Probability mapping of land use change: A GIS interface for visualizing transition probabilities

Logsdon, Miles G.; Bell, Earl J.; Westerlund, Frank

doi:10.1016/s0198-9715(97)00004-5

Cited by 34 publications

(17 citation statements)

References 2 publications

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“…Markov model will describe LU/LC change from one period to another and use this as the basis to project future changes. This is achieved by developing a transition probability matrix of LU/LC change from time one to time two, which shows the nature of change while still serving as the basis for projecting to a later time period (Logsdon 1996). Markov model provided a simple methodology and by which a dynamic system could be dissected and examined (Muller & Middleton 1994;Dongjie et al 2008;Huang et al 2008;Dadhich & Hanaoka 2010;Zhang et al 2011).…”

Section: Markov Model In Lu/lc Changementioning

confidence: 99%

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Land use change modelling using a Markov model and remote sensing

Kumar¹,

Radhakrishnan

Mathew

2013

Geomatics, Natural Hazards and Risk

174

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Land-use/land-cover (LU/LC) change is an important component of global environmental change. The need to understand LU/LC change is essential for regional development and land use management towards sustainable development. To understand LU/LC change, the different LU/LC categories and their spatial as well as temporal variability in Tiruchirappalli city has been studied over a period of eight years (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006), using the analysis of Indian Remote Sensing Satellite (IRS) images. In this, an attempt was made to adopt Markov model for obtaining and understanding LU/LC dynamics. Model performance was evaluated between the empirical LU/LC map extracted from CARTOSAT-1 PAN image and the simulated LU/LC map obtained from the Markov model. The future landscape distribution in the year 2014 and 2022 was derived using a Markov model. This result shows that Markov model and geospatial technology together are able to effectively capture the spatio-temporal trend in the landscape pattern associated with urbanization in this region.

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Section: Markov Model In Lu/lc Changementioning

confidence: 99%

“…An attempt was also made to obtain simulated LU/LC for the year 2022 using a Markov model. The model is the spatial transition based whereby transition areas and probabilities are generated from two time series LU/LC maps in order to predict changes at a specified time in the future (Logsdon et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Land use change modelling using a Markov model and remote sensing

Kumar¹,

Radhakrishnan

Mathew

2013

Geomatics, Natural Hazards and Risk

174

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“…Landsat ETMþ provides panchromatic data with 15 m spatial resolution (Yang and Lo, 2002). One major difficulty is the relatively short time span of the archived imagery (Logsdon et al, 1996). Post-classification comparison is the most commonly used quantitative method of change detection.…”

Section: Identification Of Lulcmentioning

confidence: 99%

Land‐use change and urbanization of Adana, Turkey

2003

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This study analyses land-use/land-cover (LULC) changes in Adana city, Turkey, using satellite data of 1984 and 2000. Study of the expansion of the city over adjacent agricultural fields and semi-natural areas was the major focus. The satellite images were classified using supervised classification prior to comparison of LULC on two different dates. The change map was produced by pixel-to-pixel comparison of the classified images. Urban and built-up area increased by a factor of 2Á07 during the 16 years; about 30 per cent on agricultural land and 70 per cent on previously semi-natural land. Permanent immigration and urban development strategies were the main driving forces. Some policy perspectives are also given.

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“…One of the major difficulties of using satellite imagery is the relatively short-time span of archived imagery (Logsdon et al, 1996). Landsat program, the earliest attempt aimed to establish and execute a data acquisition strategy that ensures repetitive acquisition of observations over the Earth's land mass, coastal boundaries, etc., has provided huge amount of data for monitoring changes in the Earth's land surface since 1972 (USGS, 2003).…”

Section: Resultsmentioning

confidence: 99%

Monitoring Urbanization of Iskenderun, Turkey, and its Negative Implications

Doygun

Alphan

2006

Environ Monit Assess

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This study aimed to analyze long-term urban land use (LU) change and its negative implications on the coastal environment of Iskenderun, Turkey. Information on urban LU change for the 144-year period between 1858 and 2002 was extracted from a historic city plan, black-white monoscopic aerial photographs, and Landsat ETM+ imagery. According to the results, areal extent of urban areas has increased approximately 40 times during the past 144 years. The population growth as a result of industrial developments and permanent migration was main driving force to the urbanization. Environmental problems that resulted from rapid development in the region such as air, water and soil pollution were highlighted and some recommendations were made in the light of qualitative and quantitative information on the urbanization and its negative consequences.

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Probability mapping of land use change: A GIS interface for visualizing transition probabilities

Cited by 34 publications

References 2 publications

Land use change modelling using a Markov model and remote sensing

Land use change modelling using a Markov model and remote sensing

Land‐use change and urbanization of Adana, Turkey

Monitoring Urbanization of Iskenderun, Turkey, and its Negative Implications

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