THE VISUALIZATION AND ANALYSIS OF URBAN FACILITY POIS USING NETWORK KERNEL DENSITY ESTIMATION CONSTRAINED BY MULTI-FACTORS

The urban facility, one of the most important service providers is usuallyrepresented by sets of points in GIS applications using POI (Point of Interest) modelassociated with certain human social activities. The knowledge about distributionintensity and pattern of facility POIs is of great significance in spatial analysis,including urban planning, business location choosing and social recommendations.Kernel Density Estimation (KDE), an efficient spatial statistics tool for facilitatingthe processes above, plays an important role in spatial density evaluation, becauseKDE method considers the decay impact of services and allows the enrichment ofthe information from a very simple input scatter plot to a smooth output densitysurface. However, the traditional KDE is mainly based on the Euclidean distance,ignoring the fact that in urban street network the service function of POI is carriedout over a network-constrained structure, rather than in a Euclidean continuousspace. Aiming at this question, this study proposes a computational method of KDEon a network and adopts a new visualization method by using 3-D “wall” surface.Some real conditional factors are also taken into account in this study, such astraffic capacity, road direction and facility difference. In practical works theproposed method is implemented in real POI data in Shenzhen city, China to depictthe distribution characteristic of services under impacts of multi-factors

Investigating behavioural and computational approaches for defining imprecise regions

People often communicate with reference to informally agreedplaces, such as “the city centre”. However, views of the spatial extent of such areas may vary, resulting in imprecise regions. We compare perceptions of Sheffield’s City Centre from a street survey to extents derived from various web-based sources. Such automated approaches have advantages of speed, cost and repeatability. We show that footprints from web sources are often in concordance with models derived from more labour-intensive methods. Notable exceptions however were found with sources advertising or selling residential property. Agreement between sources was measured by aggregating them to identify locations of consensus

The visualization and analysis of urban facility pois using network kernel density estimation constrained by multi-factors

The urban facility, one of the most important service providers is usually represented by sets of points in GIS applications using POI (Point of Interest) model associated with certain human social activities. The knowledge about distribution intensity and pattern of facility POIs is of great significance in spatial analysis, including urban planning, business location choosing and social recommendations. Kernel Density Estimation (KDE), an efficient spatial statistics tool for facilitating the processes above, plays an important role in spatial density evaluation, because KDE method considers the decay impact of services and allows the enrichment of the information from a very simple input scatter plot to a smooth output density surface. However, the traditional KDE is mainly based on the Euclidean distance, ignoring the fact that in urban street network the service function of POI is carried out over a network-constrained structure, rather than in a Euclidean continuous space. Aiming at this question, this study proposes a computational method of KDE on a network and adopts a new visualization method by using 3-D "wall" surface. Some real conditional factors are also taken into account in this study, such as traffic capacity, road direction and facility difference. In practical works the proposed method is implemented in real POI data in Shenzhen city, China to depict the distribution characteristic of services under impacts of multi-factors

Reflecting Human Knowledge of Place and Route-Choice Behavior Using Big Data

Exploring human knowledge of geographical space and related behavior not only helps in understanding human-environment interactions and dynamic geographic processes, but also advances Geographic Information Systems (GIS) toward a human-centric paradigm to make daily life more efficient. Today’s relatively easy acquisition of various big data provides an unprecedented opportunity for geographers to answer research questions that previously could not be adequately addressed. However, new challenges also arise regarding data quality and bias as well as change in methodology for dealing with big data that are different from traditional data types. Representing people’s perception of place and studying driver’s route-choice behavior are two of the many applications of big data in answering research questions about human knowledge and behavior in the fields of GIS and transportation. Incorporating three papers, this dissertation focuses on these two different applications to achieve the following objectives: 1) examine the degree to which a geographic place’s spatial extent can be estimated from human-generated geotagged photos; 2) address the challenge of geotagged photos’ uneven spatial distribution in place estimation and explore an approach that can better derive a place’s spatial extent; 3) develop a method that can properly estimate the spatial extent of a place that has multiple disjoint regions while considering geotagged photos’ uneven distribution; 4) explore useful spatiotemporal patterns of taxi drivers’ route-choice behavior in a dynamic urban environment. This dissertation makes three major contributions to big data applications’ systematic theory: 1) proposes an effective approach to handling the uneven spatial distribution problem of geotagged photos as a type of volunteered geographic data by modeling their representativeness; 2) develops methods that can properly derive the vague spatial extent of a place with or without disjoint regions; and 3) explores taxi drivers’ route-choice patterns in different situations that can inform future transportation decisions and policy-making processes

Exploiting empirical knowledge for automatic delineation of city centres from large-scale topographic databases

Current topographic databases rarely represent higher order geographic phenomena, such as city centres. However, such concepts are often referred to by humans and used in various forms of spatial analysis. Hence, the value and usability of topographic databases can greatly be improved by methods that automatically create such higher order phenomena through cartographic pattern recognition techniques, departing from the very detailed, geometry-oriented representations of topographic databases. As many higher order phenomena are only vaguely defined, this paper develops and evaluates a methodology to acquire definitional knowledge about geographic phenomena by participant experiments and use this knowledge to drive the cartographic pattern recognition process. The method is applied to acquire knowledge about British city centres and delineate referents of city centre from topographic data. City centres produced for ten British cities are compared to areas derived from alternative sources

Centro da cidade: "As notícias da minha morte são manifestamente exageradas"?

Mestrado em Planeamento Regional e UrbanoO centro da cidade é o espaço da cidade mais prestigiado, o local da cidade onde as pessoas podem conviver, trabalhar e aceder a comércio e a serviços. Nas últimas décadas muito se tem apregoado sobre a morte do centro tradicional, considerado o centro histórico das cidades. Com vista a desmitificar a morte há muito anunciada dos centros históricos, inicia-se uma confrontação de perspetivas de vários autores com o intuito de perceber as razões subjacentes a essa crença. Uma das causas apontadas à morte dos centros históricos tem a ver com o envelhecimento da população residente nestes locais das cidades. Centrando a atenção na vertente demográfica, procura-se de seguida perceber a dinâmica demográfica de diversos concelhos e freguesias centrais com o intuito de perceber se a dinâmica demográfica é semelhante entre as diversas escalas de análise. De seguida definem-se critérios para delimitar o objeto de estudo “centro de cidade” e estuda-se a dinâmica demográfica do centro da cidade de Aveiro. Este será o caso de estudo que permitirá perceber se efetivamente os centros históricos encontram-se envelhecidos, como se tem vindo a divulgar nas últimas décadas e sugerem-se uma série de indicadores e recomendações que visam facilitar a delimitação do centro no espaço da cidade.The centre is the most prestigious space in the city. It is where people can live, work and access to trade and services. In recent decades a lot has been told about the end of the traditional centre, which is considered the historical part of the city. In order to demystify the long announced death of historic centres, it will be exposed some different point of views of several authors. This will help us to understand the underlying reasons for this belief. It is held that one of the causes for the death of historic centres is related to the aging of those who live there. As far as the demographic aspects are concerned, a study will take place on different municipalities to realize if demographic dynamic is similar between the different features of analysis. Afterwards, criteria will be defined to delimit the study object, "city centre", and the population dynamics of the centre of Aveiro will be analysed. This will allow us to effectively comprehend if the historic centres are indeed aged, as it has been spread in recent decades. A series of indicators and recommendations is also suggested to facilitate the delimitation of the city centre on the city space