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Cartographic cultural heritage preserved in worldwide archives is often stored in the original paper version only, thus restricting both the chances of utilization and the range of possible users. The Web C.A.R.T.E. system addressed this issue with regard to the precious cadastral maps preserved at the State Archive of Como. Aim of the project was to improve the visibility and accessibility of this heritage using the latest free and open source tools for processing, cataloguing and web publishing the maps. The resulting architecture should therefore assist the State Archive of Como in managing its cartographic contents. After a pre-processing consisting of digitization and georeferencing steps, maps were provided with metadata, compiled according to the current Italian standards and managed through an ad hoc version of the GeoNetwork Opensource geocatalog software. A dedicated MapFish-based webGIS client, with an optimized version also for mobile platforms, was built for maps publication and 2D navigation. A module for 3D visualization of cadastral maps was finally developed using the NASA World Wind Virtual Globe. Thanks to a temporal slidebar, time was also included in the system producing a 4D Graphical User Interface. The overall architecture was totally built with free and open source software and allows a direct and intuitive consultation of historical maps. Besides the notable advantage of keeping original paper maps intact, the system greatly simplifies the work of the State Archive of Como common users and together widens the same range of users thanks to the modernization of map consultation tools.

In the State Archive of Como, Northern Italy, about 15,000 historical maps belonging to different national cadastral productions are preserved. The Web C.A.R.T.E. project was started to enhance the accessibility of this valuable cartographic heritage using FOSS (Free and Open Source Software) technologies. The system, which implements specific web geoservices for cataloguing and visualization, should assist the State Archive of Como in the digital management of its cartographic resources and related information. After the high-resolution digitization step, maps undergo a georeferencing operation. A special statistical procedure for choosing the best mathematical model was developed, verifying also strengths and weaknesses of georeferencing with a common free and Open Source GIS. Next, metadata consistent with current Italian standards were added to the georeferenced maps using an ad hoc localized version of GeoNetwork Opensource (recently provided as the official Italian version of the software). A dedicated WebGIS system was built for publishing the georeferenced cadastral maps. This system is capable of navigating large raster data in a georeferenced framework and easily retrieving their metadata. The WebGIS system for the State Archive of Como is an important contribution for the preservation of the original historical paper maps and also a great modernization and simplification of the end user's access to this archive.

Analysis other than simple access and visualization is the emerging trend within the web community [Berners-Lee 2007]. With the rapid development of the Internet and web technologies, “the traditional approach to publishing maps on the Internet ‘by GIS experts, for GIS experts’ is outdated, ineffective and unusable as Web mapping becomes more and more mainstream” [van der Vlugt and Stanley 2005]. Over the last few years, we have seen more and more traditional GIS functions being integrated into web mapping/GIS applications in a way transparent to users, using distributed analytical and geoprocessing services coordinated by well-defined workflows [Yang and Raskin 2009]. Web service technology has played one of the key roles in this transition. As the service-driven paradigm continues to dominate web mapping and GIS development, web-based geospatial analytical services have drawn the attention of many in the field, hoping to build such services on top of more mature basic data services. Given the complex nature of analytical services, including modelling, simulation, function and visualization services, the orchestration of web mapping and geoprocessing services from different sources becomes increasingly important. The trend towards analytical geospatial web services continues with intelligent analytical capability, which involves indepth study on dynamic geospatial service composition, for example. It is also expected that intelligent analytical services will be enhanced with further developments in Geographic Knowledge Discovery (GKD), spatial data mining techniques and tools, web-based modelling and simulation, augmented reality applications, agent-based systems and paradigms [Hutchinson and Veenendaal 2011], etc. The articles included in this special issue contribute to the capacity building towards analytical geospatial web. The three feature articles selected for this special issue touch on web geoprocessing, visualization and thematic mapping tools. The issue begins with the article authored by Eberle and Strobl, Web-based

The work presents the comparison of results obtained with two different methods for filtering LiDAR data, focusing specifically on ground (bare Earth) and vegetation classification. Data was filtered with TerraScan, a leading proprietary software for processing LiDAR point clouds, and with the specific modules available in GRASS GIS. The LiDAR dataset (1.5 points/m2) was produced with an Optech ALTM Gemini and covers an area of the Sardinia region where there are available also orthophotos and false color infrared images, both with resolution of 20 cm. Concerning TerraScan two classifications were computed: the former is a completely automatic and the latter is a semi-automatic one, with a heavy manual reclassification of the previously obtained automatic results. In GRASS GIS the modules developed by the Geomatic Laboratory of the Politecnico di Milano were applied; parameters to be used by the modules were at first calibrated on specific training sub-areas. The purpose of the work is the evaluation of the accuracy in ground and vegetation extraction. Moreover, since GRASS divides points belonging to vegetation in two classes, corresponding to high and low vegetation, the comparison is done for the latter category. The choice of concentrating on this category is motivated by the greater difficulty in distinguishing between terrain and low vegetation. As “ground truth” the result of the supervised classification performed on the orthophotos and the false color infrared images was used.

The paper presents a procedure developed to calibrate the value of parameters used in GRASS algorithms that perform LiDAR’s data filtering. These cascade commands, developed by the Geomatic Laboratory of the Politecnico di Milano, were empirically calibrated for low spatial resolution LiDAR data. UCODE_2005 from USGS was the software employed in the calibration, mainly chosen because of its flexibility and adaptability to every kind of model; it carries out an inverse model calibration in an iterative way and performs the sensitivity analysis on the parameters. In the end the filtering results obtained after the calibration were compared to the one obtained with the software TerraScan in a completely automatic procedure.

Environmental monitoring is a fundamental process in the design, construction, operation and decommissioning phases of constructing large structures, such as highways, high-speed railways, and airports. Many different actors are involved in these steps: the owner (public or private); the planning, construction, and operation managers; the environmental teams executing the monitoring; the government department or agency responsible for protecting the environment and the health of the population; and, finally, the policy-makers. The environmental agency itself is composed of various domain experts dealing with different environmental arenas (air, water, etc.). Since most of the collected information refers to space and time, GISs are natural tools for storing and processing the data. Nevertheless, instruments, people, and communications technology are involved, and there is a potential for failure, waste of time and unnecessary costs to appear. A web platform based on OGC web services and allowing for sharing and processing the sensor and geographic information can greatly improve workflow management. This article presents a description of a working pilot that can serve as a solution to managing such a project, because it makes it possible to integrate geodata (maps and orthophotos) from different sources and to visualize and analyze the sensor data with respect to both time and space.

Digital Earth is a virtual representation of the planet, encompassing all its systems and forms, including human societies, manifested as a multidimensional, multiscale, multitemporal, and multilay...

The importance of digital orthophotos in spatial databases has increased in recent years, since they are an efficient, low-cost and, if properly managed, accurate product. Usually, the generation of orthophotos is carried out using digital terrain models (DTMs); meaning without taking into account vegetation, buildings, and other attached and detached structures. This leads to low accuracies in urban areas, bringing distortions into the image. To avoid this unwanted effect, one must adopt a digital surface model (DSM), as proposed by Amhar et al. (Int Arch Photogrammetry Remote Sens 32(4):16-22, 1998). The method proposed in this paper allows for the creation of true orthophotos by using a DSM to refine the representation of buildings. The pixel size of the DSM must be similar to that of the true orthophoto in order to model the roof edges with sufficient accuracy. This paper presents a new method capable of correcting the roof displacement using an approach based on the integration of several products today available in public administrations, such as a geodatabase, DTMs/DSMs, and light detection and ranging (LiDAR) data. The method is based on a rigorous modelling of simple roofs starting from their 2D projection in the geodatabase, while information about their heights can be obtained using LiDAR data. For some selected simple roofs, automatic modelling can be carried out, in which a robust interpolation method, such as RANSAC, is used to model the pitches identified by a clustering procedure. For complex roofs, where creating a rigorous model in a fully automatic way is not possible, a procedure based on the thickening of a DSM is carried out.

The question the paper deals with refers to how it is possible to update existing geodatabases considering both their accuracies and those of the new measurements taken for their updating. Traditionally, maintaining geodatabases (or map bases) has been highly time consuming, costly, and sometimes difficult work, especially in urban and high-density areas. The most common procedure is to globally generate geodatabases every few years by photogrammetric techniques. On the opposite, the possibility of dynamically updating the landscape information from a maintained core spatial database can be considered as an appealing alternative to traditional map revision techniques. A kriging solution, based on the hypothesis that the vector field of the position error on a geodatabase is a homogeneous, isotropic intrinsic random field with constant mean and variogram depending only on the squared distance, known a priori from the relative accuracy of the map, is proposed. The method is a first approach to the problem, as far as at the moment it does not consider constraints to which points on the geodatabase must adapt to. That is the reason why it is presented as an intermezzo.

Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic. In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment. The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation–orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available. To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV since only the HOV is implemented. The software comparison guaranteed about the overall correctness and good performances of the SISAR model, whereas the results showed the good features of the LOOCV method.

Driven by the rise of Web 2.0 and the non-stop spread of mobile device sensors, the concept of Public Participation GIS (PPGIS) is knowing a revolutionary era which perfectly fits the new vision of Digital Earth (DE). This research investigates the opportunity to build up a PPGIS prototype with completely Free and Open Source Software (FOSS) architecture, in which data directly come from field surveys carried out by users. A sample application related to urban monitoring is addressed, which concentrates on user field-collected data concerning reports of road pavement damages. Open Data Kit suite allows users to collect geotagged multimedia information using mobile devices with onboard location sensors (e.g. a Global Positioning System receiver). On field-captured data are sent to a server and stored into a PostgreSQL database with PostGIS spatial extension. GeoServer then disseminates data on the Web. On the client-side, different solutions allow data visualization on both desktop computers and mobile dev...

Maps have always been tools that have fascinated men, for their ability to make us see the world that surrounds us. They were and are the outcome of models and methods applied to the observation of the world, starting from geodesy, surveying photogrammetry and remote sensing. All these disciplines, which we now group under the new name of geomatics, have had a tremendous boost in recent years. However, the synergy with information computer technology is probably the aspect that is revolutionizing more cartography. Earlier computers and after the Internet have brought us to new concepts and tools that will have profound effects not only in the world of niche of cartographers, but also more generally in the life of all human beings. The Digital Earth, proposed in 1998 by Al Gore, has been enriched in just twenty years of a set of new demands, which make even more interesting and challenging being cartographers today. The paper, without claiming to be comprehensive, aims at providing a concise overview of the state of art and of the advancement in this area. Moreover, it urges the community of geomatics to be protagonist and promoter of a new cartography, largely to be reinvented, and that would put us at the center of processes of knowledge and management of the Earth. The map makers in the past helped discovering new worlds, now the challenge is to rediscover our common world with new eyes of environmental, social, economic equity, sustainability and participation.

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014. The purpose of this research-in-progress paper is to present an initial data exploration of twitter georeferenced data related to flood events, in order to determine the potential of these type of data in flood damage assessment. Data exploration aimed at determine: (1) if the features of information associated to a flood event can be generated using Twitter, (2) What are the most frequently used hash tags related to flood events? and (3) If it is possible to detect post flood information from Twitter messages. We developed a script to gather data using the Twitter Search API. The data collected gave an idea of the main feature information, spatial distribution and better search strategies.

Rainfall is one of the most important factors affecting various types of hazards such as: landslides, floods, sea level rise and so on. With the availability of satellite rainfall estimates at fine time and space resolution, it has also become possible to mitigate such problems over the world. But satellite rainfall needs to be monitored before use, because the satellite data does not reflect the strong influences on precipitation of topography in some cases. Relief of study area is very complex including mountain and plain areas. In this paper we present a Decision System and an intelligent geoportal for North Vietnam based on Web Service allowing users to investigate satellite rainfall by means of a direct comparison and of the Revised Universal Soil Loss Equation (RUSLE) model. The comparison method uses data from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) and rain gauges (RG) to investigate the interpolation of RG data. Furthermore, we also estimate a correlation and examined a percentage of simultaneous rain or no-rain between them. We realize that correlation between PERSIANN and gauge data meets expectation value when we investigate monthly data. The RUSLE model for computing the soil loss, which requires a huge amount of information and data, was handled for both PERSIANN product and rain gauges data to estimate the difference due to the usage of the two data sources.

Virtual globes were initially released as effective and intuitive tools to view satellite and aerial photos directly superimposed on the 3D modeling of the globe. The constant update of increasingly accurate and detailed images and the ability to customize the content through the direct mapping on the globe of any geographically localized phenomenon (physical, environmental, social, etc.) have increased not only the common and popular use of virtual globes but has also offered great opportunities for geographical representation and analysis in science. The paper presents solutions we implemented for environmental purposes; in particular, three different viewers for 4D environmental variables (3D location of the variable at different times) using an open-source virtual globe developed by NASA (NASA World Wind). The third solution presented is the most innovative one and uses a “doxel-based” approach for modeling environmental variable distributions. The choice of World Wind is due to its code openness and hence the possibility for both customizing and extending its functionality. The characteristic of being written in Java makes it a platform-independent program (viewer directly executable on different operation systems) and accessible by simple web-browsers (like applet or via Java Web Start technology). In detail, we present solutions that can be directly implemented using existing software tools and an innovative solution specifically developed.

The State Archive of Como in Northern Italy has begun a process of digitization of its map heritage, with the support of interested municipalities. In its archive approximately 15000 historical cadastral maps of Como province are preserved: the Theresian cadastral maps (1718-1722), the “Lombardo-Veneto” ones (1854-1858), the “updates” (1898) and for some locations the maps of 1905. Besides their artistic value, those maps describe with great accuracy the status of the territory and therefore they are a valuable tool for scholars and professionals working on this area.

The computation of mean sea surface heights from a set of collinear Geosat ERM altimeter data tracks was carried out in a collinear adjustment, where 1 cy/rev cosine and sine coefficients for each track are estimated, so the differences between the collinear tracks are minimized. Then bias/tilt cross-over adjustments of stacked Geosat and Seasat altimetry were carried out. The problems with the free surface in the cross-over adjusted altimetric surface were treated using the absolute sea surface heights relative to the geoid model OSU89B. In a combined adjustment of the two altimeter data sets using cross-over and height informations simultaneously a RMS of the cross-overs of 0.080 m and a RMS of the sea surface heights relative to OSU89B of 0.611 m were obtained.

In this paper we present a method for detecting three-dimensional systematic errors of Digital Surface Models (DSMs) derived from satellite data. The detection process is realized via a three-dimensional comparison with reference altimetric models of better accuracy, by a matching process based on a 3D geospatial transformation without scale factor correction. The matching process of the two altimetric models is based on the estimation of the six parameters of a geospatial transformation between two 3D surfaces, minimizing the Euclidean distances between the surfaces by least squares method; this procedure does not require the a priori availability of homologous points. The method is applied on comparison of GPS surveys over Lombardy Region of Northern Italy, with SRTM (3 arc sec) and ASTER (1 arc sec) DSMs in the same region; tests of statistical significance are performed confirming, in the latter case, the existing 3D systematic error.

Primarily driven by current advances in web, web service and sensors technologies, and the expressed needs from geospatial and broader communities, the webbased sensors and geoprocessing service fields have evolved rapidly over the last 10 years. Geoprocessing services greatly facilitate the process of transforming geospatial data to geoinformation, exposing the powerful analytic capability of geographic information system (GIS) and empowering the public in today’s “electronic” decision-making over the worldwide web, particularly within spatial data infrastructure frameworks, through service composition, utilization of advanced grid/cloud computing, and well-designed client-side applications. The research topics and issues range from discovery, accessibility, usability to interoperability, which require standards support, and cooperation among academia, industry, government, commercial, and open source communities. This special issue builds on the extended version of seven papers selected from the papers submitted to the first International Workshop on Pervasive Web Mapping, Geoprocessing and Services, which was successfully held on the Politecnico di Milano campus in Como, Italy fromAugust 26 to 27, 2010. The workshop was organized by ISPRS WG IV/5 on “Distributed, Web-based Geoinformation Services and Applications” and Politecnico di Milano, and coorganized by ISPRS WG WG IV/1 on “Geospatial Data Infrastructure”, WG IV/4 on “Virtual Globes and Context-Aware Visualization”, and ICWG IV/II on “Geo-Sensor Networking and GEOGRID”. The main theme of the workshop focused on Sensor Web Enablement and Geoprocessing Services. Some of the particular topics and issues addressed in the technical sessions included (full papers are available at http://www.isprs.org/ proceedings/XXXVIII/4-W13/)

LIDAR (Light Detection and Ranging) is one of the most recent technologies in surveying and mapping. LIDAR is based on the combination of three different data collection tools: a laser scanner mounted on an aircraft, a Global Positioning System (GPS) used in phase differential kinematic modality to provide the sensor position and an Inertial Navigation System (INS) to provide the orientation. The laser sends towards the ground an infrared signal, which is reflected back to the sensor. The time employed by the signal, given the aircraft position and attitude, allows computation of the earth point elevation. In standard conditions, taking into account the flight (speed 200–250 km/hour, altitude 500–2,000 m) and sensor characteristics (scan angle ± 10–20 degrees, emission rate 2,000–50,000 pulses per second), earth elevations are collected within a density of one point every 0.5–3 m. The technology allows us therefore to obtain very accurate (5–20 cm) and high resolution Digital Surface Models (DSM). For many applications, the Digital Terrain Model (DTM) is needed: we have to automatically detect and discard from the previous DSM all the features (buildings, trees, etc.) present on the terrain. This paper describes a procedure that has been implemented within GRASS to construct DTMs from LIDAR source data.

Light detection and ranging (LIDAR) techniques represent a new and fruitful approach in the determination of digital surface models. One of the goals in processing this data is to set up filtering methods which automatically allows to extract the ground and the features (buildings, vegetation, etc.) superimposed on the terrain itself. In our work the emphasis is focused on the first topic. The implemented method takes advantage of the use of spline functions regularised by means of Tychonov functional in a least-squares approach. Firstly, the DSM pixels have been classified in order to previously detect any edges of the non-terrain feature. Then all the pixels corresponding to the ground, by means of a region growing algorithm, has been identified through a correction procedure. Finally, by a new interpolation on the classified ground pixel only, we can derive the digital terrain model. In the paper the processing methodology is discussed; and a first extensive example is presented.

The Wiener–Kolmogorov principle of minimizing the mean square estimation error is discussed in the framework of prediction theory, from both theoretical and practical points of view. Alternatives for suboptimal solutions, more easily computable and not requiring the explicit knowledge of the covariance function, are proposed. A robust version of the principle is also discussed and illustrated by a small numerical example. A plan for future work is suggested.

Community-based development through collaboration amongst software developers and researchers distributed globally has led to a wealth of feature-rich applications of Free and Open Source Software for Geoinformatics (FOSS4G). In the FOSS4G, development model online source code repository, mailing lists, and a Wiki provide the software developers and users with a virtual and ubiquitous platform for the implementation of new methods, algorithms, and tools as well as for refinement and enhancements of the existing code. For end users, this development model provides highly interoperable, sophisticated software at no cost. This approach is both flexible and immune to vendor lock-ins. Further, the reproducibility of results and quality assessment of methods is greatly facilitated since full access to the underlying algorithms is guaranteed. The source code is typically published under free and open source software licenses with end-user rights to run the program for any purpose, to study how the program works, to adapt it, and to redistribute copies including modifications. The FOSS4G offers software libraries for map projection and data format conversion, desktop Geographic Information Systems (GIS), Web mapping/Web–GIS, spatial databases, geostatistics, and metadata catalogues. Most FOSS4G software packages run natively on common operating systems and may be installed and used without restriction in any commercial or non-commercial environment at no cost for the end users. Open Source Geospatial Foundation (OSGeo, http:// www.osgeo.org) serves as an umbrella organization whose mission is to support the collaborative development of FOSS4G and promote their widespread use. OSGeo provides a common forum and shared infrastructure for improving cross-project collaboration. Acceptance of a project to OSGeo depends on a successful incubation process which includes a detailed source code audit to identify any license incompatibilities in the code. This incubation process also confirms that the project is supported by a healthy community, including validation of the rules and processes governing the project's management. Since its inception in 2006, OSGeo has been providing organizational support for building a vibrant international community to advance geospatial technologies and solutions using open source software, open data and open standards. This special issue is brought forth with the aim of presenting the rich capabilities of FOSS4G to foster original research and enable deployment of innovative solutions. The issue covers a broad range of topics, highlighting the diversity of methods, tools, and applications of FOSS4G. The first two papers introduce new tools and applications for vegetation analysis, first as a M. A. Brovelli (*) Environmental, Hydraulic, Infrastructures and Surveying Engineering Department, Politecnico di Milano-Campus Como, Via Natta 12/14, 22100 Como, Italy e-mail: maria.brovelli@polimi.it

A summary on numerical cartography and digital photogrammetry, taking into account also some aspect of GIS’s and image processing, is presented, in order to list the principal problems of spatially referenced data analysis.

In modelling the global gravity field of the earth an important step forward has been done by using altimetric observations. Yet the observational functional of altimetry as such is not a pure functional of the anomalous field T only but rather it involves other quantities like the stationary sea surface topography, t, and the (time dependent) radial orbital correction ξ which we consider as a parametric curve in time. Well known spectral analyses [2], [9] have shown that only few coefficients of the gravity field can give rise to a significant signal so ξ can ξ be modelled empirically by a relatively small number of parameters, for instance by 8 parameters per arc as in [5].

The possibility of using spaceborne gradiometric observations for the recovery of the gravity field has already been considered by several geodesist in view of the possible realization of the Aristoteles mission; the authors have already called the attention to the possible formulation of this problem in the form of an overdetermined BVP, there studying its formulation and the first analytical and statistical properties of the solution. In this paper the whole theory is summarized and simulated solutions are presented demonstrating the validity of the theory.

In altimetric measurements we observe the height of a satellite on the actual sea surface ( Hobs ). This quantity (see Fig. 1) can be modelled as: $${H_{obs}} = h - N - \zeta + v$$ (1) where h is the satellite’s height referred to the ellipsoid, N is the geoid, ζ the sea surface topography, splitted into stationary component ( ζo ) and time dependent component ( ζ✝ ) and v is the noise.

The topographic surface of the sea can be determined by subtracting the geoid from the geometric height of the stationary sea surface. This latter can be obtained from altimetry measurements; the former can be derived from marine gravity measurements, treated in the form of gravity disturbances.

WebGIS and virtual globes allow DTMs distribution and three dimensional representations to the Web users' community. In these applications, the database storage size represents a critical point. DTMs are obtained by some sampling or interpolation on the raw observations and typically are stored and distributed by data based models, like for example regular grids. A new approach to store and transmit DTMs is presented. The idea is to use multi-resolution bilinear spline functions to interpolate the observations and to model the terrain. More in detail, the algorithm performs the following actions. 1) The spatial distribution of the observations is investigated. Where few data are available, few levels of splines are activated while more levels are activated where the raw observations are denser: each new level corresponds to an halving of the spline support with respect to the previous level. 2) After the selection of the spline functions to be activated, the relevant coefficients are estimated by interpolating the observations. The interpolation is computed by batch least squares. 3) Finally, the estimated coefficients of the splines are stored. The model guarantees a local resolution consistent with the data density and can be defined analytical, because the coefficients of a given function are stored instead of a set of heights. The approach is discussed and compared with the traditional techniques to interpolate, store and transmit DTMs, considering accuracy and storage requirements. It is also compared with another multi-resolution technique. The research has been funded by the INTERREG HELI-DEM (Helvetia Italy Digital Elevation Model) project.

About 54% of world population nowadays lives in urban areas and this percentage is expected to increase up to 66% by 2050. Therefore, it is crucial to manage this social and cultural change by collecting, integrating and sharing reliable and open spatial information concerning the urban environments where we leave in. The present availability of huge archives of synthetic aperture radar (SAR) data collected since 1992 by ESA, in conjunction with the available Earth-Observation (EO) optical data, represents a unique possibility to derive valuable information for the understanding of the ongoing urban processes. In this framework, the three-year project financed by the Italian Ministry of Instruction, Research and University, entitled "URBAN GEOmatics for bulk information generation, data assessment and technology awareness" may play a role for the assessment and the development of new replicable methodologies for the study of soil consumption and mobility in urban zones. The paper aims to present some preliminary results achieved during the project, clarifying how the new emerging technologies for managing big EO data are proficient for the investigation of urban processes.

The choice of the best geopotential model to reduce geodetic data is one of the critical step in computing the geiod. In this paper, both gravity and altimetry were considered on a large area covering the Mediterranean Sea; an analisys was carried out to define the “best” geopotential model in this area. Six models were considered and statistical tests were performed on the residual data (i.e. observed data minus model).