The human risk as a spatial component using Newton?s Gravity model is explored for the first time in this research along with fuels and road density variables to predict the fire occurrences for Southeast Mississippi fire district. The fire risk map indicated that fires occur in clusters and are dependent on fire size and distance from roads. The results proved that fire size increases as fire locations increase. Fire locations decrease significantly beyond 160 meters with increasing road distance. The Gravity model proved to be a better estimator of fire risk while a similar road density model proved to be better in very low and medium fire risk zones. Compared to road density, the gravity model significantly proved a better estimate of very low fire risk for all seasons and summer low fire risk. For all other fire risks, though, gravity model showed better results no significant differences were observed.

A novel approach for modeling anthropogenically-initiated wildfire ignition was developed that significantly advances the theoretical knowledge of human-wildfire interactions. Gravity interaction models that are commonly used for economic analyses associated with business competition were combined with fluid dynamics models that mimic human movement patterns to predict the probability of anthropogenically-initiated wildfire. Herein, a combined gravity interaction and fluid dynamics models is developed and validated for wildfire potential prediction against historic and current wildfire data. The study identified population centers and transportation corridors, in particular: proximity to railroads and roads; traffic volume; and density of the corridors as the most influential factors for wildfire ignition. The population centers are identified as global influencing factors, and are modeled as the gravity term. The transportation corridors are identified as local influencing factors, and are modeled using fluid flow analogy as diffusion and convection terms. An analytic convection diffusion model (CDM) model is derived and the model coefficients calibrated using historic wildfire data. The model is implemented in GIS, and applied for the prediction of wildfire potential prediction in southeastern Mississippi. The model shows a correlation of R2=0.87 against winter historic data, whereas the Gravity model with a fuel component shows only R2=0.75 correlations. The improved predictions using the proposed CDM model is due to its capability to predict both the global and the local measure of incendiary activity patterns within a single dynamic equation. The CDM model can be used as a standalone model that can predict the wildfire potential in a region. It can also be combined with the fuel layer and meteorological conditions to obtain spatio-temporal variation of wildfire risks, which would provide a decision support system for wildfire mitigation and land use planning and development. The CDM model will help fire managers better plan wildfire mitigation (fuel reduction) strategies and effectively stage equipment and personnel geographically in areas of drought that are coincident with high ignition probability. Land use and transportation managers will gain better understanding of the changes in wildfire risk pattern due to urban fringe development.

This paper exposes problems of the commonly used technique of splitting the available data in neural spatial interaction modelling into training, validation, and test sets that are held fixed and warns about drawing too strong conclusions from such static splits. Using a bootstrapping procedure, we compare the uncertainty in the solution stemming from the data splitting with model specific uncertainties such as parameter initialization. Utilizing the Austrian interregional telecommunication traffic data and the differential evolution method for solving the parameter estimation task for a fixed topology of the network model [ i.e. J = 9] this paper illustrates that the variation due to different resamplings is significantly larger than the variation due to different parameter initializations. This result implies that it is important to not over-interpret a model, estimated on one specific static split of the data. (authors' abstract) / Series: Discussion Papers of the Institute for Economic Geography and GIScience

The city of Pretoria has a diverse mix of people moving in and around it. This dynamic, ever-changing movement, combined with the city’s cultural diversity, renders it ideal for an investigation into the relationship (or lack thereof) that exists between the moving body and architectural space. The city and its architectural spaces are viewed as static. The human body and its movement is dynamic. These static spaces cannot always accommodate the dynamic movement taking place within and around them. This leads to a lack of dialogue or interaction between the two, causing a tension which is further aggravated by the fact that they are situated within a constantly changing environment. The aim of this thesis is not only to examine the relationship between the city and the human body moving through its architectural spaces, but also to provide the platform for an investigation into the establishment of an active dialogue between the two. CAPTURE is envisaged as an experimental laboratory in the city of Pretoria. It aims to rejuvenate the city’s CBD, as well as to develop and promote arts and culture through the creation of a public exhibition space. It is a design intervention intended to create a space which captures and navigates its users through it, by exposing them to the different functions facilitated within it, as well as to the space and to each other. The introduction of this spatial intervention, informed by the existing pedestrian movement through an identified public thoroughfare, will encourage an active dialogue between the user and the space. Public art, in the form of the photographic image, has been identified as a possible means of communicating the user’s surroundings to him/her. This, in turn, may encourage interaction with, and interpretation of the space. / Dissertation (MInt(Prof))--University of Pretoria, 2009. / Architecture / unrestricted

Rural accessibility is a pressing issue in many parts of the world. Improved geographical accessibility to basic social service facilities for rural populations is a goal of most governments in developing countries. Development of a trail-based transport system is a key way to improve rural accessibility in mountainous and rugged terrain where trails criss-cross with numerous rivers. The present study focuses on Nepal, a developing country with rural accessibility challenges and a very challenging physical environment. This thesis reviews the existing accessibility patterns in rural areas of Nepal and proposes various approaches for identifying poorly served geographical areas and optimizing of location of additional new trail bridges to provide “best” links to social services. The methodology in this study is based on the concept of the gravity-based spatial interaction and accessibility models. GIS applications are used in different ways, such as in creating, acquiring, integrating spatial and attribute datasets, and spatial analysis and visualization of the output results. Amongst the different types of social services, health care and education centers are considered the most pressing services and hence are the objects of analysis. The main difference between health care service centers and educational facilities is that schools are usually very widespread across the district and serve for the school age population. Health service centers are sparsely and inequitably distributed, however, they serve the whole population at large. The results of the analysis show a fairly clear indication of problems relating to rural transport and access to social service centers in rural Nepal. This is attributed, in part, due to insufficient provision of social service centers and the lack of trail bridges over river crossing locations. The estimated numbers of trips over potential new bridges based on spatial integration modeling provides a basis for prioritization of river crossing locations for allocation of new trail bridges. The poorly served areas across the study district are identified on the basis of the results of the potential accessibility modeling. The trail network nodes with relatively low accessibility values are of prime concern and the subject of contemplation in the trail bridge planning decision-making process.

Rural accessibility is a pressing issue in many parts of the world. Improved geographical accessibility to basic social service facilities for rural populations is a goal of most governments in developing countries. Development of a trail-based transport system is a key way to improve rural accessibility in mountainous and rugged terrain where trails criss-cross with numerous rivers. The present study focuses on Nepal, a developing country with rural accessibility challenges and a very challenging physical environment. This thesis reviews the existing accessibility patterns in rural areas of Nepal and proposes various approaches for identifying poorly served geographical areas and optimizing of location of additional new trail bridges to provide “best” links to social services. The methodology in this study is based on the concept of the gravity-based spatial interaction and accessibility models. GIS applications are used in different ways, such as in creating, acquiring, integrating spatial and attribute datasets, and spatial analysis and visualization of the output results. Amongst the different types of social services, health care and education centers are considered the most pressing services and hence are the objects of analysis. The main difference between health care service centers and educational facilities is that schools are usually very widespread across the district and serve for the school age population. Health service centers are sparsely and inequitably distributed, however, they serve the whole population at large. The results of the analysis show a fairly clear indication of problems relating to rural transport and access to social service centers in rural Nepal. This is attributed, in part, due to insufficient provision of social service centers and the lack of trail bridges over river crossing locations. The estimated numbers of trips over potential new bridges based on spatial integration modeling provides a basis for prioritization of river crossing locations for allocation of new trail bridges. The poorly served areas across the study district are identified on the basis of the results of the potential accessibility modeling. The trail network nodes with relatively low accessibility values are of prime concern and the subject of contemplation in the trail bridge planning decision-making process.

Spatial interaction models of the gravity type are widely used to model origindestination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterise an origin region of a flow, variables that characterise a destination region of a flow, and finally variables that measure the separation between origin and destination regions. This paper outlines and compares two approaches, the spatial econometric and the eigenfunction-based spatial filtering approach, to deal with the issue of spatial autocorrelation among flow residuals. An example using patent citation data that capture knowledge flows across 112 European regions serves to illustrate the application and the comparison of the two approaches.(authors' abstract)

This dissertation examines multiple state and local expenditure categories in the United States to expand understanding of fiscal federalism and spatial interactions among governments. First, the author investigates the relationship between police expenditures and crime rates from a spatial perspective. Both police expenditures and crime rates in one state are found to exhibit a similar pattern to that in neighboring states. Spatial correlation is also detected between police expenditures and crime rates. As police of neighbors in fact deter crime at home, there are positive externalities present among the states. Second, the author conducts new tests on the Leviathan hypothesis, i.e., more competition, smaller government. While cost efficiency is used in place of government size to capture the idea that fiscal decentralization reduces wasteful expenditures, spatial interaction is taken as another measure for decentralization. The hypothesis is supported by some evidence from total, police, highway, and welfare expenditures.

Services provided by public facilities are essential to people's lives and are closely associated with human mobility. Traditionally, public facility access characteristics, such as accessibility, equity issues and service areas, are investigated mainly based on static data (census data, travel surveys and particular records, such as medical records). Currently, the advent of big data offers an unprecedented opportunity to obtain large-scale human mobility data, which can be used to study the characteristics of public facilities from the spatial interaction perspective. Intuitively, spatial interaction characteristics and service areas of different types and sizes of public facilities are different, but how different remains an open question, so we, in turn, examine this question. Based on spatial interaction, we classify public facilities and explore the differences in facilities. In the research, based on spatial interaction extracted from taxi data, we introduce an unsupervised classification method to classify 78 hospitals in 6 districts of Beijing, and the results better reflect the type of hospital. The findings are of great significance for optimizing the spatial configuration of medical facilities or other types of public facilities, allocating public resources reasonably and relieving traffic pressure.

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