Abstract
The urban mixed land use strategy can improve the efficiency and value of land use, which is of great significance to the sustainable development of cities. Previous studies related to urban land use mainly focused on neighborhood, grid, or parcel scales. These spatial scales are not fine enough to cover the spatial structure information of the internal multi-functional mixture, which is difficult to meet the needs of fine urban planning and construction. To this end, this paper proposes an urban mixed land use decomposition model at the pixel scale with higher spatial resolution, combined with a spectral unmixing strategy. Firstly, this paper constructs a multi-source feature set to describe the natural and socio-economic characteristics of urban functions. Then, the Fully Constrained Least Squares (FCLS) model was used to extract the information of urban functional abundance. The results of the mixed decomposition were compared qualitatively and quantitatively with previous studies, and the overall accuracy was verified to be 0.833 and 0.763 for Kappa. Finally, Shannon Diversity Indicator (SHDI) was constructed to characterize the multifunctional mixed-use level of construction land units.
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This work is supported by The National Natural Science Foundation of China (No. 41901332).
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Huang, C., Liang, X., Yang, Z., Guan, Q. (2021). A Fine-Grained Mixed Land Use Decomposition Method Based on Multi-source Geospatial Data. In: Pan, G., et al. Spatial Data and Intelligence. SpatialDI 2021. Lecture Notes in Computer Science(), vol 12753. Springer, Cham. https://doi.org/10.1007/978-3-030-85462-1_18
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DOI: https://doi.org/10.1007/978-3-030-85462-1_18
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