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<p>This study uses remote sensing techniques to investigate the spatiotemporal dynamics of urban expansion and its impact on landscape diversity in the peri-urban area of Semarang City, Indonesia. Satellite imagery from Landsat-9 OLI-2 (2022), Landsat-8 OLI (2015), and Landsat-5 TM (2008) was processed using supervised classification to map land use/land cover (LULC) and extract built-up areas (BA). The Landscape Expansion Index (LEI) was then applied to categorize BA expansion types, while Shannon’s Entropy Index assessed changes in LULC diversity. The findings reveal that between 2008 and 2022, the peri-urban areas of Semarang experienced accelerated expansion of the built-up regions, contributing to urban sprawl. The LULC classification showed high accuracy rates of 86.3% in 2008, 86.8% in 2015, and 87.6% in 2022, with the LEI achieving accuracy values of 86.4% (2008–2015) and 88.1% (2015–2022). Correlation analysis reveals strong relationships between changes in LULC diversity and outlying expansion, with coefficients of 0.55 (<i>p</i> = 0.045) (2008–2015) and 0.84 (<i>p</i> = 0.001) (2015–2022). The findings highlight the adverse effects of outlying urban growth on landscape diversity and sustainability. Outlying urban growth leads to inefficient land use and low connectivity, necessitating costly infrastructure development that encroaches on surrounding habitats. This issue is even more concerning when expansion occurs in areas not designated for residential use, such as protected zones. This research underscores the importance of integrating geospatial indices in urban planning to promote sustainable development and advance spatial information science applications in managing urban expansion.</p>

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Remote sensing-based investigation of outlying urban expansion and its impact on landscape diversity in the peri-urban area of Semarang City, Indonesia

  • 期刊论文

  • 发表日期：

    2025年4月17日

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  • Dimas Danar Dewa,
  • Imam Buchori,
  • Iwan Rudiarto,
  • Anang Wahyu Sejati

摘要

This study uses remote sensing techniques to investigate the spatiotemporal dynamics of urban expansion and its impact on landscape diversity in the peri-urban area of Semarang City, Indonesia. Satellite imagery from Landsat-9 OLI-2 (2022), Landsat-8 OLI (2015), and Landsat-5 TM (2008) was processed using supervised classification to map land use/land cover (LULC) and extract built-up areas (BA). The Landscape Expansion Index (LEI) was then applied to categorize BA expansion types, while Shannon’s Entropy Index assessed changes in LULC diversity. The findings reveal that between 2008 and 2022, the peri-urban areas of Semarang experienced accelerated expansion of the built-up regions, contributing to urban sprawl. The LULC classification showed high accuracy rates of 86.3% in 2008, 86.8% in 2015, and 87.6% in 2022, with the LEI achieving accuracy values of 86.4% (2008–2015) and 88.1% (2015–2022). Correlation analysis reveals strong relationships between changes in LULC diversity and outlying expansion, with coefficients of 0.55 (p = 0.045) (2008–2015) and 0.84 (p = 0.001) (2015–2022). The findings highlight the adverse effects of outlying urban growth on landscape diversity and sustainability. Outlying urban growth leads to inefficient land use and low connectivity, necessitating costly infrastructure development that encroaches on surrounding habitats. This issue is even more concerning when expansion occurs in areas not designated for residential use, such as protected zones. This research underscores the importance of integrating geospatial indices in urban planning to promote sustainable development and advance spatial information science applications in managing urban expansion.