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Books on the topic 'Dynamic spatial model'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Krugman, Paul R. A dynamic spatial model. National Bureau of Economic Research, 1992.

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2

Knapp, Keith. A dynamic spatial equilibrium model of the California alfalfa market. Giannini Foundation of Agricultural Economics, University of California, 1990.

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3

Karssenberg, Derek. Building dynamic spatial environmental models. Koninklijk Nederlands Aardrijkskundig Genootschap, 2002.

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4

Nijkamp, Peter. Dynamics of generalised spatial interaction models. Vrije Universiteit, Faculteit det Economische Wetenschappen, 1986.

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5

Nijkamp, Peter. Dynamics of generalised spatial interaction models. Victoria University of Wellington, Department of Economics, 1985.

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6

Sikdar, P. K. Spatial interaction models in hybrid-dynamic framework. UWIST. Department of Town Planning, 1986.

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7

Michael, Sonis, ed. Chaos and socio-spatial dynamics. Springer-Verlag, 1990.

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8

Westervelt, James D., and Gordon L. Cohen, eds. Ecologist-Developed Spatially-Explicit Dynamic Landscape Models. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1257-1.

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9

Hamermesh, Daniel S. Spatial and temporal aggregation in the dynamics of labor demand. National Bureau of Economic Research, 1992.

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10

Nijkamp, Peter. Spatial interaction and input-output models: A dynamic stochastic multi-objective framework. Vrije Universiteit, Faculteit der Economische Wetenschappen en Econometrie, 1987.

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11

Geospatial analysis and modelling of urban structure and dynamics. Springer, 2010.

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12

Cumming, Steven G. A grid-based spatial model of forest dynamics applied to the boreal mixedwood region. Sustainable Forest Management Network, 1998.

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13

W. P. A. van Deursen. Geographical information systems and dynamic models: Development and application of a prototype spatial modelling language. Koninklijk Nederlands Aardrijkskundig Genntschap/Faculteit Ruimtelijke Wetenschappen Universiteit Utrecht, 1995.

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14

Nigh, Gordon Donald. Identifying and modelling the spatial distribution dynamics of regenerating lodgepole pine. British Columbia, Ministry of Forests, Research Program, 1997.

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15

Nijkamp, Peter. A synthesis between macro and micro models in spatial interaction analysis: With special reference to dynamics. Vrije Universiteit, Faculteit der Economische Wetenschappen, 1986.

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16

Surkova, Galina. Atmospheric chemistry. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1079840.

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The textbook contains material corresponding to the course of lectures on atmospheric chemistry prepared for students studying meteorology and climatology. The basic concepts of atmospheric chemistry are given, its gaseous components, as well as aerosols and chemical processes related to their life cycles, which are important from the point of view of the formation of the radiation, temperature and dynamic regime of the atmosphere, as well as its pollution, are considered. The main regularities of the transport of impurities in the atmosphere and the role of processes of different spatial and

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17

Furtado, Bernardo Alves. Modeling social heterogeneity, neighborhoods and local influences on urban real estate prices: Spatial dynamic analyses in the Belo Horizonte metropolitan area, Brazil. Koninklijk Nederlands Aardrijkskundig Genootschap, 2009.

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18

Modeling social heterogeneity, neighborhoods and local influences on urban real estate prices: Spatial dynamic analyses in the Belo Horizonte metropolitan area, Brazil. Koninklijk Nederlands Aardrijkskundig Genootschap, 2009.

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19

Mazo, Aleksandr, and Konstantin Potashev. The superelements. Modeling of oil fields development. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1043236.

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This monograph presents the basics of super-element modeling method of two-phase fluid flows occurring during the development of oil reservoir. The simulation is performed in two stages to reduce the spatial and temporal scales of the studied processes. In the first stage of modeling of development of oil deposits built long-term (for decades) the model of the global dynamics of the flooding on the super-element computational grid with a step equal to the average distance between wells (200-500 m). Local filtration flow, caused by the action of geological and technical methods of stimulation,

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20

Geographical population analysis: Tools for the analysis of biodiversity. Blackwell Scientific Publications, 1994.

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21

Biller, Dan, Luis Andres, and David Cuberes. A Dynamic Spatial Model of Rural-Urban Transformation with Public Goods. The World Bank, 2014. http://dx.doi.org/10.1596/1813-9450-7051.

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22

Schmidt, Alexandra, Jennifer Hoeting, João Batista M. Pereira, and Pedro Paulo Vieira. Mapping malaria in the Amazon rain forest: A spatio-temporal mixture model. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.5.

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This article focuses on the use of a spatio-temporal mixture model for mapping malaria in the Amazon rain forest. The spatio-temporal model was developed to study malaria outbreaks over a four year period in the state of Amazonas, Brazil. The goal is to predict malaria counts for unobserved municipalities and future time periods with the aid of a free-form spatial covariance structure and a methodology that allows temporal prediction and spatial interpolation for outbreaks of malaria over time. The proposed structure is unique in that it is not a distance- or neighbourhood-based covariance mod

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23

Cavanagh, Patrick, Lorella Battelli, and Alex Holcombe. Dynamic Attention. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.016.

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The authors review how attention helps track and process dynamic events, selecting and integrating information across time and space to produce a continuing identity for a moving, changing target. Rather than a fixed ‘spotlight’ that helps identify a static target, attention needs a mobile window or ‘pointer’ to track a moving target, picking up pieces of evidence along the way to determine not just what the target is, but what it is doing. Behavioural studies show that this dynamic version of attention is model-based, using familiar trajectories to help identify a target and to guide encoding

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24

Low Choy, Samantha, Justine Murray, Allan James, and Kerrie Mengersen. Combining monitoring data and computer model output in assessing environmental exposure. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.18.

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This article discusses an approach that combines monitoring data and computer model outputs for environmental exposure assessment. It describes the application of Bayesian data fusion methods using spatial Gaussian process models in studies of weekly wet deposition data for 2001 from 120 sites monitored by the US National Atmospheric Deposition Program (NADP) in the eastern United States. The article first provides an overview of environmental computer models, with a focus on the CMAQ (Community Multi-Scale Air Quality) Eta forecast model, before considering some algorithmic and pseudo-statist

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25

Dendrinos, Dimitrios S., and Michael Sonis. Chaos and Socio-Spatial Dynamics. Springer, 2012.

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26

A, Levin Simon, Powell T. M, and Steele John H. 1926-, eds. Patch dynamics. Springer-Verlag, 1993.

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27

Patch Dynamics. Springer, 2012.

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28

Ecologistdeveloped Spatially Explicity Dynamic Landscape Models. Springer, 2012.

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29

Aura, Reggiani, and Nijkamp Peter, eds. Spatial dynamics, networks and modelling. Edward Elgar, 2006.

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30

Westervelt, James D., and Gordon L. Cohen. Ecologist-Developed Spatially-Explicit Dynamic Landscape Models. Springer, 2014.

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31

Hauer, J. Urban Dynamics and Spatial Choice Behaviour. Ingramcontent, 2011.

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32

Urban dynamics and spatial choice behaviour. Kluwer Academic, 1989.

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33

1967-, Bascompte Jordi, and Solé Ricard V. 1962-, eds. Modeling spatiotemporal dynamics in ecology. Springer, 1998.

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34

(Editor), Massimo Gastaldi, and Aura Reggiani (Editor), eds. New Analytical Advances in Transportation and Spatial Dynamics. Ashgate Pub Ltd, 2002.

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35

Baker, Robert G. V. Dynamic Trip Modelling. Springer, 2008.

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36

Nguyen, Linh Thu. A spatial model for studying population dynamics of the California Mojave Desert tortoise. 1999.

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37

Nackoney, Janet, Jena Hickey, David Williams, Charly Facheux, Takeshi Furuichi, and Jef Dupain. Geospatial information informs bonobo conservation efforts. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198728511.003.0017.

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The endangered bonobo (Pan paniscus), endemic to the Democratic Republic of Congo (DRC), is threatened by hunting and habitat loss. Two recent wars and ongoing conflicts in the DRC greatly challenge conservation efforts. This chapter demonstrates how spatial data and maps are used for monitoring threats and prioritizing locations to safeguard bonobo habitat, including identifying areas of highest conservation value to bonobos and collaboratively mapping community-based natural resource management (CBNRM) zones for reducing deforestation in key corridor areas. We also highlight the development

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38

Keilbach, Max C. Spatial Knowledge Spillovers and the Dynamics of Agglomeration and Regional Growth. Physica-Verlag Heidelberg, 2000.

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39

(Editor), Ulf Dieckmann, Richard Law (Editor), and Johan A. J. Metz (Editor), eds. The Geometry of Ecological Interactions: Simplifying Spatial Complexity (Cambridge Studies in Adaptive Dynamics). Cambridge University Press, 2005.

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40

Moulin, Bernard, Jianhong Wu, and Dongmei Chen. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases. Wiley & Sons, Incorporated, John, 2014.

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41

Moulin, Bernard, Jianhong Wu, and Dongmei Chen. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases. Wiley & Sons, Incorporated, John, 2014.

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42

Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases. Wiley & Sons, Limited, John, 2015.

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43

Islam, Kazi mohammed Saiful. Spatial dynamic queueing models for the daily deployment of airtankers for forest fire control. 1998.

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44

Jacobsen, Dean, and Olivier Dangles. Community dynamics in highland watersheds. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198736868.003.0006.

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Chapter 6 presents the interaction between space and time in determining the organization of natural communities in high altitude heterogeneous waterscapes. After explaining why high altitude waters represent suitable models for examining metacommunity organization, the chapter focuses on dispersal—a central process to allow colonization and establishment of populations in remote localities and to counter local extinctions. Community organization patterns are then described for a variety of organisms living in high altitude waters, from microbes to invertebrates to fish and birds. These patter

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45

Spatial Dynamics, Networks And Modelling (New Horizons in Regional Science Series). Edward Elgar Publishing, 2006.

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46

Baker, Robert G. V. Dynamic Trip Modelling: From Shopping Centres to the Internet (GeoJournal Library). Springer, 2006.

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47

Gao, Yanhong, and Deliang Chen. Modeling of Regional Climate over the Tibetan Plateau. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.591.

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The modeling of climate over the Tibetan Plateau (TP) started with the introduction of Global Climate Models (GCMs) in the 1950s. Since then, GCMs have been developed to simulate atmospheric dynamics and eventually the climate system. As the highest and widest international plateau, the strong orographic forcing caused by the TP and its impact on general circulation rather than regional climate was initially the focus. Later, with growing awareness of the incapability of GCMs to depict regional or local-scale atmospheric processes over the heterogeneous ground, coupled with the importance of t

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48

A, Kohler Timothy, and Gumerman George J, eds. Dynamics in human and primate societies: Agent-based modeling of social and spatial processes. Oxford University Press, 2000.

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49

Anderson, James A. Loose Ends. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0017.

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This chapter presents some ideas about Ersatz Brain Theory, which generalizes models presented in the book. It is based on three equal components: computation, cognition, and neuroscience. In the Ersatz Brain, the basic computing elements are locally interconnected groups of neurons, for example, cortical columns, and not single neurons. Columns are more powerful than neurons alone because of the potential for selectivity and reliability. A “network of networks” modular architecture is formed from interconnected groups. Response selection emerges from the stability properties of dynamical syst

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50

Hassell, Michael P. The Spatial and Temporal Dynamics of Host-Parasitoid Interactions (Oxford Series in Ecology and Evolution). Oxford University Press, USA, 2000.

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