Computational Science and Its Applications -- ICCSA 2015

Renewal projects on neighborhood scale often include several sub-projects aiming at fulfill the different functions of urban areas, while public funds or activated public-private partnership can be insufficient to face the implementation of subprojects simultaneously. Therefore single parts of wider projects are frequently realized at different period of time, according to the availability of public funds or the interest of private partners in the most profitable projects. Although a major organizational effort of funding could be necessary, a more rational approach is required, which will be able to identify the most suitable sequence of realization ensuring the greatest advantage if non-completion of the entire urban renewal project occurs or during the time of its fulfillment which is usually long. This paper proposes a multi-criteria and multistage evaluation model supporting prioritization of sub-projects belonging to a wider renewal plan. The model is applied to a real world decision problem.

Sustainability indicators are gaining more and more attention as a powerful tool for supporting policy making, providing information on different fields, such as environment, economy, society, technology etc. A very important aspect when dealing with sustainability indicators is related to the procedure for the construction of composite indices, that combine the information coming from several indicators and that are easier to be managed and communicated. The paper investigates the use of indicators in sustainability assessment of projects, plans and programmes and proposes an application of the Multi Attribute Value Theory (MAVT) for the definition of synthetic indices of evaluation. With the aim of highlighting potentialities and limits of the proposed approach, the methodology is applied to a real case concerning a set of well-being indicators. The results of the study show that MAVT is suitable for dealing with the aggregation of indicators systems.

This paper tests the use of Genetic Algorithms to interpret the relationship between real estate prices and the geographic locations of the properties. Issues of choosing algorithm parameters are discussed on the basis of applying data collected in the city of Potenza to 190 houses. The aim of the study is to show the potential and the limits of genetic algorithms in this field and how they can be effectively used in the analysis of the housing market.

In previous works we provided some theoretical results on the estimates of a fuzzy linear regression model. In this paper we propose a generalization of such results to a polynomial model with multiplicative factors, which is actually more appropriate than the linear one. In fact, even in a fuzzy approach the growth rate of the dependent variable can vary depending on the values assumed by independent variables as well as on their interaction. In this application case, we regress the overall satisfaction for the working experience, expressed by the second cycle graduates in the 2008 of the University of Bari, on their satisfaction for specific aspects of job. Since the interviewed graduates express their own liking through scores which do not represent an objective measure of the personal opinions, but rather correspond to accumulation values on the submitted scale, the fuzzy approach is adequate to deal with such collected data.

The recovery and enhancement of historic buildings require interventions aimed also at the energetic requalification. Indeed, on one side there is a growing attention to the reuse of these buildings not only for conservative purposes, but even for economic and environmental aims; by forcing to include in the project even the energy efficiency improvement. On the other side, the current legislation on environmental sustainability in construction gives clear guidelines in energetic improvement object regarding the entire real estate assets, including historic buildings.

The paper aims to define a technical-economic model for the selection of technologically advanced interventions useful to improve the buildings energy performance of historical and architectural interest. This can happens by respecting the needs and regulations on the protection of the valued property.

The software implementation for the energy characterization of the historic building and the use of cost-benefit analysis, allow to drawing up an analysis protocol to support investment decisions. The issues research about the low thermal and acoustic insulation of the building envelopment and inefficient plants leads to outline intervention strategies and corresponding technical solutions, listed in detail in the article.

The research appears important on the theoretic side because rationalizes the various phases necessary for the selection of the energetic requalification interventions, for which the cash flows analysis is essential to ensure the financial sustainability of the initiative. It’s also true in operative terms since it provides an easy instrumentation to professionals and operators in this sector to lead towards technologically efficient interventions, profitable in management phase and respectful of the historical and architectural values of the built heritage.

Given the current economic crisis, there is a lack of investments also for public sport facilities, which are vital to the urban quality of the city and the quality of life of its citizens. The situation is serious in Italy, especially after the failure of public policies for funding of major events (World Cup, 1990; Winter Olympics, 2006). Some recent laws (147/2013) have revived the sector with particular attention to the medium size facilities but have neglected the small structures that represent the basic activities. In case of the latter, a convergence of objectives is needed between public administrations and private investors. Therefore, public authorities should think in terms of sustainability and investment performance, a perspective that involves the private sector. The research extends the knowledge framework for the financial outline of investments in the sector of swimming pools, starting with a technical and financial analysis of 18 case studies and building confidence intervals for the relevant variables.

In complex programs of urban redevelopment recourse to negotiation procedures between PA and private developers emphasizes the role of evaluation, both in terms of the collective advantage and from the point of view of financial feasibility. The purpose of the contribution is twofold: the first is to investigate the role that can be exercised by the evaluation in order to confer efficiency, fairness, transparency and democratic participation in the processes of formation and implementation of strategic programs for urban and metropolitan development characterized by high levels of complexity, the second objective is to provide an integrated assessment model which can fulfill this role properly and adequately support the decision-makers and the public in decision-making ex-ante to an integrated assessment of the “public convenience” and at the same time check whether there are sufficient margins of feasibility and financial sustainability for the private developer to carry out the investment program.

In this paper the financial feasibility in the installation of roof-top wind turbines in the territory of the city of Bari (Italy) has been analyzed. The elaborations carried out have allowed to define “wind” maps, in terms of annual mean wind speed and annual energy production, and evaluative maps, in terms of total profit for the investor and land lease values of the flat roofs of existing buildings. The thematic maps generated constitute a primary support for the operators interested in taking advantage of European resources and/or the incentives offered by energy regulations for the installation of roof-top wind turbines and identifying the areas characterized by higher yields. Furthermore, the model obtained provides investors and flat roofs’ owners motivated and contextualized economic values, referred to the local wind power capacities of the areas in which the installation of roof-top wind turbines is financially convenient.

Cluster analysis is highly advantageous as it provides “relatively distinct” (or heterogeneous) clusters, each consisting of units (families) with a high degree of “natural association”. Different approaches to cluster analysis are characterized by the need to define a matrix of dissimilarity or distance between the n pairs of observations. The cluster analysis allows to identify the profiles families who meet certain descriptive characteristics, not defined a priori. Fuzzy clustering is useful to mine complex and multi-dimensional data sets, where the members have partial or fuzzy relations. Among the various developed techniques, fuzzy-C-means (FCM) algorithm is the most popular one, where a piece of data has partial membership with each of the pre-defined cluster centers. Fu and Medico [1] developed a clustering algorithm to capture dataset-specific structures at the beginning of DNA microarray analysis process, which is known as Fuzzy clustering by Local Approximation of Membership (FLAME). It worked by defining the neighborhood of each object and Identifying cluster supporting objects that have great importance in the field of market research in order to identify not only the average profiles (centroid) but the real prototypes and assigned to other units observed a degree of similarity.

The definition and adoption of practices “sustainable” at economic, social and environmental level, is an important tool to respond to multiple pressures from different stakeholders operating at multiple levels (local, national and supranational). The idea of sustainability implies a crucial change in the relationship between the company and the community (understood in a more or less wide) belongs to. In order to assess whether the adoption of a socially responsible conduct has a positive impact on turnover of manufacturing enterprises, this works refers to the multinational IKEA, among those working in the field of furniture.

This paper describes a methodology for analyzing the feasibility of a system of minor airports designed to increase the use of air travel for short trips in Italy. The study starts with an analysis of Italian territory and the positioning of its minor airports; the database of the Geographical Information System (GIS) provided by Italy’s National Institute of Statistics (ISTAT) is sued to describe the country’s main geographical and economic features. A multi-criteria decision analysis (MCDA) is developed for processing the dataset and creating a platform shared by all stakeholders. Thanks to the Spatial Multi-Criteria Analysis (SDSS) arrived at, it is possible to localize the best position for new minor airports and to formulate strategies for improving existing ones.

In the forecasts related to air traffic in the period 2015-2030, as worldwide as in Italy, is expected a substantial increase in air traffic individual. In Italy, the development and increase of “individual” air traffic is closely linked to the construction of a network of second-level airport infrastructures for civil aviation (minor airports), suitably distributed throughout the national territory, efficient, accessible, interconnected with other means of transport and easy-to-use. A network structured in this way can also contribute to the improvement of the conditions of the context of peripheral areas.

The model of multi-criteria analysis proposed is aimed to identify useful elements for supporting the choices needed to redefine Italy’s minor airport system so as to construct a second-level airport infrastructure network (nodes of a so-called “highway in the sky”) integrated with the general airport and infrastructure system and aimed at supporting local sustainable development of the different areas of Italy.

The urban transformation projects are very complex and have to be examined from several points of view (socio-cultural, environmental, infrastructural, administrative, and economic-financial) to determine their sustainability. This study aims to test the financial analysis as a tool for outlining the morphogenesis of the project’s characteristics and exploring the frontiers of the financial feasibility especially when the urban projects, according to Italian laws, involve Public Private Partnerships (PPPs). A financial model is applied to a case study (the transformation of an abandoned railway area) in which the absence of an adequate returns on investment, because of the crisis of the real estate market, requires one to iteratively modify the project’s characteristics and define various alternative scenarios for obtaining the project’s form that achieves the financial feasibility.

In the current economic situation, characterized by a high uncertainty in the appraisal of property values, the need of “slender” models able to operate even on limited data, to automatically capture the causal relations between explanatory variables and selling prices and to predict property values in the short term, is increasingly widespread. In addition to Artificial Neural Networks (ANN), that satisfy these prerogatives, recently, in some fields of Civil Engineering an hybrid data-driven technique has been implemented, called Evolutionary Polynomial Regression (EPR), that combines the effectiveness of Genetic Programming with the advantage of classical numerical regression. In the present paper, ANN methods and the EPR procedure are compared for the construction of estimation models of real estate market values. With reference to a sample of residential apartments recently sold in a district of the city of Bari (Italy), two estimation models of market value are implemented, one based on ANN and another using EPR, in order to test the respective performance. The analysis has highlighted the preferability of the EPR model in terms of statistical accuracy, empirical verification of results obtained and reduction of the complexity of the mathematical expression.

The exact prediction of housing selling prices is a relevant issue for real estate market, also to evaluate alternative forms of financial investment. In this paper a hedonic price function built through a semiparametric additive model is implemented. This model use penalized spline functions and aims to achieve a significant improvement in the prediction of the market price of the properties.

The old town of Ragusa is undertaking a regeneration process in some different directions. Its differently valued areas need to be comprised in a whole valorisation strategy, connecting the decision making process with functional and symbolic values. In such a multi-layered urban sub-system, the architectural unit can play the role of one of the main information/value units which the valuation/decision making pattern starts from. The pattern works as an impact assessment tool, that generates a great number of intervention strategies in order to maximize different and conflicting objectives, and provides for each of them an axiological profile aimed at defining a trade-off scheme between them. Some GIS tools and a WebGIS interface allow the real-time control of the different scenarios envisaged in the decision making process.

Troina is a town in the central mountainous area of Sicily, in the Province of Enna, and well represents the general social and economic profile of this territory. Its real estate market is assumed in this study as one of the most significant ones for the description of this profile, because of its characteristics that, especially during the current economic-financial crisis, are particularly evident. The study of this market has been carried out as a basis for a possible redevelopment capital-centered policy, so that both urban/architectural and real estate characteristics have been considered within the proposed pattern. This pattern is based on the decision trees technique, a data mining procedure that allows defining the different submarkets under some specified hypotheses. The different aggregations we have figured out express different ways of assuming the real estate market profile and the directions of any policy that could boost the preservation of the historical urban context instead of promoting the outward urban spreading with further land consumption.

Only recently seismic prevention has come up in urban planning and considered as a significant part of the social capital of the urban heritage. Among the planning tools for reducing the vulnerability of urban fabrics, the Emergency Limit Condition (ELC) defines the fields which require widespread strengthening interventions in the buildings involved in resilient town units. The extent and intensity of such interventions can be graded so as to find an optimal ELC measure, taking the needs of the urban and human capital into account. In case of the old town centre of Ragusa, a model for analysing the seismic vulnerability of the built-up areas has been integrated with a model for a cost-revenue estimation in order to identify the conditions of the ELC dimensioning and to develop the relevant incentive system.

This paper examines the preliminary cost estimate procedure followed in planning the reconstruction of the city of L’Aquila and of 56 other towns in the Abruzzo region damaged by the 2009 earthquake. As with past catastrophic events, the Italian Government has assumed full responsibility for funding repair/reconstruction of both private and public properties. A highly articulated legislative cost estimation system - developed on behalf of the national authorities in the wake of the earthquake that caused over three hundred victims - was implemented to coordinate the distribution of funding among the different municipalities and private subjects affected by the earthquake. The paper shows how the automatism of this procedure may have produced a distortion in cost estimates when compared to the costs actually needed for reconstruction. An alternate cost estimation model is proposed based on multiple linear regression analysis that uses bills of quantities from reconstruction projects funded immediately following the quake (and is based on actual structural designs rather than emergency damage assessment data). The objective of the proposed model is to achieve a more realistic reconstruction cost estimate framework, while respecting the need for a quick and rational procedure that requires no additional information beyond the post-earthquake expert survey reports available only weeks after the earthquake.

The proposed study deals with the analysis of the real estate market in the quarter of San Cristoforo in Catania, trying to integrate different approaches to define its possible articulation in submarkets. The first one is a phenomenal type of approach that intends to represent some of the most manifest characteristics, and provides an initial hypothesis of classification of the cases (a census has been taken of) and delimitation of the segments, taking into account the ranges of prices registered inside the different classes of the characteristics. The second consists of an in-depth clustering analysis basing on three different hypotheses of three, four and five clusters respectively. The third one is a DRSA application, which is meant to extract from the studied sample a set of rules for the possible definition of a segment representing the general market rules. Given the complexity of the studied context, the results allow different interpretations and considerations of method.

In 2006 European Commission stated that soil, fairly recognisable as an ecosystem structure, can be considered essentially as a non-renewable resource, thus triggering both studies for the assessment of land take phenomenon and actions for its mitigation and reduction. In last two decades, a deeper and ecosystem approach to land-use policies targeted to the sustainable development enabled a closer understanding of the complexity of urban dynamics leading to the necessity of multidimensional and integrated approaches for the assessment of the use of resources. The paper presents a multi-dimensional approach to evaluate the phenomenon of land take and soil sealing implemented on a sample of municipalities in Apulia Region, in Southern Italy. The construction of a composite indicator for comparative qualitative and quantitative measurement of land take and soil sealing among the municipalities is aimed at a better evaluation of future urbanisation scenarios and at a monitoring process of urban growth.

The growing need to support financially the processes of urban regeneration of city centers clashes with the limited availability of public resources. Administrations are therefore forced to evaluate the priority areas of intervention, on the one hand trying to pursue goals of social equity, other actions to promote efficient financial plan. Consequently the reference institutional policy of intervention is based on regulatory frameworks that require a closer integration of programming needs of the allocation of resources, and social needs. The chapter shows an example of conciliation among the seek for efficiency and for social equality in choosing priority of intervention in the urban make up of historic centers.

In urban contexts characterized by the presence of settlements where services are lacking, densification with the transfer of development rights brings benefits, through intensification of urban areas, reduction of the vehicular mobility and containment of soil consumption.

Indeed, under certain conditions, the transfer of development rights allows to identify the volumes to be deployed by evaluating the receptive capacity of the soil.

Geographic Data Infrastructure could be a valid tool to make an Evaluation Support System to compare alternatives with different compensation criteria. These different options arising from the request for satisfaction of collective needs, due to the growing demand for supply of services to upgrade the technology and energy building.

The use of multivariate micro-data, data aggregated for small-areas, allows detailed analysis of the physical and social structures of regional landscapes. Such exercises are in many cases univariate and static in nature; this happens when geometries are not coincident between datasets. Common solutions to such inconsistencies involve the use of areal interpolation techniques to build coherent information sets; when ancillary information is available, dasymetric mapping using control units may then be used. Techniques vary on the type and quality of the ancillary (or control) information. The purpose of the present article is to present a generalized tool to tackle common practical analytical problems and which produces geometrically coherent datasets. It is generalised because: (1) it is flexible, allowing distinct parametrization depending on the data; (2) it is based on Open Source tools anchored on robust database management systems (DBMS) technologies. Its aim is to provide the regular GIS user with a tool to tackle a common problem of geometric mismatch.

Researh efforts in the Social Sciences have a great potential impact on society in general as it promotes greater knowledge of any and every aspect of human interactions. With this in mind, a combined project - Comuns, was developed, bringing together recent technological trends in data exploration and visualization, and the production of new high-precision historical geo-demographic datasets. Using dasymetric algorithms implemented within an Free and Open Source Software (FOSS) platform, source geographical data- aggregated according to distinct geometrical schema, was re-allocated according to common areas. The innovative nature of Comuns is three-folded: (1) for the first time, a large scale comprehensive time-space database is built for Portuguese census data; (2) the fact that data is made available online contributes to the goal of making knowledge symmetrically available; (3) the fact the only FOSS is used means that, other than man-hours, the project is costs’ free, accountability increases as does reproducibility. The open character of the project have potential implications in terms of the way human landscapes are perceived, given that new coherent datasets allow new explorations of the territory. Its target are primarily civil society in general; its applications range from academic to recreational, with potential uses in geomarketing projects.

Presently, the use of new technologies for the acquisition of 3D geographical data on time is very important for urban planning. Applications include evaluation and monitoring of urban parameters (ie. volumetric data),indicators of an urban plan, or monitoring built-up areas and illegal buildings. This type of 3D data can be acquired through an Airborne Laser Scanning system, also known as LiDAR (Light Detection And Ranging) or by Unmanned Aerial Vehicles (UAV). The aim of this article is to use and compare these two technologies for extracting building parameters (facade height and volume). Existing literature evaluates each technology separately. This work pioneers benchmarking between LiDAR and UAV point-clouds. The basic function of LiDAR is collecting a georeferenced and dense 3D point-cloud from a laser scanner during flight. Therefore it is possible to obtain a similar 3D point-cloud using processing algorithms for stereo aerial images, obtained by large or small-format digital cameras (the small-format camera implemented in Unmanned Aerial Vehicles). The chosen study area is located in Praia de Faro, an open sandy beach in Algarve (Southern Portugal), limited west by the Ria Formosa barrier island system. The area defined has an extension of 300100m. The methodology is divided in two distinct stages: (1) building parameters extraction, (2) comparative technology analysis. Lidar point-cloud resolution is approximately 6 pts/m2 and UAV point-cloud 60 pts/m2. FOSS technologies have proven to be the most adequate adequate platform for the development and diffusion of advanced analytical tools in the Geographical Information Sciences (GISci). Data management in this paper is supported by a Geographical Database Management System (GDBMS), implemented using PostgreSQL and PostGIS. Statistical analysis is performed using R whilst advanced spatial functions are used in GRASS.

We propose a new modelling method for the simulation of pedestrian dynamics when the walking direction of the pedestrians cannot be represented by straight lines. The geometry of the simulation is approximated on a special triangular grid. We also study the pedestrians’ step execution for the general case of multi-position velocities and the possible interaction among them. We discuss the model on a ring-formed environment with periodic boundary.

We present in this paper the analysis of mobility in the provinces of Salento, in the modal split and their reasons for moving. We used data on commuting (OD matrix municipal disaggregated) recognized by ‘ISTAT in the 2011 census and published in December 2014. The results of the analysis are represented by thematic maps showing estimated levels of air and noise pollution on each municipal areas. The analysis software is designed for automatic search as a decision support system for the intervention policies for the smooth flow of traffic and noise and air pollution.

Seismic risk maps are a useful tool researchers use for representing to stakeholder and decision makers the adverse outcomes a seismic event can have over the territory. Generally, in those studies, urban areas, where the human activities are concentrated, focuses major attention. Main concerns are about the existing building stock, mostly composed by structures not compliant with modern seismic design criteria. The production of a seismic risk map is a complex task that involves the combination of data coming from different field of expertise. The aim of the study is to show how the already available information can be combined together in a Geographical Information System (GIS) tool. The results provide a reliable representation of the seismic risk at urban scale to be used when planning the mitigation measures to be undertaken in order to improve the level of preparedness in case of an earthquake. The analysis has been applied for demonstration purposes to the town of Cassino, Central Italy.

This article gives insight in a running dissertation as well as a finished project of the Masterprogram Geoinformation and Visualization at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data, that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic ‘Geovisual Analytics and geographical profiling’. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

Coastal zone of Emilia-Romagna region, Italy, has been significantly urbanized during the last decades, as a result of a tourism development. This was the main motivation to estimate future trajectories of urban growth in the area. Cellular automata (CA)-based SLEUTH model was applied for this purpose, by using quality geographical dataset combined with relevant information on environmental management policy. Three different scenarios of urban growth were employed: sprawled growth scenario, compact growth scenario and a scenario with business-as-usual pattern of development. The results showed the maximum increase in urbanization in the area would occur if urban areas continue to grow according to compact growth scenario, while minimum was observed in case of more sprawled-like type of growth. This research goes beyond the domain of the study site, providing future users of SLEUTH detailed discussion on considerations that need to be taken into account in its application.

The building stock of Cremona is considered here as good opportunity to provide potential socioeconomic and physical/architectural analyses to assess the suitability for intervention in existing structures. The treatment of alpha-numeric, vector databases is integrated with the physical dimension of buildings that, in this article, refers to living characteristics useful to assess the suitability for change of each statistical unit analysed. However, single variables can only outline the geographies of specific phenomena. The use of multi-dimensional appraisals allows understanding how these phenomena interact, showing complex latent potentialities. This enables the identification of units requiring strategic interventions for urban regeneration, using innovative analyses based on thematic paths geographies within the built space. These techniques are useful to enhance the preservation and overall quality of city cultural heritage and the urban building stock. Finally, a ‘suitability for intervention’ map which considers the relationships between economic activities, cultural/monumental heritage, vegetation structures is presented.

This paper presents a hydrological and water quality model for Cherry Creek watershed, located in southeastern Kansas, USA. The Cherry Creek catchment drains approximately 88220 ha and it is a main contributor of water to the Neosho River. Hydrological modeling of the Cherry Creek watershed is performed using the Hydrological Simulation Program Fortran (HSPF). Simulated results for total ammonia (TAM) concentrations occurring at the Cherry Creek watershed outlet for four land use scenarios and a 2-year simulation period, are presented. Sensitivity analysis of total ammonia estimations (TAM=NH

3

+NH

4

) to the unbounded HSPF parameter POTFW is subsequently presented. POTFW represents the ratio of a water quality constituent yield to sediment wash-off outflow. Results showed that small perturbations to a 50 mg/Kg POTFW base value produce the largest normalized sensitivities. Peak sensitivities reached up to 248%, with the -1% perturbation producing the most dramatic sensitivity response in TAM estimations. Results showed a strong relationship between normalized sensitivities to river flow regime. Non-linearities in sensitivity for small ±1% perturbations were detected. These non-linearities are more evident for high stream flow values (strong flood events). For larger perturbations (±60%, ±40%, ±20%, and ±5%) the sensitivity response was shown to be linear.

This paper presents results of assimilation of TRMM precipitation into a hydrological model of Los Almendros River watershed, assessed by the comparison of simulated stream flow values to observed stream flow data. Los Almendros River is a tributary to the Clarillo River, located in Reserva Nacional Rio Clarillo (National Reserve Clarillo River), Chile, South America. Los Almendros basin, covering approximately 4.9 km

2

, is a typical Andean watershed with an average slope of 46.3. It drains an average of 18.5 L/s from a catchment area covered predominantly by grasslands (91%), while forests and savanna land cover types are less predominant (3% and 6% respectively). The hydrological model of Los Almendros watershed was developed using the Hydrological Simulation Program Fortran (HSPF). Results showed that raw TRMM precipitation time-series overestimated disaggregated precipitation values for the whole period of analysis. TRMM data required time-averaging for the monthly and annual values to be in the same range as those of disaggregated data. Time-averaging produced daily precipitation time-series consistent to disaggregated data (R

2

=0.85). The use of TRMM-enriched precipitation time-series for hydrological modeling of stream flow at Los Almendros watershed outlet, slightly improved a previous simulation in which only disaggregated precipitation dataset was used. When comparing simulated and observed data, the statistical fit coefficient improved from R

2

=0.64 (corresponding to only disaggregated precipitation data introduced into the hydrological model) to R

2

=0.68 (corresponding to TRMM-enriched precipitation data).

The smart cities initiative does not consist of filling our cities with tech gadgets, cameras and sensors for the purpose of monitoring and controlling both citizens and urban environment. The smart cities movement is not a marketplace for companies and businesses to sell their ICT products and services to governments. The smart cities objective is not to target the use of urban technology as an end in itself but as a tool towards more citizen-centric cities. Therefore, smart cities are not a big brother watching citizens but an inclusive and participatory arena for local governments and all interested stakeholders (including citizens) to co-create communities that can offer development opportunities to everyone and quality of live, no matter social group, age, or gender. This is the true objective of smart cities, which sometimes gets lost, forgotten or becomes shadowed by an excess of technology. But, how to achieve such a challenging objective? Fortunately, just recently, a definition on smart cities has been agreed by international standardization bodies which, so far, are the ones paving the way regarding concepts, terminology and general understanding of the smart cities movement. This novel definition builds on the sustainability concept, promotes urban development in good harmony with resilience, and uses technology only as a way for cities to measure their smartness and improve their performance. The author, aware of the big step forward that this internationally acknowledged definition is, takes the opportunity that this new piece of formally structured knowledge offers to elaborate a first-of-a-kind framework to conceptualize, model and simulate sustainability, and its practical implementation while promoting urban development and resilience to achieve higher performance levels of urban smartness.

GIS technologies are able to provide useful tools for estimating the energy resource from the sea waves, assessing whether this energy is exploitable and evaluating possible environmental impacts. The idea to convert the energy associated with the marine wave motion (both off-shore and coastal) into exploitable electrical energy is not new and over time several projects have been developed, aiming at the implementation of devices for electrical energy generation from the sea. However, compared to other well-established renewable sources (such as wind, solar or biomass), the exploitation of the tidal power, is currently only in prototype form. Nevertheless, it has shown very promising potentiality, as also emerges from the activities currently carried-out by public institutions and private stakeholders.

This paper describes an approach, based on Geomatics, developed to assess the marine energy resource, evaluating if it is possible to exploit such resource and estimating also environmental and socio-economic impacts in blue water and/or in the seaboard. In this framework, a DSS-WebGIS application has been developed (called “Waves Energy”), as tool for displaying and sharing geospatial data and maps related to the potential use of energy from the sea, as well as a valuable support for new installations planning, forecasting systems and existing infrastructure management.

This research aims to provide a robust evidence base contributing to improving the quality of policy formation from local to national level in Ireland. The distributions of businesses within key economic sectors in Ireland are explored aiming to find clustering effects occurring across the country. The density mapping and hot spot analysis approaches were applied to find statistically significant clusters of companies for specific business sectors. The research was implemented in collaboration with Dublin Regional Authority to inform key policy makers in Ireland. It assists in assessments of the nationwide spatial distribution of economic activities adding to the overall body of evidence on business intensive regions.

The construction of the territorial information systems, provided by the recent law for territorial governance of Lombardy (the most industrious Northern Italian region), has become an essential procedure to evaluate of environmental sustainability of urban planning. This procedure is necessary for the handing of descriptive and relevant data that is needed to represent the environmental complexity of a region. In addition, territorial information systems allow for the composition of useful indicators to identify the intrinsic peculiarity of a territory (as in our area application, Parco della Valle del Lambro, 35 municipalities on a North-South axis of 25 km, extending across 4,081 hectares). The proposed case for the Lambro Valley and the related Strategic Environmental Assessment represents a positive example of how territorial governance and land use is often conflict.

This paper describes a new idea and methodology developed for overcoming problems linked to the climate changes science and how to make them effectively accessible by end users. In today’s scientific approach, communication, on climatic information and on climatic changes condition, has to be clear, accessible and perceptive to everyone, to definitely address the right interest on such problem. Results coming from climatic changes Research and Development projects, in addition to being accepted by policymakers, that have to take future decisions and practical actions to mitigate their possible negative effects, must also be recognized and believed by ordinary citizens that have to understand and accept restrictions, for example in energy consumptions, potentially affecting their habit of life. Accordingly, it will be necessary to regenerate policy-making so as to make it more direct and potentially open to networking interactive communication tools.

The present work substantially deals with the problem of the outcomes communication both in the field of climatic studies both of climatic trend conditions, also at a long-term scale.

Furthermore, it has been observed that one of the most widely discussed issues, in addition to that of the uncertainty of the climatic condition predictions, is the data/results communication to policy makers, stakeholders, environmental agencies, citizens, etc.

In recent years, people’s need to participate to decision making, especially when it concerns inalienable human rights such as health and living in a healthy environment, has become increasingly manifest. In order to meet the request for environmental information sharing on the web and to make citizens feel “partakers” in the development of environmental policies, the Physical Agents Simple Operative Unit of ARPA Puglia, developed an open source WebGIS as a communication, participation and working tool for both Citizens and Technicians.

This paper proposes an efficient approach to customize and integrate an open source WebGIS system based on MapServer and Pmapper. The layout of the WebGIS was customized by filling pages in Cascading Style Sheets (CSS) to make it intuitive and easy to use. The features offered are those commonly provided by a WebGIS system, in particular: geographical navigation (pan, zoom, zoom to selection), query time and multiple layers, transparency level options, printing and exporting of current image views or pdf files. Environmental data results from a query can be downloaded in pdf, kml and shp formats. The possibility to download files is a key component of the system as it allows the average expert user to find data in an easily and processable format.

This paper presents a novel software approach termed “Geodata Discovery Assistant” (GDA) to visualise and visually analyse heterogenous statistical mass data with a spatial component. Only recently the potential of digital geospatial information has been recognised in large to small scale enterprises. This is partly caused by the fact that software systems used in the industry to model and process economic or business information lack functions to handle the geospatial attributes properly. The GDA is currently developed in an ongoing R&D project between commercial and academic partners. When fully implemented, the GDA will contribute to the full utilisation of statistical mass data with a spatial component thus facilitating meaningful and informed decision making for users of classical data discovery or business intelligence and analysis systems. In this contribution, we focus on its core component, the rule-based map construction process.

Spatial data mining, space-temporal modelling and visual exploratory data analysis are tools that are useful not only for the analysis of multi-characteristics spatial data, but can also be used for the development of Spatial Decision Support Systems. Such system enables the optimisation of decision-making based on a thorough Spatial Multicriteria Decision Analysis. The authors of the present study have developed a set of multicriteria analyses with use of spatial data mining (SDM) techniques for the analysis of the spatial distribution of the allocation and spending of EU funds in Poland. The ten-year period of Poland’s membership in the EU enables not only the analysis of spatial differentiation of EU subsidies in different regions of the country, but also the dynamics of changes in this differentiation in time.

The proposed analytical system based on information technologies combines the possibilities offered by GIS packages and advanced statistical software, thus enabling to conduct highly complex analyses. One of the methods to carry out such analysis is the application of so-called data mining and data enrichment to detect patterns, rules and structures “hidden” in the database.

Co.Tr.I.S is a multifunction information system that will be used for the effective design of coastal transportation lines. Co.Tr.I.S incorporates six subsystems (S1-S6) which include models, tools and techniques that may support the design of improved coastal networks. A major contribution expected by Co.Tr.I.S is to support the decision making process of the policy makers and the involved players (Ministry, Maritime companies, Local Authorities), towards an improved Coastal Transport System. In order to support this functionality, Co.Tr.I.S is equipped with subsystems for data retrieval (S1, S2), statistical analysis (S3), data visualization (S4), as well as subsystems with specialized modules for network generation, scenario validation (S5), solution optimization and decision support (S6). All these subsystems can have access to the vast amount of the up-to-date data classified and modeled by Co.Tr.I.S, and therefore, the system user (coastal line designer or decision maker) will benefit from the improved representation and the improved solution proposals offered by Co.Tr.I.S. The aim of this paper is to present the Co.Tr.I.S subsystems with emphasis to subsystems S5 & S6.

The economic problems involved in new high-rise buildings are mainly approached from the developer’s perspective, especially in private-public partnerships, popular in Italian urban planning. Interest in energy savings and sustainability for buildings has recently increased considerably. Italian regulations have generally approached these problems from the viewpoint of materials and structures; zoning regulations do not cover energy from the viewpoint of investment projects and their externalities, either in urban development or from the economic viewpoint.

This paper examines the economic problems of energy consumption, with specific reference to tall buildings and high-density areas. Due to their typology of construction, dimensions and complexity, tall buildings may be viewed as urban developments in their own right. In more detail, this paper describes how the energy demand and consumption of single buildings can affect the energy trade-off of entire cities.

The problem of excessive soil sealing and the consequent macro-microclimate degradation process need specific measures.

The use of standards and indexes finalized to the regulation of the soil permeability permits flexible and resilient solutions that allow environment to find a new balance.

The application of the Biotope Area Factor (BAF), as index focused on the integration of urban planning and ecology, is a tool with a dual function: it allows to address a structural choice giving more space to planning and to get better consolidated areas.

The main scope of the paper is presenting a way to calculate BAF which is automatic and based on existing digital cartography and GIS technology.

First authors present a description of the general problem; then they focus on the BAF index as urban parameter computable from direct analysis and web images. The classical way to manually measure BAF is presented with application to the city of Pavia.

Then authors introduce the automatic GIS-based procedure starting from a description of the specification of the Lombardy Region cartography and illustrate all the steps and issues of the developed procedure.

Finally authors rigorously assess the developed procedure by means of manually surveyed test areas and discuss results and further steps of the research.

In this paper possible analyses and simulations are presented based on a city modeling process in order to manage realistic approach for city planning within the Smart City concept. The 3D city model was constructed for City of Plock in Poland on Level of Detail 1, 2 and 3. The model consisted of almost 18,000 buildings. The proposed analyses within both environmental and urban fields were directly addressed to issues that the City of Plock is currently struggling with, such as air pollution, solar panels, flood risk, landscape analysis and city management. The paper concludes with the presentation of technological trends as well as data and policies that needs improvement to provide accurate 3D city model analyses.

Infestations caused by the mountain pine beetle (MPB) can be seen as complex spatio-temporal process with severe ecological impacts on the forest environment. In order to manage and prevent the insect infestation and reduce significant forest loss it is necessary to improve knowledge about the infestation process. The main objective of this research study is to design and implement a model based on decision trees (DT) mashie learning (ML) technique to forecast the spatial propagation of MPB infestation. The study is implemented in the Bulkley-Nechako region of British Columbia, Canada using data sets for the three time points 2004, 2008 and 2012. The results indicate that the derived DT can accurately characterize the relationships between the considered factors and MPB propagation. The developed DT method can be used to estimate future spread patterns of MPB infestations.

The “National Strategy for Internal Areas”, made by the Italian Government for the European Union Partnership Agreement 2014-2020, defines the territory of the Italian internal areas as a set of project-areas, local inter-municipal systems each with its own territorial identity defined by social, economic, geographic, demographic and environmental characteristics. In this sense, we can define “internal” those areas significantly distant from the centers of supply of essential services (education, health, and mobility), rich in environmental and cultural resources with highly diversified natural aspects. The objective of the work is to re-elaborate the existing mapping for the identification of the internal areas, made by the Italian Government, especially taking into account the demographic, economic, morphological profiles and essential services supply, through the use of fuzzy logic. Then, trying to deep explain possible planning strategies and policies for these relevant, sometimes abandoned and extremely diffuse territories.

Transport modelling and in particular transport assignment is a well-known bottleneck in computation cost and time for urban system models. The use of Transport Analysis Zones (TAZ) implies a trade-off between computation time and accuracy: practical computational constraints can lead to concessions to zone size with severe repercussions for the quality of the transport representation in urban models. This paper investigates how a recently developed geographical topology called adaptive zoning can be used to obtain more favorable trade-offs between computational cost and accuracy than traditional TAZ. Adaptive zoning was developed specifically for representing spatial interactions; it makes use of a nested zone hierarchy to adapt the model resolution as a function of both the origin and destination location. In this paper the adaptive zoning method is tied to an approach to trip assignment that uses high spatial accuracy (small zones) at one end of the route and low spatial accuracy (large zones) at the other end of the route. Opportunistic use of either the first or second half of such routes with asymmetric accuracy profiles leads to a method of transport assignment that is more accurate than traditional TAZ based assignment at reduced computational cost. The method is tested and demonstrated on the well-known Chicago Regional test problem. Compared with an assignment using traditional zoning, an adaptive-zoning-based assignment that uses the same computation time reduces the bias in travel time by a factor 16 and link level traffic volume RMSE by a factor 6.4.

Different motivation are related with the analysis of Spatial Big Data (SBD). Google Earth, Google Maps, Navigation, location-based service allow to obtain a great amount of geo-referenced data. Often spatial datasets exceed the capacity of current computing systems to manage, process, or analyze the data with reasonable effort. Considering SBD history methodology as Data-intensive Computing and Data Mining techniques have been useful. In this context the problem regards the analysis of of high frequency spatial data. In this paper we present an approach to clustering of high dimensional data which allows a flexible approach to the statistical modeling of phenomena characterized by unobserved heterogeneity. We consider the MDBSCAN and compare it with the classical k-means approach. The applications concern a synthetic data set and a data set of satellite images.

We describe two technologies of web-based application of GIS in the monitoring and analysis of environmental processes. One technology is a web-based GIS platform, which offers information resources and tools for two levels of environmental process analysis. Level 1 is fast shallow express analysis and level 2 is sophisticated research implemented by specialists. This platform, available at

http://dcs.isa.ru/geo/2/

and

http://saltlab.emsd.ru/server2/

, is used for summarization of seismic activity fields. The other technology is a web GIS incorporated into a large-scale information system for environmental monitoring. It is used for the presentation and analysis of spatial and spatio-temporal data on the World Ocean. A demo version is available at

http://www.geo.iitp.ru/esimo/

.

We present a search engine called

TexSpaSearch

that can search text documents with associated locations in space. We defined three search queries denoted as Q1(

t

), Q2(

t

,

r

) and Q3(

p

,

r

) for finding documents containing text

t

intersecting a disc centered at position

p

with radius

r

. Testing was performed using the UNB Connell Memorial Herbarium database whose records normally contain the location where plant specimens were collected along with associated textual data. The sample herbarium database of size

$$N= 40,791$$

N

=

40

,

791

records with associated locations was indexed using a novel R*-tree and suffix tree data structure to achieve efficient search for the defined queries. Significant preprocessing was performed to transform the database into the index data structure used by

TexSpaSearch

. Testing was performed with 20 example Q1 text only queries to compare

TexSpaSearch

to a Google Search Appliance, as well as a significant number of example Q2 and Q3 queries.

TexSpaSearch

search results are ranked by a modified Lucene scoring algorithm, and combined with a spatial rank for Q2 search. A theoretical analysis shows that

TexSpaSearch

requires

$$O(A^{2}\overline{|b|})$$

O

(

A

2

|

b

|

¯

)

average time for Q1 search, where

A

is the number of single words in the query string

t

, and

$$\overline{|b|}$$

|

b

|

¯

is the average length of a subphrase in

t

. Q2 and Q3 queries require

$$O(A^{2}\overline{|b|} + Z\log _{\mathcal {M}}\mathcal {D}_N + y)$$

O

(

A

2

|

b

|

¯

+

Z

log

M

D

N

+

y

)

and

$$O(\log _{\mathcal {M}}\mathcal {D}_N + y)$$

O

(

log

M

D

N

+

y

)

time, respectively, where

Z

is the number of point records in the list

$$\mathcal {P}$$

P

of text search results,

$$\mathcal {D}_N$$

D

N

is the number of data objects indexed in the R*-tree for

N

records,

$$\mathcal {M}$$

M

is the maximum number of entries of an interior node in the R*-tree, and

y

is the number of R*-tree leaf nodes found in range in a Q3 query.

Urban development is a complex process influenced by a number of driving forces, including spatial planning, topography and urban economics. Identifying these drivers is crucial for the regulation of urban development and the calibration of predictive models. Existing land-use models generally consider urban development as a binary process, through the identification of built versus non-built areas. This study considers urban development as a continuum, characterized by different level of densities, which can be related to different driving forces.

A multinomial logistic regression model was employed to investigate the effects of drivers on different urban densities during the past decade in Wallonia, Belgium. Sixteen drivers were selected from sets of driving forces including accessibility, geo-physical features, policies and socio-economic factors.

It appears that urban development in Wallonia is remarkably influenced by land-use policies and accessibility. Most importantly, our results highlight that the impact of different drivers varies along with urban density.

Landscapes can be viewed as a continuum and studied using spatial gradients along which environmental modifications determine the structural and functional components of ecosystems. The analysis and quantification of Ecosystem Services, intended as the benefits people obtain from ecosystems, play a crucial role in sustainable landscape planning. In this framework we developed a novel method for the identification and characterization of the landscapes nested along the urban-rural-natural gradient and the analysis of potential ES supply and demand within said landscapes. The Kernel Density Estimation technique was applied to calculate continuous intensity indicators associated with urbanization, agriculture, and natural elements, considered as key components of the gradient. The potential ES demand and supply within each landscape area were assessed using expert–knowledge based indices associated to the LULC CORINE classes. Results showed a complex organization of “pillar” and transitional landscapes along the gradient, which match different bundles of ES demand and supply.

In a few recent papers we presented a methodology and the related planning and design support tool, Walkability Explorer, for the evaluation of walkability of places which are relevant for people’s capabilities. The method is an attempt to move beyond the known approaches to evaluating walkability based on the analysis of proximity to urban places and on macro urban and socioeconomic factors, because it conceptualises walkability as the effective capability to walk offered by the environment thanks to micro-urban characteristics. It evaluates how the urban environment is conducive to walk by combining three elements: the destinations/opportunities reachable by foot, their walking distance and the quality of the path to these destinations. Following this approach, here we present and discuss an example assessment of walkability for the city of Alghero (Italy).

Retrofitting and management strategies of existing RC buildings are actually a crucial topic. In this work, a novel approach in order to define a retrofitting and management strategies is reported. The main goal is define a framework based on multidisciplinary approach. An accurate seismic performance evaluation model is considered. This probabilistic model is combined with a probabilistic depreciation model in order to define a completely probabilistic model to economic life prediction. The proposed methodology can be used in different way and applications. It can be the basis of both methods of mitigation of seismic risk strategies and as reference tool for seismic insurance model for wide building stock.

The paper aims at the development of a Collaborative Multi-Criteria Spatial Decision Support System (C-MC SDSS) for the evaluation of multifunctional landscape according to a human smart perspective. The C-MC SDSS addresses landscape transformation and preservation processes, leading to consistent choices with the principles of local self-sustainable development, considering the decision-making environment as a heterogeneous field, where conflicting interests interplay. The methodological approach, implemented in the case study of the National Park of Cilento, Vallo di Diano and Alburni (Southern Italy) demonstrates that the inclusion of web-based data and common knowledge in MC-SDSSs is a major challenge. The multidimensional nature of the landscape evaluation requires a mutual understanding, communication and collaboration, allowing an expansion of the knowledge-base to sharpen questions and improving the quality of the decision process. The paper investigates potentials of a C-MC SDSS for supporting transparent and democratic decision processes, helpful in selecting landscape enhancement policies.

Landuse/cover evolution dynamic is a subject widely and thoroughly investigated, especially concerning consumption of natural and other lands, due to anthropogenic activities. This paper focuses on a region in southern Italy, where soil consumption is known to represent a urging matter of concern. However, although negative impacts of soil consumption are well known, to our knowledge there are no case studies presenting a precise quantitative measurement of the intensity of such phenomenon for the region of interest. This study aims at forecasting the development of urban settlements through the application of the cellular automata model SLEUTH; the first region to be investigated has been the Municipality of Altamura (Apulia region, Italy). This area has been used as a pilot case study to explore many difficulties and advantages in applying such a methodology to the whole southern Italian region. The final goal was to frame and populate an atlas of soil consumption in southern Italy, which intends to offer useful support to sustainable planning and policies.

The low density regions represent the wider portion of European lagging areas. Even if several models for territorial analysis and interpretation were proposed, several issues comes when planning process start the assessment phase. The paper proposes a procedure for the spatial assessment of socio-economic phenomena based on a multiple density measures combined in a discrete model.