Spatial Data Harmonisation in Regional Context in Accordance with INSPIRE Implementing Rules

Spatial data seamless exchange and interoperable usage has become a necessity in efficient data management and competitive positioning in the European Union. Conceptual and technical framework for the spatial data and services interoperability is specified within the EU INSPIRE Directive. The Directive provides flexible and modular structure, giving the opportunity for customisation of the data specifications and usage. From the data publisher level to the European spatial data infrastructure, this opened the question of disharmony of the spatial data structure and sharing. Arisen challenges in data harmonisation process are thus subject of interest for different formalisation approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study (1) analyses the INSPIRE data harmonisation process, (2) assesses critical factors of the process in the region and (3) tests the implementation of the INSPIRE data model harmonised in accordance with user needs. Results of the analysis present the structure and formalisation concepts of the INSPIRE data model, its extensibility, means for securing interoperability and standardised approach in defining data model elements. Critical factors of the harmonisation process are assessed through semi-structured questionnaire answered by competent representatives of the Western Balkans countries. The results show that, on a regional level, spatial data managers have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Aside from the low capacities, due to the current state of the data structures, harmonisation is a highly complex process and a goal that is difficult to reach. The outcomes of the INSPIRE defined harmonisation process and user needs are implemented on a practical example, a INSPIRE Theme Geology dataset from a Western Balkans region stakeholder. The user needs and data model structure characteristics of the regional geology dataset were integrated in the formal description of the source and transformed to target INSPIRE data model. The concept required structuring the source model to meet both INSPIRE and local requirements. The study general aim was reached by implementing the INSPIRE data harmonisation with fulfilling the main objectives – creating market-oriented, interoperable and accessible dataset, meeting national legal requirements towards the geological data management and increasing efficiency of data usage. Further application of the developed approach is seen as the implementation methodology for other INSPIRE themes and other geographical regions.Spatial data seamless usage and exchange has become a necessity in management of natural resources, environmental risk assessment, infrastructural planning and various other industrial domains. Framework for spatial data seamless usage is specified within the EU INSPIRE Directive on the continent-wide level. The Directive enables customisation of the data specifications and usage. However, high-level specification raised the issue of disharmony of the spatial data structure and sharing on regional level. Challenges in data harmonisation process therefore became subject of interest for different research approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study assesses the regional needs and, in that light, develops the example of geological spatial data harmonisation. The needs and the critical factors of the harmonisation process are assessed through a questionnaire answered by competent representatives of the Western Balkans countries. It was found that spatial data managers in the region have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Moreover, the current state of the datasets structure makes harmonisation a complex process and a goal that is difficult to reach. Geology dataset from a Western Balkans region stakeholder was used as a practical example for testing the harmonisation process in accordance with user needs and INSPIRE requirements. The result was harmonised INSPIRE conformant spatial dataset, with validated seamless sharing and usage possibilities of the spatial dataset on both local and EU-wide level. The study showed the possibility of applying the INSPIRE data harmonisation, with fulfilling the main objectives of (1) creating market-oriented, interoperable and accessible dataset, (2) meeting national legal requirements towards the geological data management and (3) increasing efficiency of data usage. Further application of the presented approach is seen as the implementation methodology for other spatial themes and different geographical regions

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

Semantic array programming in data-poor environments: assessing the interactions of shallow landslides and soil erosion

This research was conducted with the main objective to better integrate and quantify the role of water-induced shallow landslides within soil erosion processes, with a particular focus on data-poor conditions. To fulfil the objectives, catchment-scale studies on soil erosion by water and shallow landslides were conducted. A semi-quantitative method that combines heuristic, deterministic and probabilistic approaches is here proposed for a robust catchment-scale assessment of landslide susceptibility when available data are scarce. A set of different susceptibility-zonation maps was aggregated exploiting a modelling ensemble. Each susceptibility zonation has been obtained by applying heterogeneous statistical techniques such as logistic regression (LR), relative distance similarity (RDS), artificial neural network (ANN), and two different landslide-susceptibility techniques based on the infinite slope stability model. The good performance of the ensemble model, when compared with the single techniques, make this method suitable to be applied in data-poor areas where the lack of proper calibration and validation data can affect the application of physically based or conceptual models. A new modelling architecture to support the integrated assessment of soil erosion, by incorporating rainfall induced shallow landslides processes in data-poor conditions, was developed and tested in the study area. This proposed methodology is based on the geospatial semantic array programming paradigm. The integrated data-transformation model relies on a modular architecture, where the information flow among modules is constrained by semantic checks. By analysing modelling results within the study catchment, each year, on average, mass movements are responsible for a mean increase in the total soil erosion rate between 22 and 26% over the pre-failure estimate. The post-failure soil erosion rate in areas where landslides occurred is, on average, around 3.5 times the pre-failure value. These results confirm the importance to integrate landslide contribution into soil erosion modelling. Because the estimation of the changes in soil erosion from landslide activity is largely dependent on the quality of available datasets, this methodology broadens the possibility of a quantitative assessment of these effects in data-poor regions

Urban land-use planning using Geographical Information System and Analytical Hierarchy Process : case study Dhaka city

Urban land-use planning, which is a useful tool for the sustainable development of a city, is a complex decision making process. However, the modern GIS technologies facilitate such complex jobs in two ways – (i) GIS allows to work with large numbr of datasets, (ii) a number of methods, techniques or models could be embeded in GIS for land-use suitability analysis. Analytical Hierarchy Process (AHP), which is a kind of Multi-Criteria Decision Making (MCDM) technique, could be used for urban land-use planning with support of GIS technology. The aim of this thesis is preparing urban land-use planning using GIS and AHP, where the case study is Dhaka city. Dhaka, which is one of the fastest growing mega cities in the world and is the capital city of Bangladesh, is facing acute pressure of increasing population and unplanned urbanization, despite, a number of planning interventions have been taken for the planned development of the city. Recent Detail Area Planning (DAP) for Dhaka city was a cumbersome job but brought little benefits. DAP primarily prepared a land-use plan at city scale using GIS technology. Although huge resources and times were used to build the GIS database, it had promlems on (i) specifying data requirements, (ii) ensuring quality database (having topological rules, elimination of sliver polygons etc.) and (iii) using the database for spatial analysis in view to make better planning decision. In this connection, this thesis tried to conceptualize a model to build geographical database for urban land-use planning to address first two problems and applied GIS-based AHP technique for more sophisticated analysis (problem-iii). After literature review and selection of the study area (Group-E of DAP), the study set a number of criteria through sharing experts’ opinions. Based on those criteria the collected GIS data was transformed into the Geodatabase, where the geodatabase was conceptualized using Unified Modelling Language (UML). Five experts’ opinions were shared and further literature reviews were done for calculating Eigen Values using AHP methodological operations. The Eigen Values show the degree of priority of the criteria. Using Eigen Values, raster criterion maps were prepared from data available in the geodatabase. These criterion maps were overlaid to develop a composite map which was later classified to prepare suitability map. The research result shows that highly suitable area (13%) should be used for urban residential zone; moderately suitable area (35%) should be designated as mixed use zone; low suitable area (42%) should be reserved for agricultural use and open spaces; and not suitable area (10%) should be protected from any types of activities except agriculture. The research approached an urban land-use planning at a regional scale. The research results were also validated with Detail Area Plan of Dhaka Metropolitan Development Plan package in some order. Such validation concludes that Geographical Information System based Analytical Hierarchy Process can be applied successfully for preparing urban land-use planning at the regional level.Dhaka, the capital city of Bangladesh, is one of the fastest growing mega cities in the world. The city is facing acute pressure of increasing population and unplanned urbanization. Since 1959 a number of planning mechanisms have been formulated to promote planned growth of the city. But the city never experienced planned development. Current state of city development is quite unsustainable in nature. Urban land-use planning is a useful mechanism for sustainable city development. At the same time, land-use planning is a complex decision making process as such planning approach encompasses a number of socio-economic, physical and environmental criteria. Modern Geographical Information System (GIS) technology is very much helpful to incorporate these criteria and allow improved decision making process to prepare sustainable planning. Different Multi-Criteria Decision Making Models (MCDM), like, Analytical Hierarchy Model (AHP), can be applied fruitfully with the support of GIS to ease the complex decision making process of spatial planning, e.g., land-use planning. So, the aim of the thesis is to prepare urban land-use planning using GIS and AHP in context of Dhaka city. The thesis used both primary and secondary data. Experts’ opinions were shared to select the criteria for land-use planning and to fix the level of preferences of each criterion. The objective of selecting criteria and their level of preferences were to identify the suitability of areas for residential, industrial, commercial development and for protecting agricultural land. In this purpose, AHP technique was used so that the criteria can be selected easily in hierarchy order, the preferences level can be fixed with consistency and finally, the suitability of land-use can be ranked using GIS. The ranking of suitability allow deciding which land is more suitable for which category of development or for which development control. The research result shows that – The Highly Suitable areas are featured by vacant land, high elevation, no earthquake risk, and well connected with utilities and community services. Hard urban development can be promoted in these areas. These areas should be used for urban residential areas to facilitate new housing development. Moderately Suitable areas are featured by rural homestead, vacant land, existing residential use, high elevation, minimum earthquake risk, close to market places and connected with utilities and community services. These areas have been proposed as mixed-use area. This mixed-use area has potentiality of housing, commercial and industrial development. Low Suitable areas are predominated by agricultural and low lying flood flow zones. These areas should be free from major development. The lands here are close to fault lines. So, the places are also prone to earthquake risk. Here development controlling mechanism is earnest necessary. Agricultural lands should be protected as Bangladesh is facing acute shortages of agricultural land. However, as these areas fall within the Greater Dhaka Metropolitan Area jurisdiction, so, some parcels of land in these areas could be used for sports grounds, parks and other recreational open spaces as a requirement of city’s civic amenities. The Not Suitable areas are featured by agricultural uses, restricted areas (e.g. military camp) and high earthquake risk. Any type of use other than agriculture should be protected in these areas

3D City Models and urban information: Current issues and perspectives

Considering sustainable development of cities implies investigating cities in a holistic way taking into account many interrelations between various urban or environmental issues. 3D city models are increasingly used in different cities and countries for an intended wide range of applications beyond mere visualization. Could these 3D City models be used to integrate urban and environmental knowledge? How could they be improved to fulfill such role? We believe that enriching the semantics of current 3D city models, would extend their functionality and usability; therefore, they could serve as integration platforms of the knowledge related to urban and environmental issues allowing a huge and significant improvement of city sustainable management and development. But which elements need to be added to 3D city models? What are the most efficient ways to realize such improvement / enrichment? How to evaluate the usability of these improved 3D city models? These were the questions tackled by the COST Action TU0801 “Semantic enrichment of 3D city models for sustainable urban development”. This book gathers various materials developed all along the four year of the Action and the significant breakthroughs

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

A Two-Level Information Modelling Translation Methodology and Framework to Achieve Semantic Interoperability in Constrained GeoObservational Sensor Systems

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation. Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data models underpinning these information systems are typically too rigid in their data representation to allow for the ever-changing and evolving nature of geo-spatial domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in an interoperable and computable way. The health domain experiences similar challenges with representing complex and evolving domain information concepts. Within any complex domain (such as Earth system science or health) two categories or levels of domain concepts exist. Those concepts that remain stable over a long period of time, and those concepts that are prone to change, as the domain knowledge evolves, and new discoveries are made. Health informaticians have developed a sophisticated two-level modelling systems design approach for electronic health documentation over many years, and with the use of archetypes, have shown how data, information, and knowledge interoperability among heterogenous systems can be achieved. This research investigates whether two-level modelling can be translated from the health domain to the geo-spatial domain and applied to observing scenarios to achieve semantic interoperability within and between spatial data infrastructures, beyond what is possible with current state-of-the-art approaches. A detailed review of state-of-the-art SDIs, geo-spatial standards and the two-level modelling methodology was performed. A cross-domain translation methodology was developed, and a proof-of-concept geo-spatial two-level modelling framework was defined and implemented. The Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard was re-profiled to aid investigation of the two-level information modelling approach. An evaluation of the method was undertaken using II specific use-case scenarios. Information modelling was performed using the two-level modelling method to show how existing historical ocean observing datasets can be expressed semantically and harmonized using two-level modelling. Also, the flexibility of the approach was investigated by applying the method to an air quality monitoring scenario using a technologically constrained monitoring sensor system. This work has demonstrated that two-level modelling can be translated to the geospatial domain and then further developed to be used within a constrained technological sensor system; using traditional wireless sensor networks, semantic web technologies and Internet of Things based technologies. Domain specific evaluation results show that twolevel modelling presents a viable approach to achieve semantic interoperability between constrained geo-observational sensor systems and spatial data infrastructures for ocean observing and city based air quality observing scenarios. This has been demonstrated through the re-purposing of selected, existing geospatial data models and standards. However, it was found that re-using existing standards requires careful ontological analysis per domain concept and so caution is recommended in assuming the wider applicability of the approach. While the benefits of adopting a two-level information modelling approach to geospatial information modelling are potentially great, it was found that translation to a new domain is complex. The complexity of the approach was found to be a barrier to adoption, especially in commercial based projects where standards implementation is low on implementation road maps and the perceived benefits of standards adherence are low. Arising from this work, a novel set of base software components, methods and fundamental geo-archetypes have been developed. However, during this work it was not possible to form the required rich community of supporters to fully validate geoarchetypes. Therefore, the findings of this work are not exhaustive, and the archetype models produced are only indicative. The findings of this work can be used as the basis to encourage further investigation and uptake of two-level modelling within the Earth system science and geo-spatial domain. Ultimately, the outcomes of this work are to recommend further development and evaluation of the approach, building on the positive results thus far, and the base software artefacts developed to support the approach