Spatial Patterns and Irregularities of the electoral data: general elections in Canada

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

The influence of off-screen landmarks on user orientation

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

High or low initial setting price?: Initial setting price as prediction of intention to bid in on line auctions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Reconceptualising public spaces of (IN)equality: sensing and creating layers of visibility

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Territorial - Especialidade: Geografia Humana

Correction of the anisotropy in resistivity: application to pore pressure prediction

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

Constituição de Geocomunidades de Informação Geográfica em Meio Empresarial

O presente trabalho de projecto, realizado no âmbito do Mestrado em Gestão do Território, Área de Especialização em Detecção Remota e Sistemas de Informação Geográfica, ministrado na Faculdade de Ciências Sociais e Humanas (FCSH) da Universidade Nova de Lisboa, regista o trabalho desenvolvido sobre a constituição de geocomunidades de informação geográfica em meio empresarial. Este trabalho foi realizado com o apoio partilhado FCSH e Nokia Portugal. O trabalho projecto está dividido em duas partes. Uma primeira parte que consiste numa abordagem teórica sobre a evolução dos SIG, sobre o estado da arte, sobre a nova geografia (neogeography); contem também uma abordagem sobre o crowdsourcing e as suas funcionalidades e potencialidades, caracterização dos seus utilizadores e o seu valor económico e social. Esta primeira parte tem o intuito de tentar chegar a uma conclusão sobre qual a melhor opção para uma empresa, no que toca à criação de base de dados geográficas olhando para as variadíssimas opções que existem no mercado desde base de dados governamentais, às privadas até às base de dados de cariz voluntário e sem custo para o utilizador ao aceder a essa informação. A segunda parte, de natureza prática, pretende cruzar dados e informação sobre duas Expert-Community que foram criadas com o intuito de testar a plataforma Map-Wiki da Nokia durante doze meses. Apesar de ser uma parte mais prática, conta também com uma breve retrospectiva da Nokia e das aplicações baseadas em Global Position Systems, uma explicação sobre o que é o Nokia Here e uma comparação entre as várias propostas existentes no mercado.

Interactive spatial decision support for sustainable agroforestry management: a case study in East Kalimantan, Indonesia

Forest managers, stakeholders and investors want to be able to evaluate economic, environmental and social benefits in order to improve the outcomes of their decisions and enhance sustainable forest management. This research developed a spatial decision support system that provides: (1) an approach to identify the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a tool to inform prospective investors and stakeholders of the potential and opportunities for integrated agroforestry management; (3) a simulation environment that enables evaluation via a dashboard with the opportunity to perform interactive sensitivity analysis for key parameters of the project; (4) a 3D interactive geographic visualization of the economic, environmental and social outcomes, which facilitate understanding and eases planning. Although the tool and methodology presented are generic, a case study was performed in East Kalimantan, Indonesia. For the whole study area, it was simulated the most suitable location for three different plantation schemes: monoculture of timber, a specific recipe (cassava, banana and sugar palm) and different recipes per geographic unit. The results indicate that a mixed cropping plantation scheme, with different recipes applied to the most suitable location returns higher economic, environmental and social benefits.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Relating the spatial component and users interests to improve applications based on questions, petitions and participatory processes

Nowadays, participatory processes attending the need for real democracy and transparency in governments and collectives are more needed than ever. Immediate participation through channels like social networks enable people to give their opinion and become pro-active citizens, seeking applications to interact with each other. The application described in this dissertation is a hybrid channel of communication of questions, petitions and participatory processes based on Public Participation Geographic Information System (PPGIS), Participation Geographic Information System (PGIS) and ‘soft’ (subjective data) Geographic Information System (SoftGIS) methodologies. To achieve a new approach to an application, its entire design is focused on the spatial component related with user interests. The spatial component is treated as main feature of the system to develop all others depending on it, enabling new features never seen before in social actions (questions, petitions and participatory processes). Results prove that it is possible to develop a working application mainly using open source software, with the possibility of spatial and subject filtering, visualizing and free download of actions within application. The resulting application empowers society by releasing soft data and defines a new breaking approach, unseen so far.

Spatial analysis of crime evolution in Portugal between 1995 and 2013

The main objective of this survey was to perform descriptive analysis of crime evolution in Portugal between 1995 and 2013. The main focus of this survey was to analyse spatial crime evolution patterns in Portuguese NUTS III regions. Most important crime types have been included into analysis. The main idea was to uncover relation between local patterns and global crime evolution; to define regions which have contributed to global crime evolution of some specific crime types and to define how they have contributed. There were many statistical reports and scientific papers which have analysed some particular crime types, but one global spatial-temporal analysis has not been found. Principal Component Analysis and multidimensional descriptive data analysis technique STATIS have been the base of the analysis. The results of this survey has shown that strong spatial and temporal crime patterns exist. It was possible to describe global crime evolution patterns and to define crime evolution patterns in NUTS III regions. It was possible to define three to four groups of crimes where each group shows similar spatial crime dynamics.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Analysis of temporal and spatial variations of forest. A case of study in notheastern Armenia

The forest has a crucial ecological role and the continuous forest loss can cause colossal effects on the environment. As Armenia is one of the low forest covered countries in the world, this problem is more critical. Continuous forest disturbances mainly caused by illegal logging started from the early 1990s had a huge damage on the forest ecosystem by decreasing the forest productivity and making more areas vulnerable to erosion. Another aspect of the Armenian forest is the lack of continuous monitoring and absence of accurate estimation of the level of cuts in some years. In order to have insight about the forest and the disturbances in the long period of time we used Landsat TM/ETM + images. Google Earth Engine JavaScript API was used, which is an online tool enabling the access and analysis of a great amount of satellite imagery. To overcome the data availability problem caused by the gap in the Landsat series in 1988- 1998, extensive cloud cover in the study area and the missing scan lines, we used pixel based compositing for the temporal window of leaf on vegetation (June-late September). Subsequently, pixel based linear regression analyses were performed. Vegetation indices derived from the 10 biannual composites for the years 1984-2014 were used for trend analysis. In order to derive the disturbances only in forests, forest cover layer was aggregated and the original composites were masked. It has been found, that around 23% of forests were disturbed during the study period.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Tool for spatial and dynamic representation of artistic performances

This proposal aims to explore the use of available technologies for video representation of sets and performers in order to serve as support for composition processes and artistic performer rehearsals, while focusing in representing the performer’s body and its movements, and its relation with objects belonging to the three-dimensional space of their performances. This project’s main goal is to design and develop a system that can spatially represent the performer and its movements, by means of capturing processes and reconstruction using a camera device, as well as enhance the three-dimensional space where the performance occurs by allowing interaction with virtual objects and by adding a video component, either for documentary purposes, or for live performances effects (for example, using video mapping video techniques in captured video or projection during a performance).