Urban sprawl: metrics, dynamics and modelling using GIS

Sudhira, HS; Ramachandra, T. V.; Jagadish, K. S.

doi:10.1016/j.jag.2003.08.002

Cited by 599 publications

(323 citation statements)

References 7 publications

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“…It is the basic unit of landscape change. In previous research, GIS along with remote sensing data can help in analyzing the growth, pattern and extent of sprawl (Sudhira et al, 2004). In this study, we use GIS to visualize the three urban growth types.…”

Section: Identify Three Urban Growth Types Of Infilling Edge-expansimentioning

confidence: 99%

Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

Sun¹,

Wu²,

Lv³

et al. 2013

International Journal of Applied Earth Observation and Geoinfor

188

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Section: Identify Three Urban Growth Types Of Infilling Edge-expansimentioning

confidence: 99%

Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

Sun¹,

Wu²,

Lv³

et al. 2013

International Journal of Applied Earth Observation and Geoinfor

188

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“…Although the images have varied quality and product, it was ensured that they have the same pixel level and enhanced spatial resolution, textural, and structural details. ArcGIS (v. 10.3) software, was used for geometric correction, land use classification [SUDHIRA et al 2004] and accuracy assessment [FOODY 2002]. The historical and current base maps of the study area couple with field data were used for identification of targeted five land-use classes.…”

Section: Land Use Classification and Predictionmentioning

confidence: 99%

Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model

Bello

Hashim

Haniffah

2017

Journal of Water and Land Development

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Abundant rainfall areas promote sediment yield at both sub-watershed and watershed scale due to soil erosion and increase siltation of river channel, but it can be curtailed through planned urbanization. The urbanization of Skudai watershed is analysed from historical and future perspective. A GIS-based model (Hydrological Simulation Programme-FORTRAN-HSPF) is used to modelled sediment flow using basin-wide simulation, and the output result is utilized in evaluating sediment yield reduction due to increased urbanization by swapping multiple temporal land-use of decadent time-steps. The analysis indicates that sediment yield reduces with increase urban built-up and decrease forest and agricultural land. An estimated 12 400 tons of sediment will be reduced for every 27% increase in built-up areas under high rainfall condition and 1 490 tons at low rainfall. The sensitivity analysis of land-use classes shows that built-up, forest and barren are more sensitive to sediment yield reduction compared to wetland and agricultural land at both high and low rainfall. The result of the study suggests that increased urbanization reduced sediment yield in proportion to the rainfall condition and can be used as an alternative approach for soil conservation at watershed scale independent of climate condition.

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“…The more compact of the structures and the built up areas is closer to zero entropy value, while the closer to the logarithm number of zones is the more dispersed the region [7] [9].…”

Section: Introductionmentioning

confidence: 97%

The Use of GIS, Remote Sensing and Shannon’s Entropy Statistical Techniques to Analyze and Monitor the Spatial and Temporal Patterns of Urbanization and Sprawl in Zarqa City, Jordan

Mashagbah¹

2016

JGIS

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Urban sprawl: metrics, dynamics and modelling using GIS

Cited by 599 publications

References 7 publications

Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model

The Use of GIS, Remote Sensing and Shannon’s Entropy Statistical Techniques to Analyze and Monitor the Spatial and Temporal Patterns of Urbanization and Sprawl in Zarqa City, Jordan

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