The Experts below are selected from a list of 423615 Experts worldwide ranked by ideXlab platform
Sandy Dallerba - One of the best experts on this subject based on the ideXlab platform.
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Spatial distribution of employment in hermosillo 1999 2004
Urban Studies, 2012Co-Authors: Liz Rodriguezgamez, Sandy DallerbaAbstract:While the suburbanisation process has been well documented in some large cities of several developed countries, much less attention has been devoted to the case of small and middle-sized cities in developing countries. This article focuses on an exploratory Spatial Data Analysis to investigate the location of the central business district (CBD) and other employment centres in Hermosillo, Mexico. The results reveal the significant presence of Spatial dependence and Spatial heterogeneity, although their extent varies with the sector under study. These Spatial effects take the form of a persistent cluster of high values of employment around the historical district of the city shaping a huge CBD, although a sub-centre of high values emerges to the south and to the north-west of the CBD in 2004. Overall, Hermosillo is still characterised by a traditional monocentric model, but the role of its CBD has changed.
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distribution of regional income and regional funds in europe 1989 1999 an exploratory Spatial Data Analysis
Annals of Regional Science, 2005Co-Authors: Sandy DallerbaAbstract:The efforts of the European Commission to reduce regional inequalities over its territory continue to attract the attention of researchers. The purpose of this paper is to perform an exploratory investigation of the relationship between the Spatial distribution of regional income and of regional development funds among 145 European regions over 1989–1999. Using a set of tools of Spatial statistics, we first detect the presence of global and local Spatial autocorrelation in the distribution of regional per capita incomes, traducing that rich (poor) regions tend to be clustered close to other rich (poor) regions, and in the distribution of regional growth rate and regional funds. Second, the results of LISA statistics conclude to the presence of Spatial heterogeneity in the form of two Spatial clusters of rich and poor regions over the decade, highlighting the persistence of a significant core-periphery pattern among European regions. Finally, an exploratory Analysis reveals a negative correlation between growth and initial income, that tends to indicate β-convergence. A positive relationship between regional growth and structural funds is identified among the significant results as well. Only Andalucia, Galicia and Sterea Ellada show atypical linkages. These results suggest that further research should include Spatial effects and the distribution of regional funds in the Spatial econometric estimation of regional convergence in Europe.
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distribution of regional income and regional funds in europe 1989 1999 an exploratory Spatial Data Analysis
MPRA Paper, 2003Co-Authors: Sandy DallerbaAbstract:The efforts of the European Commission to reduce regional inequalities over its territory continues to attract the attention of researchers. The purpose of this paper is to perform an exploratory investigation of the relationship between the Spatial distribution of regional income and of regional development funds among 145 European regions over 1989-1999. Using a set of tools of Spatial statistics, we first detect the presence of global and local Spatial autocorrelation in the distribution of regional per capita incomes, traducing that rich (poor) regions tend to be clustered close to other rich (poor) regions, and in the distribution of regional growth rate and regional funds. Second, the results of LISA statistics conclude to the presence of Spatial heterogeneity in the form of two Spatial clusters of rich and poor regions over the decade, highlighting the persistence of a significant core-periphery pattern among European regions. Finally, an exploratory Analysis reveals a negative correlation between growth and initial income, that tends to indicate beta-convergence. A positive relationship between regional growth and structural funds is identified among the significant results as well. Only Andalucia, Galicia and Sterea Ellada show atypical linkages. These results suggest that further research should include Spatial effects and the distribution of regional funds in the Spatial econometric estimation of regional convergence in Europe.
Trevor C Bailey - One of the best experts on this subject based on the ideXlab platform.
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interactive Spatial Data Analysis in medical geography
Social Science & Medicine, 1996Co-Authors: Anthony C. Gatrell, Trevor C BaileyAbstract:Interactive Spatial Data Analysis involves the use of software environments that permit the visualization, exploration and, perhaps, modelling of geographically-referenced Data. Such systems are of obvious value in epidemiological research, both of an environmental and geographical nature. There is an increasing number of such software environments available on a variety of platforms and operating systems. This paper considers the use of the proprietary Geographical Information System, ARC/INFO, in a Spatial Analysis context, showing how the Spatial analytic tools that may be added to it can be exploited by geographical epidemiologists; such tools include those for modelling possible raised incidence of disease around suspected sources of pollution. The paper also reviews the use of systems such as S-Plus and XLISP-STAT, statistical programming environments to which Spatial Analysis functions or libraries may be added. The use of INFO-MAP, a system designed to aid in the teaching of interactive Spatial Data Analysis, is also highlighted. The various software environments are illustrated with reference to examples concerned with: clustering of childhood leukaemia in part of Lancashire, England; Burkitt's lymphoma in Uganda; larynx cancer in Lancashire; and childhood mortality in Auckland, New Zealand.
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interactive Spatial Data Analysis
1995Co-Authors: Trevor C Bailey, Anthony C. GatrellAbstract:A: Introduction 1. Spatial Data Analysis 2. Computers and Spatial Data Analysis B: The Analysis of Data Associated with Points 3. Methods Relating to Point Patterns 4. Methods Relating to Marked Point Patterns 5. Methods Relating to a Continuously Varying Attribute Sampled at Points C: The Analysis of Data Associated with Areas 6. Univariate Analysis of Area Data 7. Analysis of Relationships Between Attributes of Areas 8. Multivariate Methods of Area Data D: The Analysis of Data Associated with Lines 9. Network Analysis 10. Spatial Interaction Models
Anthony C. Gatrell - One of the best experts on this subject based on the ideXlab platform.
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interactive Spatial Data Analysis in medical geography
Social Science & Medicine, 1996Co-Authors: Anthony C. Gatrell, Trevor C BaileyAbstract:Interactive Spatial Data Analysis involves the use of software environments that permit the visualization, exploration and, perhaps, modelling of geographically-referenced Data. Such systems are of obvious value in epidemiological research, both of an environmental and geographical nature. There is an increasing number of such software environments available on a variety of platforms and operating systems. This paper considers the use of the proprietary Geographical Information System, ARC/INFO, in a Spatial Analysis context, showing how the Spatial analytic tools that may be added to it can be exploited by geographical epidemiologists; such tools include those for modelling possible raised incidence of disease around suspected sources of pollution. The paper also reviews the use of systems such as S-Plus and XLISP-STAT, statistical programming environments to which Spatial Analysis functions or libraries may be added. The use of INFO-MAP, a system designed to aid in the teaching of interactive Spatial Data Analysis, is also highlighted. The various software environments are illustrated with reference to examples concerned with: clustering of childhood leukaemia in part of Lancashire, England; Burkitt's lymphoma in Uganda; larynx cancer in Lancashire; and childhood mortality in Auckland, New Zealand.
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interactive Spatial Data Analysis
1995Co-Authors: Trevor C Bailey, Anthony C. GatrellAbstract:A: Introduction 1. Spatial Data Analysis 2. Computers and Spatial Data Analysis B: The Analysis of Data Associated with Points 3. Methods Relating to Point Patterns 4. Methods Relating to Marked Point Patterns 5. Methods Relating to a Continuously Varying Attribute Sampled at Points C: The Analysis of Data Associated with Areas 6. Univariate Analysis of Area Data 7. Analysis of Relationships Between Attributes of Areas 8. Multivariate Methods of Area Data D: The Analysis of Data Associated with Lines 9. Network Analysis 10. Spatial Interaction Models
Younes Noorollahi - One of the best experts on this subject based on the ideXlab platform.
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thermo economic modeling and gis based Spatial Data Analysis of ground source heat pump systems for regional shallow geothermal mapping
Renewable & Sustainable Energy Reviews, 2017Co-Authors: Younes Noorollahi, Hamidreza Gholami Arjenaki, Roghayeh GhasempourAbstract:The increasing interest in ground source heat pump system (GSHP) as well as its high initial investment cost accentuate the necessity for an assessment tool which supports policy makers with decisions regarding technology development and subsidization. Since the performance of a geothermal heat pump system depends strongly on parameters such as geological and climate conditions, a regional-scale energy-economic mapping by Spatial Analysis was accomplished for priority assessment of each region which is to be subsidized. The procedure includes numerical modeling and optimization of GSHP systems by Genetic Algorithm (GA), regional heating/cooling design load estimation and Spatial Data Analysis to achieve an economic-based map for 234 cities in Iran. Moreover, Spatial interpolation was carried out in order to achieve a statistical surface map for the entire country. For the first time, Iran's regional shallow geothermal map was accurately presented along with other geographical maps including air and earth surface’s mean temperature, heating/cooling loads, GSHP required operating hours and Iran's climatology. Total Annual Cost (TAC) values were categorized into five equal ranges from CA (the highest priority class) to CE (the lowest priority class) which highlight the convenient regions for shallow geothermal energy use. Finally, Iran’s provinces were sorted according to TAC weighted average values.
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Spatial Data Analysis for exploration of regional scale geothermal resources
Journal of Volcanology and Geothermal Research, 2013Co-Authors: Majid Kiavarz Moghaddam, Younes Noorollahi, Farhad Samadzadegan, Mohammad Ali Sharifi, Ryuichi ItoiAbstract:Abstract Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry Analysis as a Spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as Spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience Data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry Analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the Spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the Spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly Spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical Data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m 2 . In general, geochemical and geophysical Data were better evidence layers than geological Data for exploring geothermal resources. The Spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.
Ryuichi Itoi - One of the best experts on this subject based on the ideXlab platform.
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Spatial Data Analysis for exploration of regional scale geothermal resources
Journal of Volcanology and Geothermal Research, 2013Co-Authors: Majid Kiavarz Moghaddam, Younes Noorollahi, Farhad Samadzadegan, Mohammad Ali Sharifi, Ryuichi ItoiAbstract:Abstract Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry Analysis as a Spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as Spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience Data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry Analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the Spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the Spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly Spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical Data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m 2 . In general, geochemical and geophysical Data were better evidence layers than geological Data for exploring geothermal resources. The Spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.