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.

Integration of a mobile autonomous robot in a surveillance multi-agent system

This dissertation aims to guarantee the integration of a mobile autonomous robot equipped with many sensors in a multi-agent distributed and georeferenced surveillance system. The integration of a mobile autonomous robot in this system leads to new features that will be available to clients of surveillance system may use. These features may be of two types: using the robot as an agent that will act in the environment or by using the robot as a mobile set of sensors. As an agent in the system, the robot can move to certain locations when alerts are received, in order to acknowledge the underlying events or take to action in order to assist in resolving this event. As a sensor platform in the system, it is possible to access information that is read from the sensors of the robot and access complementary measurements to the ones taken by other sensors in the multi-agent system. To integrate this mobile robot in an effective way it is necessary to extend the current multi-agent system architecture to make the connection between the two systems and to integrate the functionalities provided by the robot into the multi-agent system.

Mobile image processing to support educational geometry games

The mobile IT era is here, it is still growing and expanding at a steady rate and, most of all, it is entertaining. Mobile devices are used for entertainment, whether social through the so-called social networks, or private through web browsing, video watching or gaming. Youngsters make heavy use of these devices, and even small children show impressive adaptability and skill. However not much attention is directed towards education, especially in the case of young children. Too much time is usually spent in games which only purpose is to keep children entertained, time that could be put to better use such as developing elementary geometric notions. Taking advantage of this pocket computer scenario, it is proposed an application geared towards small children in the 6 – 9 age group that allows them to consolidate knowledge regarding geometric shapes, forming a stepping stone that leads to some fundamental mathematical knowledge to be exercised later on. To achieve this goal, the application will detect simple geometric shapes like squares, circles and triangles using the device’s camera. The novelty of this application will be a core real-time detection system designed and developed from the ground up for mobile devices, taking into account their characteristic limitations such as reduced processing power, memory and battery. User feedback was be gathered, aggregated and studied to assess the educational factor of the application.

Can location-based mobile marketing enhance the customer experience and increase customer satisfaction and loyalty?

This study intends to explore the impact of customer experience on customer satisfaction and loyalty by trying to understand how location-based mobile marketing might enhance the customer experience. Primary data was collected from 201 smartphone users in 24 countries. Results have indicated that targeted location-based marketing positively influences customers’ experiences. Besides, the analysis has also shown a favorable impact on customers’ satisfaction and self-perceived loyalty. This suggests that location-based mobile marketing has the potential to positively add value to a customer’s experience and should therefore be considered an important tool in marketing communications.

Evaluation of the welfare impact of regulating mobile termination rates in Portugal

Following the European Commission’s 2009 Recommendation on the Regulatory Treatment of Fixed and Mobile Termination Rates in the EU, the Portuguese regulatory authority (ANACOM) decided to reduce termination prices in mobile networks to their long-run incremental cost (LRIC). Nevertheless, no serious quantitative assessment of the potential effects of this decision was carried out. In this paper, we adapt and calibrate the Harbord and Hoernig (2014) model of the UK mobile telephony market to the Portuguese reality, and simulate the likely impact on consumer surplus, profits and welfare of four different regulatory approaches: pure LRIC, reciprocal termination charges with fixed networks, “bill & keep”, and asymmetric termination rates. Our results show that reducing MTRs does increase social welfare, profits and consumer surplus in the fixed market, but mobile subscribers are seriously harmed by this decision.

How to design and develop There App: A mobile app focused on live video streaming, promoting new social interactions

This work project aims to demonstrate how to design and develop an innovative concept of video streaming app. The project combines technology push and market pull theories into developing a product that is more suitable for the customer needs, with the particularity that there is no other way of seeing any place in the world, live and ondemand. An analysis on the bigger influencers in terms of design-thinking and new product development, as Tim Brown or Paul Trott, lead to a better understanding on how There App should evolve, keeping in mind the customer desires and technical features.

Opportunities and threats for the launch of a smartphone app

Field lab: Entrepreneurial and innovative ventures

Impact of mobile app user acquisition on managerial decisions: Evidence from empirical experiment

In this research we conducted a mixed research, using qualitative and quantitative analysis to study the relationship and impact between mobile advertisement and mobile app user acquisition and the conclusions companies can derive from it. Data was gathered from management of mobile advertisement campaigns of a portfolio of three different mobile apps. We found that a number of implications can be extracted from this intersection, namely to product development, internationalisation and management of marketing budget. We propose further research on alternative app users sources, impact of revenue on apps and exploitation of product segments: wearable technology and Internet of Things.

Cliente mobile para consumo e disponibilização de serviços georreferenciados

Actualmente as aplicações móveis são indispensáveis para o utilizador. De acordo com estudos recentes, as receitas geradas pela sua utilização resultaram em aproximadamente 20 biliões de dólares só em 2013. Com estes valores estima-se que no futuro estes números aumentem, daí tornar-se imperativo abordar num estudo científico sobre este mercado em expansão. A somar às inúmeras aplicações referentes ao sistema móvel Android, surgem as aplicações de serviços georreferenciados que vão aqui ser abordadas em maior profundidade, nomeadamente o consumo e disponibilização destes serviços em clientes mobile. Ponderadas diversas soluções é possível com alguns melhoramentos atingir benefícios específicos para um maior número de utilizadores tendo em conta as suas características a priori. Uma das questões principais passa pela capacidade de publicação de diversas fontes de informação (vários publishers) com o uso de uma Application Programing Interface (API) documentada e aberta para que qualquer entidade possa publicar os seus conteúdos georreferenciados. O consumo por parte dos utilizadores (subscriber) é feita numa plataforma móvel Android onde os possam vários publishers possam publicar os seus conteúdos a partir da posição do utilizador. Esta publicação será facilitada criando bases de dados para o armazenamento de todas as informações relevantes tanto da parte dos publishers como dos subscribers. A validação deste trabalho consistiu em testar vários tipos de publicações, nomeadamente texto, imagem e gráficos na sua pesquisa e consumo numa plataforma móvel Android. Numa segunda fase, foi testada a publicação de gráficos em tempo real na plataforma.

A business plan for a new mobile application to the consumer foodservice industry

The Portuguese consumer foodservice industry is experiencing a boost in technology adoption, driven by significant changes in consumer behavior and business dynamics, due to mobile increasing penetration. Accordingly, the present work project consists on developing a business plan for meeting an identified opportunity in the technological foodservice landscape. Therefore, this report is divided into three sections, each of which addressing different objectives: (A) External Environment, providing key external insights that support the opportunity; (B) Strategy Formulation, establishing a strategic direction; and (C) Action Plan, determining an implementation plan for starting the business

Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery

Many municipal activities require updated large-scale maps that include both topographic and thematic information. For this purpose, the efficient use of very high spatial resolution (VHR) satellite imagery suggests the development of approaches that enable a timely discrimination, counting and delineation of urban elements according to legal technical specifications and quality standards. Therefore, the nature of this data source and expanding range of applications calls for objective methods and quantitative metrics to assess the quality of the extracted information which go beyond traditional thematic accuracy alone. The present work concerns the development and testing of a new approach for using technical mapping standards in the quality assessment of buildings automatically extracted from VHR satellite imagery. Feature extraction software was employed to map buildings present in a pansharpened QuickBird image of Lisbon. Quality assessment was exhaustive and involved comparisons of extracted features against a reference data set, introducing cartographic constraints from scales 1:1000, 1:5000, and 1:10,000. The spatial data quality elements subject to evaluation were: thematic (attribute) accuracy, completeness, and geometric quality assessed based on planimetric deviation from the reference map. Tests were developed and metrics analyzed considering thresholds and standards for the large mapping scales most frequently used by municipalities. Results show that values for completeness varied with mapping scales and were only slightly superior for scale 1:10,000. Concerning the geometric quality, a large percentage of extracted features met the strict topographic standards of planimetric deviation for scale 1:10,000, while no buildings were compliant with the specification for scale 1:1000.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.