Fractal Characteristic Analysis of Urban Land-Cover Spatial Patterns with Spatiotemporal Remote Sensing Images in Shenzhen City (1988–2015)

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 22; p. 4640
• Main Authors: Cheng, Luxiao, Feng, Ruyi, Wang, Lizhe
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2021
• Subjects: bifractals; Cities; Complexity; Cultivated lands; Entropy (Information theory); Evolution; Fractal analysis; fractal dimension; Fractal geometry; Fractals; Grasslands; Land cover; Land resources; Land use; land-cover evolution; Landsat; Landsat satellites; Least squares method; Morphology; Remote sensing; Research methodology; Satellite imagery; Structural hierarchy; Sustainable development; urban spatial structure; Urbanization; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13224640

Understanding the urban land-cover spatial patterns is of particular significance for sustainable development planning. Due to the nonlinear characteristics related to the spatial pattern for land cover, it is essential to provide a new analysis method to analyze them across remote sensing imagery. This paper is devoted to exploring the fractals and fractal dimension properties of land-cover spatial patterns in Shenzhen city, China. Land-cover information was extracted using a supervised classification method with ArcGIS technology from cloud-free Landsat TM/ETM+/OLI imagery, covering 1988–2015. The box-counting method and the least squares regression method are combined to estimate fractal dimensions of the land-cover spatial pattern. The information entropy was used to verify our fractal dimension results. The results show the fractal dimension changes for each land cover type from 1988 to 2015: (1) the land-cover spatial form of Shenzhen city has a clear fractal structure, but fractal dimension values vary in different land cover types; (2) the fractal dimension of build-up land increases and reaches a stable value, while grassland and cultivated land decrease; The fractal structure of grassland and bare land showed a bifractals trend increasing year by year; (3) the information entropy dimension growth is approaching its maximum capacity before 2011. We integrated the information entropy index and fractal dimension to analyze the complexity in land-cover spatial evolution from space-filling, space balance, and space complexity. It can be concluded that driven by policies, the land-cover spatial form in Shenzhen experienced a process from a hierarchical spatial structure with a low evolution intensity to a higher evolution intensity with multiscale differential development. The fractal dimension has been becoming better through self-organization, and its land resources are reaching the growth limits.