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Fig 1.

Location of the study area, mainly included urban area and suburb areas.

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Fig 2.

The flowchart of this study.

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Fig 3.

Illustration of linear model fitting of time series values.

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Fig 4.

The linear fitting goodness evaluations of NTL and NDVI time series.

(a) the RMSE map of the NTL time series; (b) examples of NTL linear fitting at sample points with high RMSE values; (c) the RMSE map of NDVI time series; (d) examples of NDVI linear fitting of sample points with high RMSE values.

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Fig 5.

The spatial distributions of the linear model parameters.

(a) map of aNTL values; (b) map of bNTL values; (c) map of aNDVI values; (d) map of bNDVI values.

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Fig 6.

The linear model lines of the samples of cluster 1, cluster 2, cluster 3, cluster 4, cluster 10 and class 11.

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Fig 7.

The linear model lines of the samples of cluster 5, cluster 6, cluster 7, cluster 8, cluster 9 and class 12.

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Table 1.

Results of clustering the linear model parameters and the urban development trends of each cluster.

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Fig 8.

The urban development trend clustering results.

LDSU-VI (type 1): Low density stable urban and vegetation increase type; UE-LDSV (type 2): Urban expansion and Low density stable vegetation type; LDSU-HDSV (type 3): Low density stable urban and High density stable vegetation type; HDSU-LDSV (type 4): High density stable urban and low density stable vegetation type; UE-HDSV (type 5): Urban expansion and high density stable vegetation type; UE-VD (type 6): Urban expansion and vegetation degeneration type.

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Fig 9.

Exclusion layers for urban expansion scenarios.

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Table 2.

Calibration results of the three scenarios.

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Fig 10.

Urban land area predicted under three scenarios by 2030.

(a) Scenario 1, historical growth; (b) Scenario 2, gentle restriction of urban expansion; (c) Scenario 3, strict restriction of urban expansion.

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Table 3.

Predicted urban expansion statistics, in 2030, under three scenarios.

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Fig 11.

T-test values of time series normalized NTL linear fitting.

(a) the spatial distribution map of t-test values. (b) examples of NTL linear fitting at sample points with low t-test values.

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