Mapping Urban Expansions along China–Europe Railway Express with the 30 m Time-Series Global Impervious Surface Area (GISA-2) Data from 2010 to 2019
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.2.1. Global Impervious Surface Area (GISA 2)
2.2.2. CRE Outline Data and Other Ancillary Data
2.3. Methodology
- (1)
- Initial boundary extraction: aggregation of ISA to delineate prospective urban fringes through a kernel density estimator;
- (2)
- Boundary improvement: multiscale fusion applied to refine the initial urban boundaries, which distinctively diverges from Li’s foundational framework [34] by offering an explicit spatial enhancement for cities of different scales;
- (3)
- Post-processing: measures designed to rectify minor discontinuities (e.g., small water bodies and green spaces) within the urban fabric and to ensure the temporal coherence of the urban expansion patterns.
2.3.1. Urban Fringe and Initial Boundary Extraction
2.3.2. Boundary Improvement with Multiscale Fusion
3. Results
3.1. Evaluations of Derived Urban Boundaries
3.1.1. Comparison with Historical Google Imagery
3.1.2. Cross-Comparisons with Other Global 30 m Urban Products
3.2. The Spatiotemporal Dynamics of Urban Boundaies from 2010 to 2019
3.2.1. Spatiotemporal Patterns Urban Clusters
3.2.2. Comparison of Spatial Dynamics between ON-CRE and OFF-CRE Cities
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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(1) 18 Countries and Regions along the Express | (2) 19 Countries and Regions Not along the Express |
---|---|
Austria, Belarus, Belgium, Czech Republic, France, Germany, Hungary, Italy, Latvia, Lithuania, Luxembourg, Monaco, Netherlands, Poland, Serbia, Slovakia, Spain, United Kingdom. | Albania, Andorra, Bosnia and Herzegovina, Bulgaria, Croatia, Denmark, Estonia, Greece, Ireland, Liechtenstein, Moldova, Montenegro, North Macedonia, Portugal, Romania, San Marino, Slovenia, Switzerland, Vatican City. |
Entire Study Area | ||||||
---|---|---|---|---|---|---|
Area (number) | L1 | L2 | L3 | L4 | L5 | Total |
2010 | 25,513.4 (3547) | 14,969.0 (334) | 8300.4 (50) | 6186.2 (14) | 6650.3 (6) | 61,619.4 (3951) |
2015 | 26,258.2 (3620) | 15,157.4 (331) | 8497.6 (51) | 4566.8 (11) | 9333.3 (10) | 63,813.4 (4023) |
2019 | 28,811.8 (3973) | 17,284.5 (376) | 10,386.1(63) | 4184.4 (10) | 10,287.6 (11) | 70,954.4 (4433) |
ON-CRE | ||||||
Area (number) | L1 | L2 | L3 | L4 | L5 | Total |
2010 | 1791.3 (218) | 1956.2 (42) | 3437.8 (18) | 3650.1 (9) | 5699.1 (5) | 16,534.5 (292) |
2015 | 1874.8 (225) | 1971.4 (42) | 3478.2 (18) | 2278.9 (6) | 7745.9 (8) | 17,349.2 (299) |
2019 | 1998.5 (233) | 2319.7 (47) | 3754.6 (18) | 2359.0 (6) | 7956.2 (8) | 18,387.9 (312) |
OFF-CRE | ||||||
Area (number) | L1 | L2 | L3 | L4 | L5 | Total |
2010 | 23,722.1 (3329) | 13,012.9 (292) | 4862.5 (32) | 2536.1 (5) | 951.2 (1) | 45,084.8 (3659) |
2015 | 24,383.4 (3395) | 13,186.0 (289) | 5019.4 (33) | 2288.0 (5) | 1587.4 (2) | 46,464.2 (3724) |
2019 | 27,026.5 (3769) | 14,962.8 (329) | 6627.6 (45) | 1797.6 (4) | 2331.4 (3) | 52,746.0 (4150) |
Paris | The Hague–Rotterdam | Antwerp– Brussels | Minsk | Kaiserslautern | |
---|---|---|---|---|---|
Population (m) | 2.2 | 1.7 | 2.8 | 2.0 | 0.1 |
Area (2010, km2) | 1474.63 | 498.65 | 660.11 | 230.16 | 24.63 |
Area (2015, km2) | 1501.6 | 624.95 | 683.85 | 253.98 | 26.11 |
Area (2019, km2) | 1540.27 | 647.269 | 711.5 | 274.18 | 27.04 |
Expansion rates (2010–2015) | 1.83% | 25.33% | 3.60% | 10.35% | 6.03% |
Expansion rates (2015–2019) | 2.58% | 3.57% | 4.04% | 7.95% | 3.57% |
Birmingham | Barcelona | Rome | Bratislava | Potsdam | |
---|---|---|---|---|---|
Population (m) | 2.6 | 5.5 | 4.2 | 0.4 | 0.2 |
Area (2010, km2) | 593.51 | 576.64 | 383.07 | 98.02 | 24.46 |
Area (2015, km2) | 603.53 | 586.47 | 395.04 | 99.87 | 25.53 |
Area (2019, km2) | 607.22 | 649.74 | 404.43 | 101.85 | 26.93 |
Expansion rates (2010–2015) | 1.69% | 1.71% | 3.12% | 1.89% | 4.36% |
Expansion rates (2015–2019) | 0.61% | 3.57% | 2.38% | 1.98% | 5.48% |
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Guo, X.; Pei, Y.; Xu, H.; Wang, Y. Mapping Urban Expansions along China–Europe Railway Express with the 30 m Time-Series Global Impervious Surface Area (GISA-2) Data from 2010 to 2019. Sustainability 2024, 16, 1651. https://doi.org/10.3390/su16041651
Guo X, Pei Y, Xu H, Wang Y. Mapping Urban Expansions along China–Europe Railway Express with the 30 m Time-Series Global Impervious Surface Area (GISA-2) Data from 2010 to 2019. Sustainability. 2024; 16(4):1651. https://doi.org/10.3390/su16041651
Chicago/Turabian StyleGuo, Xian, Yujie Pei, Hong Xu, and Yang Wang. 2024. "Mapping Urban Expansions along China–Europe Railway Express with the 30 m Time-Series Global Impervious Surface Area (GISA-2) Data from 2010 to 2019" Sustainability 16, no. 4: 1651. https://doi.org/10.3390/su16041651