José António Tenedório

Predicting the impact of climate change on the invasive decapods of the Iberian inland waters: an assessment of reliability

In an effort to predict the impact of climate change on the distribution of existing invasive species, niche-based models (NBMs) are being increasingly used to make forecasts. Here, we investigate the reliability of these models in predicting future climatic suitability for 4 invasive decapods of the Iberian Peninsula: Cherax destructor, Eriocheir sinensis, Pacifastacus leniusculus and Procambarus clarkii. From an ensemble of forecasts generated by 5 distinct algorithms (generalized linear models, artificial neural networks, support vector machines, random forests and alternating decision trees), we calculated consensus predictions for current conditions and 3 future time periods (2030, 2050 and 2080) under low and high scenarios of greenhouse gas emissions. Three criteria were examined to infer the robustness of the forecasts: ability to predict current distributions, inter-model variability and degree of environmental extrapolation. Our results indicate an overall decline in climatic suitability for the 4 invaders as time progresses. However, we also identified highly distinct levels of predictive uncertainty among species. Good indicators of reliability were found for Procambarusclarkii and Pacifastacusleniusculus, whereas the predictions for C. destructor showed low predictive performance, low inter-model agreement and wide areas of environmental extrapolation. For E. sinensis, the models also showed high variability with respect to areas projected to lose climatic suitability. Overall, our results highlight the need to consider and evaluate multiple sources of uncertainty when using NBM predictions for invaders under current and future conditions.

Fractal cartography of urban areas

In a world in which the pace of cities is increasing, prompt access to relevant information is crucial to the understanding and regulation of land use and its evolution in time. In spite of this, characterization and regulation of urban areas remains a complex process, requiring expert human intervention, analysis and judgment. Here we carry out a spatio-temporal fractal analysis of a metropolitan area, based on which we develop a model which generates a cartographic representation and classification of built-up areas, identifying (and even predicting) those areas requiring the most proximate planning and regulation. Furthermore, we show how different types of urban areas identified by the model co-evolve with the city, requiring policy regulation to be flexible and adaptive, acting just in time. The algorithmic implementation of the model is applicable to any built-up area and simple enough to pave the way for the automatic classification of urban areas worldwide.

Paying as the urban areas grow – implementing and managing urban development charges using a GIS application

Urban development charges (UDC) are considered relevant taxation instruments that can improve the economic sustainability of urban areas and the financial health of the respective local governments. The economic formulation and justification based on the ‘direct benefit principle,’ the ‘accountability principle,’ and the ‘proportionality principle’ requires a methodology that can be supported by a geographic information system (GIS) application. This article presents the research output of a real case study – the municipality of Aljezur, Portugal – and the fundamentals of the GIS tool that was designed. This GIS-based methodology comprises a multi-annual infrastructure capital plan and an accurate zoning map for spatial differentiation of values combining municipal-wide and site-specific approaches, following ‘pay as the urban areas grow’ perspective applied to urban development and new buildings. It requires data integration of the urban planning process with infrastructure and urban growth data in order to manage and monitor the computation of this charge over time, thereby increasing the accuracy, the objectivity and the clarity of the process. The results obtained show that this UDC-GIS application seems well adapted to small municipalities. Its possible replication and use in other contexts require adaptations derived from different urban and taxation policy options and from different legal, organizational, technological, and informational local systems.

Metropolitan Dynamics Typology of the Portuguese Urban System

The metropolitan dynamics typology of the Portuguese urban system is the product of a methodology based on Geographic Information Systems (GIS). A GIS data describes six dimensions of metropolisation (population, economy, urban organisation, society and culture, networks and territorial organisation), based on a matrix of entities or indicators. Such a matrix has been subjected to treatment by neuronal networks through a Self-Organising Map (SOM). The method is robust in order to obtain a typology designated as DYMET (Metropolitan Dynamics Typology). As a result of the application of SOM’s classification algorithm ten types of areas were identified (metropolis core of Lisbon and of Porto, suburbanised area, suburbanised area in consolidation, potential metropolis centre, metropolisation area, area of urban dynamics, area of local centrality, peri-urbanised area, area with weak urban dynamics, area without urban dynamics) and compared to the typologies based on empirical studies of the Portuguese urban network developed mainly in the nineties. The identified types are described and characterised with some global dimension indicators.

Methodology for the development of 3D GIS models in the Coastal Zone

ABSTRACT Magarotto, M., Costa, C., Tenedório, J.A., Silva, C.P., Pontes, T., 2014. Methodology for the development of 3D GIS models in the Coastal Zone. In: Green, A.N. and Cooper, J.A.G. (eds.), Proceedings 13th International Coastal Symposium (Durban, South Africa), Journal of Coastal Research, Special Issue No. 70, pp. 479–484, ISSN 0749-0208. The present work involved a methodology which analyzes land use changes, from 1961 – 2011 using digital image processing and visual analysis of one satellite image and aerial photos. A simplified methodology using GIS 3D generates models of the coastal zone and its index of vertical growth. The GIS method uses SPRING - INPE (freeware) and ArcScence (ESRI). The data was obtained in the field (2011). The base area used was seventeen census sectors of the Brazilian Institute of Geography and Statistics (IBGE). To analyze vertical growth, a Volumetric Compactness Index (CVI) was created. It is able to track the tallest buildings over the years studied. The sectors were analyzed for spatial (N-S; E-W) and temporal (50 years) variations, where they were divided into North, Central and South zones of Boa Viagem. At all sectors occupation indexes are presently high, a strong trend of vertical growth exist that results in high volumetric compactness. Occupation and vertical growth are especially accentuated in the 1981–1996, reaching a maximum in 2011. Vertical growth increased from shore- inland being more prevalent towards the Central Zone, followed by the North and South. As a result of these processes, several problems arose with the most relevant including: impermeable coverings; large volumes of urban runoff; increasing temperatures; wind funneling; traffic jams; air pollution and; deficient water supply, wastewater collection and solid wastes collection. The results obtained using this methodology may be useful for the management of coastal areas and the potential for its development in relation to urban planning and development. The models obtained can prioritize mitigation actions in similarly developed neighborhoods.

Technologies for Urban and Spatial Planning: Virtual Cities and Territories

This book will discuss how technological advancements have changed traditional urban and spatial planning. The inclusion of conventional elements with modern technologies is allowing this field to advance at a rapid pace. The objectives of this book are to: (i) contribute to the dissemination of the recent research and development of the use of information and communication technologies (ICT) in urban and spatial planning by trying to demonstrate their usability in the planning processes through the presentation of relevant case studies; (ii) give additional evidence to the fact that ICT are the privileged means to produce virtual cities and territories; and (iii) present a group of illustrative reviews of the scientific production made by both academics and practitioners in the field.

Metropolitan Dynamics Typology of the Portuguese Urban System~!2009-04-07~!2009-05-15~!2010-03-02~!

The metropolitan dynamics typology of the Portuguese urban system is the product of a methodology based on Geographic Information Systems (GIS). A GIS data describes six dimensions of metropolisation (population, economy, urban organisation, society and culture, networks and territorial organisation), based on a matrix of entities or indicators. Such a matrix has been subjected to treatment by neuronal networks through a Self-Organising Map (SOM). The method is robust in order to obtain a typology designated as DYMET (Metropolitan Dynamics Typology). As a result of the application of SOM’s classification algorithm ten types of areas were identified (metropolis core of Lisbon and of Porto, suburbanised area, suburbanised area in consolidation, potential metropolis centre, metropolisation area, area of urban dynamics, area of local centrality, peri-urbanised area, area with weak urban dynamics, area without urban dynamics) and compared to the typologies based on empirical studies of the Portuguese urban network developed mainly in the nineties. The identified types are described and characterised with some global dimension indicators.

Valorisation of urban elements through 3D models generated from image matching point clouds and augmented reality visualization based in mobile platforms

The use of multiple sets of images with high level of overlapping to extract 3D point clouds has increased progressively in recent years. There are two main fundamental factors in the origin of this progress. In first, the image matching algorithms has been optimised and the software available that supports the progress of these techniques has been constantly developed. In second, because of the emergent paradigm of smart cities which has been promoting the virtualization of urban spaces and their elements. The creation of 3D models for urban elements is extremely relevant for urbanists to constitute digital archives of urban elements and being especially useful for enrich maps and databases or reconstruct and analyse objects/areas through time, building and recreating scenarios and implementing intuitive methods of interaction. These characteristics assist, for example, higher public participation creating a completely collaborative solution system, envisioning processes, simulations and results. This paper is organized in two main topics. The first deals with technical data modelling obtained by terrestrial photographs: planning criteria for obtaining photographs, approving or rejecting photos based on their quality, editing photos, creating masks, aligning photos, generating tie points, extracting point clouds, generating meshes, building textures and exporting results. The application of these procedures results in 3D models for the visualization of urban elements of the city of Barcelona. The second concerns the use of Augmented Reality through mobile platforms allowing to understand the city origins and the relation with the actual city morphology, (en)visioning solutions, processes and simulations, making possible for the agents in several domains, to fundament their decisions (and understand them) achieving a faster and wider consensus.

Sensitivity Analysis of Spatial Autocorrelation Using Distinct Geometrical Settings: Guidelines for the Quantitative Geographer

Inferences based on spatial analysis of areal data depend greatly on the method used to quantify the degree of proximity between spatial units - regions. These proximity measures are normally organized in the form of weights matrices, which are used to obtain statistics that take into account neighbourhood relations between agents. In any scientific field where the focus is on human behaviour, areal datasets are greatly relevant since this is the most common form of data collection (normally as count data). The method or schema used to divide a continuous spatial surface into sets of discrete units influences inferences about geographical and social phenomena, mainly because these units are neither homogeneous nor regular. This article tests the effect of different geometrical data aggregation schemas - administrative regions and hexagonal surface tessellation - on global spatial autocorrelation statistics. Two geographical variables are taken into account: scale (resolution) and form (regularity). This is achieved through the use of different aggregation levels and geometrical schemas. Five different datasets are used, all representing the distribution of resident population aggregated for two study areas, with the objective of consistently test the effect of different spatial aggregation schemas.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

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.