Data Science Technologies for Vibrant Cities

Smart Cities forced IT technologies make a significant step in their development. A new generation of agile knowledge based software applications and systems have been successfully designed and implemented. Wide capabilities of the agile applications were sufficient to meet the complete set of requirements of smart cities. Fast transformation of modern cities from smart cities to vibrant cities throws new even more complicated challenges to information technologies. While smart cities assumed wide usage of agile means and tools for solving applied tasks, applications for vibrant cities must provide agile environment for exploring and managing of all types of data, information and knowledge. Agile environment must be flexible enough to support iterative data processing and analyses procedures that can be easily reorganized or changed depending on context. The aim of agile environment creation and support is to extend a set of used mathematical, technological and program solutions. In the paper it is proposed to build applications for vibrant cities using agile data science methodologies and toolsets within the commonly used approaches for developing agile information systems

Technological Solutions for Knowledge Management in Smart Cities

Nowadays huge volume of information, data and knowledge, that directly or indirectly relates to modern cities, their state and problems is gathered and stored. Effectiveness of its use significantly influences on effectiveness of city development. Due to constantly increasing amount of information and knowledge, for its best use special tools for knowledge management, including tools for knowledge systematization and building formalized descriptions as well as new algorithms for knowledge processing and application are required. In the paper a set of technological solutions focused on knowledge retrieval from multidimensional measurements provided by different sources of information is suggested. Use of developed technologies allow to organize operative processing of new measurements, taking into account all available knowledge. Dealing with measurements at the level of knowledge about measurements provides solutions of end user problems in terms of subject domain objects or situations but not separate measurements. Several subject domains and their tasks, that can be solved using the proposed set of technological solutions, are defined

Trends and concerns in digital cartography

CISRG discussion paper ;

Geographical information retrieval with ontologies of place

Geographical context is required of many information retrieval tasks in which the target of the search may be documents, images or records which are referenced to geographical space only by means of place names. Often there may be an imprecise match between the query name and the names associated with candidate sources of information. There is a need therefore for geographical information retrieval facilities that can rank the relevance of candidate information with respect to geographical closeness of place as well as semantic closeness with respect to the information of interest. Here we present an ontology of place that combines limited coordinate data with semantic and qualitative spatial relationships between places. This parsimonious model of geographical place supports maintenance of knowledge of place names that relate to extensive regions of the Earth at multiple levels of granularity. The ontology has been implemented with a semantic modelling system linking non-spatial conceptual hierarchies with the place ontology. An hierarchical spatial distance measure is combined with Euclidean distance between place centroids to create a hybrid spatial distance measure. This is integrated with thematic distance, based on classification semantics, to create an integrated semantic closeness measure that can be used for a relevance ranking of retrieved objects

Collaborative geographic visualization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative visualization purposes. Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment

Mapping and monitoring forest remnants : a multiscale analysis of spatio-temporal data

KEYWORDS : Landsat, time series, machine learning, semideciduous Atlantic forest, Brazil, wavelet transforms, classification, change detectionForests play a major role in important global matters such as carbon cycle, climate change, and biodiversity. Besides, forests also influence soil and water dynamics with major consequences for ecological relations and decision-making. One basic requirement to quantify and model these processes is the availability of accurate maps of forest cover. Data acquisition and analysis at appropriate scales is the keystone to achieve the mapping accuracy needed for development and reliable use of ecological models.The current and upcoming production of high-resolution data sets plus the ever-increasing time series that have been collected since the seventieth must be effectively explored. Missing values and distortions further complicate the analysis of this data set. Thus, integration and proper analysis is of utmost importance for environmental research. New conceptual models in environmental sciences, like the perception of multiple scales, require the development of effective implementation techniques.This thesis presents new methodologies to map and monitor forests on large, highly fragmented areas with complex land use patterns. The use of temporal information is extensively explored to distinguish natural forests from other land cover types that are spectrally similar. In chapter 4, novel schemes based on multiscale wavelet analysis are introduced, which enabled an effective preprocessing of long time series of Landsat data and improved its applicability on environmental assessment.In chapter 5, the produced time series as well as other information on spectral and spatial characteristics were used to classify forested areas in an experiment relating a number of combinations of attribute features. Feature sets were defined based on expert knowledge and on data mining techniques to be input to traditional and machine learning algorithms for pattern recognition, viz . maximum likelihood, univariate and multivariate decision trees, and neural networks. The results showed that maximum likelihood classification using temporal texture descriptors as extracted with wavelet transforms was most accurate to classify the semideciduous Atlantic forest in the study area.In chapter 6, a multiscale approach to digital change detection was developed to deal with multisensor and noisy remotely sensed images. Changes were extracted according to size classes minimising the effects of geometric and radiometric misregistration.Finally, in chapter 7, an automated procedure for GIS updating based on feature extraction, segmentation and classification was developed to monitor the remnants of semideciduos Atlantic forest. The procedure showed significant improvements over post classification comparison and direct multidate classification based on artificial neural networks.</p

Building Smart Applications for Smart Cities – IGIS based Architectural Framework

To solve different kinds of complicated problems which arise in context of intensive development of modern cities a great number of various applications are constantly being developed. The most part of these applications are based on processing big volumes of heterogeneous data gathered from different types of available sources in real time. In the report an architectural framework oriented on building applications for smart cities in shortest time and with minimum spent of resources is suggested. The framework is based on intelligent geo information technologies and includes architectural and technological solutions along with many different computational libraries for building intelligent adaptive applications. Special attention is paid to information and knowledge organization. Different aspects of use of ontologies in the framework is discussed. Main directions of further development of proposed approach are defined

An Egocentric Spatial Data Model for Intelligent Mobile Geographic Information Systems

Individuals in unknown locations, such as utility workers in the field, soldiers on a mission, or sightseeing tourists, share the need for an answer to two basic questions: Where am I? and What is in front of me?Because such information is not readily available in foreign locations, aids in the form of paper maps or mobile GISs, which give individuals an all-inclusive view of the environment, are often used. This panoptic view may hinder the positioning and orienteering process, since people perceive their surroundings perspectively from their current position. In this thesis, I describe a novel framework that resolves this problem by applying sensors that gather the individual\u27s spatial frame of reference. This spatial frame of reference, in combination with an egocentric spatial data model enables an injective mapping between the real world and the data frame of reference, hence, alleviating the individual\u27s cognitive workload. Furthermore, our egocentric spatial data model allows intelligent mobile Geographic Information Systems to capture the notions of here and there, and, consequently, provides insight into the individual\u27s surroundings. Finally, our framework, in conjunction with the context given by the task to be performed, enables intelligent mobile Geographic Information Systems to implicitly answer questions with respect to where, what, and how