Urban Growth and Clustering Surakarta Peri-Urban Area

Muhamad Rizal Fernandita Pamungkas; Anang Wahyu Sejati

doi:10.14710/ijpd.9.1.%p

DOI: https://doi.org/10.14710/ijpd.9.1.%25p

Urban Growth and Clustering Surakarta Peri-Urban Area

Muhamad Rizal Fernandita Pamungkas - Smart City Infromation Systems, Universitas Tuna Pembangunan, Surakarta, Indonesia, Indonesia

*Anang Wahyu Sejati - Department of Urban and Regional Planning, Faculty of Engineering, Universitas Diponegoro, Semarang, Indonesia, Indonesia

Published: 28 Feb 2024.

Editor(s): Jawoto Setyono

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

BibTex Citation Data :

@article{IJPD27054,
    author = {Muhamad Pamungkas and Anang Sejati},
    title = {Urban Growth and Clustering Surakarta Peri-Urban Area},
    journal = {The Indonesian Journal of Planning and Development},
  volume = {9},
    number = {1},
    year = {2024},
    keywords = {cluster area; remote sensing; urban growth},
    abstract = { The high rate of urbanization in the world has an impact on the urban growth that extend to urban fringe areas or commonly called suburbanization. Surakarta City is one of the PKN in Central Java Province which serves the surrounding area. During its development, Surakarta City was transformed into a main city that served its suburbs. Limited land in cities causes urban activity to spread to peri-urban areas.  As a result, there have been many changes in agricultural land into built-up areas that threaten the food resilience. Research on urban growth is not only calculating changes in area over a certain period of time, but needs to pay attention to the cluster area. This study aims to monitoring urban growth and clustering of the Surakarta peri-urban area. This study used remote sensing methods to detect land use change and cluster analysis to classify peri-urban areas based on suburbanization characteristics. This research used a random forest supervised classification method to determine the type of land cover and a non-hierarchical method in clustering its peri-urban areas. The results showed that for 18 years, there was an increase in the area of built land covering an area of 4248 hectares. It is predicted that the peri-urban area of Surakarta will continue to grow. In 2036, 9024 hectares will be built in the peri-urban area of Surakarta. In the cluster analysis test, 3 clusters were produced including clusters with low, medium, and high suburbanization characteristics. },
   issn = {2442-983X},  doi = {10.14710/ijpd.9.1.%p},
    url = {https://ejournal2.undip.ac.id/index.php/ijpd/article/view/27054}
}

Citation Format:

Abstract

The high rate of urbanization in the world has an impact on the urban growth that extend to urban fringe areas or commonly called suburbanization. Surakarta City is one of the PKN in Central Java Province which serves the surrounding area. During its development, Surakarta City was transformed into a main city that served its suburbs. Limited land in cities causes urban activity to spread to peri-urban areas. As a result, there have been many changes in agricultural land into built-up areas that threaten the food resilience. Research on urban growth is not only calculating changes in area over a certain period of time, but needs to pay attention to the cluster area. This study aims to monitoring urban growth and clustering of the Surakarta peri-urban area. This study used remote sensing methods to detect land use change and cluster analysis to classify peri-urban areas based on suburbanization characteristics. This research used a random forest supervised classification method to determine the type of land cover and a non-hierarchical method in clustering its peri-urban areas. The results showed that for 18 years, there was an increase in the area of built land covering an area of 4248 hectares. It is predicted that the peri-urban area of Surakarta will continue to grow. In 2036, 9024 hectares will be built in the peri-urban area of Surakarta. In the cluster analysis test, 3 clusters were produced including clusters with low, medium, and high suburbanization characteristics.

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Keywords: cluster area; remote sensing; urban growth

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In Vol 9, No 1 (2024): February 2024

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