Skip to the content

Simulating urban growth processes incorporating a potential model with spatial metrics

Kong, Fanhua, Yin, Haiwei, Nakagoshi, Nobukazu and James, Philip 2012, 'Simulating urban growth processes incorporating a potential model with spatial metrics' , Ecological Indicators, 20 , pp. 82-91.

[img] PDF - Published Version
Restricted to Repository staff only

Download (2966kB) | Request a copy

    Abstract

    Urbanization is one phenomena that drives land use pattern change. Persistent rapid urbanization is associated with depletion of natural resources and worsening conditions in the urban environment. Monitoring urban development is, therefore, an absolute necessity in order to assure sustainable cities in the future. The main objective of this paper is to develop and apply an urban growth potential model incorporating spatial metrics. The model has been tested in Jinan City, China. Firstly, two satellite images (1989 and 2004 SPOT) were used to extract the land-cover. A general land use spatial pattern analysis, based on landscape metrics and a transformation matrix analysis, was conducted. Secondly, a moving window method was used to identify and capture the urbanization process through the PLAND landscape metric. The remote satellite data have been further processed:first to produce an initial state of the land-cover surface, and second to perform a time-series analysis and to assess the potential accuracy of the model application. In the second step, the calibrated model was used to predict the location of the urban growth over 16 years (2004–2020). The results indicated there will be a significant land use change until 2020. However, the spatial distribution of the potential growth areas is not homogenous. The study has confirmed the usefulness of a growth potential model incorporating the moving window method to predict urban growth trends and examining the impacts of urban development on natural resources. The results can provide decision support documents for urban planners and stakeholders with spatially explicit information for future planning and monitoring plans.

    Item Type: Article
    Themes: Built and Human Environment
    Schools: Colleges and Schools > College of Science & Technology
    Colleges and Schools > College of Science & Technology > School of Environment and Life Sciences
    Colleges and Schools > College of Science & Technology > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
    Journal or Publication Title: Ecological Indicators
    Publisher: Elsevier
    Refereed: Yes
    ISSN: 1470-160X
    Related URLs:
    Depositing User: Professor Philip James
    Date Deposited: 07 Mar 2012 10:24
    Last Modified: 23 Sep 2013 15:35
    URI: http://usir.salford.ac.uk/id/eprint/20707

    Document Downloads

    More statistics for this item...

    Actions (login required)

    Edit record (repository staff only)