Wang Yue, Lu Xingrong, Chen Guohong
School of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China.
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130012, China.
Sci Rep. 2025 Jul 1;15(1):21249. doi: 10.1038/s41598-025-94770-z.
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.
确定土地利用和土地覆盖变化（LUCC）时空尺度特征的适当分析方法，能够有效地揭示和把握复杂的地理现象与格局。然而，当前的方法往往存在主观性、实验误差以及空间表征方面的局限性，因为它们通常依赖统计数据。迫切需要创新方法来识别空间（基于网格）和时间（时间序列）尺度。本研究聚焦于沈阳经济区，采用增强型分形盒计数维模型和小波分析来客观确定LUCC的时空尺度。研究结果表明：（1）分形特征有效地衡量了空间尺度，（2）小波方差作为描述LUCC时间发展的一个新参数。这些结果表明，分形特征和小波方差是LUCC的有力描述指标，所提出的时空尺度识别方法具有很强的适用性。
