regions are classified according to application driven qualitative or quantitative rules. Often, upon the resulting classified regions which define spatially constrained classes, users intent to position facilities in order to satisfy a series of demand sites spread throughout the study area. This fine tuning procedure, not tackled under classic clustering and location analysis algorithms, is addressed through the extension of k-means algorithm, by restricting cluster centers inside a priori outlined regions, while minimizing distance metrics towards demand locations. Experimentation in both synthetic and real based datasets shows the applicability of the approach and demonstrates the overall performance of the algorithm.

Monitoring urban growth process and its patterns for the city of Bucharest was the starting point in our attempt to identify and propose a more general procedure for monitoring this type of process in Romania using remote sensing data. Several important technical aspects such as comparable data sources, comparable algorithms, interoperability issues as well as final presentation standards are discussed. The paper is meant to be considered as a basis for promoting a unitary technical approach concerning urban growth monitoring in Romania using remote sensing data.

For the 2013-14 year as part of the study Anapa accumulative coasts was performed aerial survey, including airborne laser scanning and digital aerial photography. Size of the survey was 48 km, width of pregnancy ranged from 500 to 1500 meters, depending on the configuration of the coastline. Surveying was done using aerial mapping production Leica Geosystems, consisting of airborne laser scanner ALS70-CM and digital aerophotocamera RCD-30. The data allowed us to obtain highly accurate digital terrain models and orthophotos. To perform morphological and morphometric analysis of the territory at the micro and nanoscale.

Rockfall incidents affect civil security and hamper the sustainable growth of hard to access mountainous areas due to casualties, injuries and infrastructure loss. Rockfall occurrences cannot be easily prevented, whereas previous studies for rockfall multiple sensor early detection systems have focused on large scale incidents. However, even a single rock may cause the loss of a human life along transportation routes thus, it is highly important to establish methods for the early detection of small-scale rockfall incidents. Terrestrial photogrammetric techniques are prone to a series of errors leading to false alarm incidents, including vegetation, wind, and non relevant change in the scene under consideration. In this study, photogrammetric monitoring of rockfall prone slopes is established and the resulting multi-temporal change imagery is processed in order to minimize false alarm incidents. Integration of remote sensing imagery analysis techniques is hereby applied to enhance early detection of a rockfall. Experimental data demonstrated that an operational system able to identify a 10-cm rock movement within a 10% false alarm rate is technically feasible.

The impact of the upper atmosphere on navigation, communication as well as surveillance systems is defined by the state of the ionosphere and in particular by variations in its electron density profile along the signal propagation path. The requirement for the accurate specification of the electron density profile stems from the fact that the electron density at each altitude determines the refractive index for radiowaves that are refracted by or penetrate the ionosphere and therefore affects significantly navigation and communication signals. Consequently satellite systems that are based on trans-ionospheric propagation may be affected by complex variations in the ionospheric structure in space and time leading to degradation of the availability, accuracy and reliability of their services. Therefore the specification of the electron density profile over a geographical region is very important within the context of operation of such systems. Although regional models have been developed for such a purpose by interpolating data coming from different instruments using various techniques, for a limited geographical scope, the single station model approach is the preferable option as it best encapsulates the behaviour of the ionosphere over the station. This paper presents the development of an Artificial Neural Network (ANN) model for the electron density profile of the ionosphere over Cyprus based on manually scaled ionograms collected at the Nicosia ionosonde station during the period 2009-2013.

The specification of the near surface ground conditions is highly important for the design of civil constructions. These conditions determine primarily the ability of the foundation formations to bear loads, the stress – strain relations and the corresponding settlements, as well as the soil amplification and corresponding peak ground motion in case of dynamic loading. The static and dynamic geotechnical parameters as well as the ground-type/soil-category can be determined by combining geotechnical and geophysical methods, such as engineering geological surface mapping, geotechnical drilling, in situ and laboratory testing and geophysical investigations. The above mentioned methods were combined, through the Thalis ″Geo-Characterization″ project, for the site characterization in selected sites of the Hellenic Accelerometric Network (HAN) in the area of Crete Island. The combination of the geotechnical and geophysical methods in thirteen (13) sites provided sufficient information about their limitations, setting up the minimum tests requirements in relation to the type of the geological formations. The reduced accuracy of the surface mapping in urban sites, the uncertainties introduced by the geophysical survey in sites with complex geology and the 1D data provided by the geotechnical drills are some of the causes affecting the right order and the quantity of the necessary investigation methods. Through this study the gradual improvement on the accuracy of site characterization data is going to be presented by providing characteristic examples from a total number of thirteen sites. Selected examples present sufficiently the ability, the limitations and the right order of the investigation methods.

A spectral calibration algorithm for the hyperspectral geostationary environmental monitoring spectrometer (GEMS) onboard GEO-KOMPSAT-2B (GK-2B) planned to launch in 2019 has been developed. Although spectral registration for the CCD detector is done by the optical parameters prepared during the ground test of the instrument, the algorithm is applied for the improved spectral accuracy. The prototype algorithm is based on the best fitting of the measured spectrum to the known high resolution reference spectrum such as the solar irradiance. To characterize the prototype algorithm, a series of sensitivity tests for various spectral parameters, such as squeeze, shift, spectral response function, and reference solar spectrum, has been performed. The prototype algorithm shows a minimal sensitive to the uncertainties associated with several parameters such as squeeze, shift, or spectral band. However, the algorithm performance degrades by an order if the spectral response function including its shape has uncertainty. Thus, it is recommended to measure the spectral response function at the ground test as accurately as possible. Furthermore, the prototype algorithm is also highly sensitive to the used reference solar spectrum, which needs further investigation.

The five channel meteorological imager (MI) on-board the geostationary Communication, Ocean, and Meteorological Satellite (COMS) of Korea has been operationally used since April 2011. For a better utilization of the MI data, a rigorous characterization of the four infrared channel data has been conducted using the GSICS (Global Space-based Inter-Calibration System) approach with the IASI (Infrared Atmospheric Sounding Interferometer) on-board the European Metop satellite as the reference instrument. Although all four channels show the uncertainty characteristics that are in line with the results from both the ground tests and the in-orbit-test, there shows an unexpected systematic bias in the water vapor channel of MI, showing a cold bias at the warm target temperature and a warm bias with the cold target temperature. It has been shown that this kind of systematic bias could be introduced by the uncertainties in the spectral response function (SRF) of the specific channel which is similar to the heritage instruments on-board GOES series satellite. An extensive radiative transfer simulation using a radiative transfer model has confirmed that the SRF uncertainty could indeed introduce such a systematic bias. By using the collocated data set consisting of the MI data and the hyperspectral IASI data, the first order correction value for the SRF uncertainty is estimated to be about 2.79 cm-1 shift of the central position of the current SRF.

The delineation of ocean regions with similar water quality characteristics is an all important component of the study of marine environment with direct implications for management actions. Marine eutrophication constitutes an important facet of ocean water quality, and pertains to the natural process representing excessive algal growth due to nutrient supply of marine systems. Remote sensing technology provides the de-facto means for marine eutrophication assessment over large regions of the ocean, with increasingly high spatial and temporal resolutions. In this work, monthly measurements of sea water quality variables – chlorophyll, nitrates, phosphates, dissolved oxygen – obtained from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) with spatial resolution 0.125 degrees for the East Mediterranean region over the period January 1999 to December 2010, are used to define regions or zones of similar eutrophication levels. A novel variant of the K-medoids clustering algorithm is proposed, whereby the spatial association of the different variables (multivariate textural information) is explicitly accounted for in terms of the multivariate variogram; i.e., a measure of joint dissimilarity between different variables as a function of geographical distance. Similar water quality regions are obtained for various months and years, focusing on the spring season and on the qualitative comparison of the traditional and proposed classification methods. The results indicate that the proposed clustering method yields more physically meaningful clusters due to the incorporation of the multivariate textural information.

Our study is focused on the Anapa Bay Bar, a 43-km long body of sand on the Black Sea coast, which stretches from the Russian town of Anapa to the Zhelezny Rog Cape on the Taman’ peninsula. It is a major recreational resource and a host to unique ecosystems of beaches and partially vegetated sand dunes. Due to large recreational pressure, it is important to identify features of the bay bar that have to be preserved in order to keep this resource sustainable. We have conducted landscape and morphological mapping with WorldView-2 images. Methods included field research, analysis of multitemporal stereopairs and automated image interpretation to create maps of key areas of the Anapa Bay Bar. In our paper we showcase the map for a section of the Anapa Bay Bar created through visual image interpretation. It presents all morphological elements such as beaches, sand dunes, sand ridges and lowlands adjoining lagoons. Each element has its specific vegetation and sustainability against recreational pressure. We also present results of automated image analysis of seasonal dynamics of the beach and dunes on the basis of multitemporal imagery.