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<p>Determining the appropriate analysis of spatio-temporal scale characteristics of land use and land cover change (LUCC) can effectively reveal and grasp complex geographical phenomena and patterns. However, current methodologies often suffer from subjectivity, experimental errors, and limitations in spatial representation, as they typically rely on statistical data. There is an urgent need for innovative methods to identify spatial (grid-based) and temporal (time series) scales. This study focuses on the Shenyang Economic Zone, employing an enhanced fractal box-counting dimension model and wavelet analysis to objectively determine the spatial and temporal scales of LUCC. The findings indicate that: (1) Fractal characteristics effectively measure spatial-scale, and (2) Wavelet variance serves as a novel parameter for describing LUCC’s temporal development. These results demonstrate that fractal characteristics and wavelet variance are robust descriptors of LUCC, with the proposed spatio-temporal scale identification methods showing strong applicability.</p>

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Spatio-temporal scale identification of LUCC based on remote sensing images in Shenyang Economic Zone

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Yue Wang,
  • Xingrong Lu,
  • Guohong Chen

摘要

Determining the appropriate analysis of spatio-temporal scale characteristics of land use and land cover change (LUCC) can effectively reveal and grasp complex geographical phenomena and patterns. However, current methodologies often suffer from subjectivity, experimental errors, and limitations in spatial representation, as they typically rely on statistical data. There is an urgent need for innovative methods to identify spatial (grid-based) and temporal (time series) scales. This study focuses on the Shenyang Economic Zone, employing an enhanced fractal box-counting dimension model and wavelet analysis to objectively determine the spatial and temporal scales of LUCC. The findings indicate that: (1) Fractal characteristics effectively measure spatial-scale, and (2) Wavelet variance serves as a novel parameter for describing LUCC’s temporal development. These results demonstrate that fractal characteristics and wavelet variance are robust descriptors of LUCC, with the proposed spatio-temporal scale identification methods showing strong applicability.