Information Theory and Sequences of Land Use: An Application

Robinson, Vincent Β.

doi:10.1111/j.0033-0124.1978.00174.x

Cited by 24 publications

(19 citation statements)

References 7 publications

(4 reference statements)

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“…When a few hundred hectares of land are involved, data sampling is usually applied to limit the workload to scattered plots or transects (Baker, 1989). On the other hand, land use studies using Markov chain models tend to focus on a much larger spatial scale, and involve both urban and non-urban covers (Drewett, 1969;Bourne, 1971;Bell, 1974;Bell and Hinojosa, 1977;Robinson, 1978;Jahan, 1986;Muller and Middleton, 1994). All of these studies use the first-order Markov chain models.…”

Section: Markov Modelling Of Land Use and Land Cover Changesmentioning

confidence: 99%

“…All of these studies use the first-order Markov chain models. The order of the Markov chains has only been formally tested in a few studies (Bell, 1974;Robinson, 1978). Stationarity has usually been assumed, except in a few instances where it has been tested (Bourne, 1971;Bell, 1974;Bell and Hinojosa, 1977).…”

Section: Markov Modelling Of Land Use and Land Cover Changesmentioning

confidence: 99%

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Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling

Weng

2002

Journal of Environmental Management

748

407

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Section: Markov Modelling Of Land Use and Land Cover Changesmentioning

confidence: 99%

Section: Markov Modelling Of Land Use and Land Cover Changesmentioning

confidence: 99%

Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling

Weng

2002

Journal of Environmental Management

748

407

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“…Markov chains have been widely used to model land use changes including both urban and nonurban areas at large spatial scales (Drewett, 1969;Bourne, 1971;Bell, 1974;Robinson, 1978;Jahan, 1986;Muller and Middleton, 1994). Stationary and first-order have usually been assumed except in a few studies where the stationary or the order of Markov chains was tested (Bell, 1974;Robinson, 1978).…”

Section: Markov Analysis Of the Land Use Change Processmentioning

confidence: 99%

“…Stationary and first-order have usually been assumed except in a few studies where the stationary or the order of Markov chains was tested (Bell, 1974;Robinson, 1978). This paper assumed land use change as a finite first-order Markov chain with stationary transition probabilities, and different categories were the states of a chain, and both time homogeneity (time stationary) and Markov property (time independence) were tested using Pearson χ 2 goodness-of-fit tests.…”

Section: Markov Analysis Of the Land Use Change Processmentioning

confidence: 99%

Monitoring and predicting land use change in Beijing using remote sensing and GIS

Wu¹,

Li²,

Wang³

et al. 2006

Landscape and Urban Planning

331

170

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Rapid land use change has taken place in many mega cities of China such as Beijing over the past two decades. In this paper, land use change dynamics were investigated by the combined use of satellite remote sensing, geographic information systems (GIS). The results indicated that there had been a notable and uneven urban growth and a major loss of cropland loss between 1986 and 2001. Most of the urban growth and loss of agriculture land occurred in inner and outer suburbs. Land use change was projected for the next 20 years using Markov chains and regression analyses. The further integration of remote sensing and GIS technologies with Markov model and regression model was found to be useful for describing, analyzing and predicting the process of land use change.

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“…The only large gain in information occurs when considering sequences of length 2. Along the lines set forth in Robinson (1978), the information graphs exhibits a well-defined elbow indicating the appropriateness of a first-order model. The graph suggests that information gains are not large when considering sequences of lengths 3, 4, and 5, and that little information is gained by speclfying a model of an order greater than one.…”

Section: Resultsmentioning

confidence: 96%

On the Issue of Orderedness in Social Accounting Models of Residential Change

Robinson

Utano

1980

Geographical Analysis

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Residential Change in a Social Accounting FrameworkParticular attention has been devoted to changes occurring within the existing housing stock of a metropolitan area, since the standing stock provides the physical space for urban activities. From the urban planner's point of view, the important questions about neighborhood change deal directly with compositional changes in occupancy of the housing stock. In this manner, the planner is more concerned with identifying the characteristics of households occupying a neighborhood at a given time period rather than monitoring the movements of individual households whose destinations may lie outside the neighborhood. Therefore, by focusing on a set of dwelling units with their attendant household composition, modeling endeavors accounting for the shifts in the characteristics of a sequence of household types by dwelling unit would be invaluable to planners as a means of discerning household compositional shifts in the housing stock (Moore and Gale 1979).Social accounting models of residential changes have been endorsed recently in lieu of conventional microeconomic attempts at uncovering the exchange mechanisms between households and dwelling units (Byler and Gale 1978; Moore and Gale 1979;Stone 1975) The latter's difficulty with (a) identifying extremely localized pockets of population movement, (b) providing current and reliable predictions on household/dwelling unit composition in housing submarkets, and (c) formulating the housing process solely within a market-based model reflect the foremost factors for this shift in modeling attempts of the housing process. In its primitive form, accounting models of the housing process represent an extension of the "models of data" concept proposed by Suppes (1962) and elaborated by Moore and Gale (1974). These models are useful for monitoring the sequence of states through which elements of the system pass. For example, such models may be used to "account" for the spatial pattern of change in (a) housing stock composition caused by construction, demolition, or other types of structural modification; (b) household composition due to migration, formulation, or other types of consumer household change; and (c) the matching process between the two elements.General modeling focus on these activities has been structured within a contingency-table formulation in which the table represents longitudinal time sequences of household types occupying specific classes of dwelling units. These tables may be multidimensional in form where both elements, household and dwelling unit type, are represented by a set of attributes depicting various properties of the two elements. Although this contingency-table framework has been used for housing inventory and descriptive purposes, more parsimonious "accounting" models have been proposed.

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Information Theory and Sequences of Land Use: An Application

Cited by 24 publications

References 7 publications

Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling

Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling

Monitoring and predicting land use change in Beijing using remote sensing and GIS

On the Issue of Orderedness in Social Accounting Models of Residential Change

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