Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Resources and Image Pre-Processing
2.3. Object-Oriented Land Cover Classification and Accuracy Assessment
2.4. Land Cover Change Analysis
2.5. RSEI Model
2.5.1. Greenness (NDVI)
2.5.2. Wetness
2.5.3. Heat (LST)
2.5.4. Dryness (NDBSI)
2.5.5. Integration of the Four Indicators
2.6. Spatial Auto-Correlation Analysis
2.6.1. Global Spatial Auto-Correlation Analysis
2.6.2. Local Spatial Auto-Correlation Analysis (Hot-Spot Analysis)
3. Results
3.1. Validation of the LC Classifications and the Final Classification Maps
3.2. Spatial-Temporal Conversion Analysis of the Land Cover Types
3.3. The Spatio-Temporal Transformation of Ecological Quality
3.4. Spatial Auto-Correlation Analysis
4. Discussion and Policy Implications
4.1. LC and Ecological Quality Changes Resulting from Traditional Urbanization (2009–2015) and NTU (2015–2019)
4.2. Uncertainties and Future Work
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Satellites | Acquisition Date | Bands | Spatial Resolution (Pan/Multi-Spectral, m) |
---|---|---|---|
RapidEye | 25 Jun 2009 | Blue, Green, Red, Red edge, Near infrared | none, 5 |
GF-1 WFV4 | 3 Aug 2015 | Blue, Green, Red, Near infrared | none, 16 |
Sentinel-2A | 19 Sep 2019 | Blue, Green, Red, Red edge, Near infrared, Shortwave infrared | none, 10 |
Landsat 5 TM | 13 Jun 2009 | Blue, Green, Red, Near infrared, Shortwave infrared, Longwave infrared | none, 30 |
Landsat 8 OLI/TIRS | 14 Jun 2015 13 Sep 2019 | Blue, Green, Red, Near infrared, Shortwave infrared, Longwave infrared | 15, 30 |
Sensor | Gain | Bias | K1 (W·m−2·sr−1·μm−1) | K2 (K) |
---|---|---|---|---|
TM (band 6) | 0.055 | 1.18243 | 607.76 | 1260.56 |
TIRS (band 10) | 3.342 × 10−4 | 0.1 | 774.89 | 1321.08 |
Dataset | Segmentation Scale | Shape | Compactness | Overall Accuracy (%) | Kappa Coefficient |
---|---|---|---|---|---|
RapidEye | 67 | 0.2 | 0.5 | 90.75 | 0.88 |
GF-1 WFV4 | 77 | 0.2 | 0.6 | 91.75 | 0.90 |
Sentinel-2A | 65 | 0.4 | 0.6 | 92.04 | 0.90 |
Final | Urban | Cropland | Water Body | Forest | Grassland | Unused Land | ||
---|---|---|---|---|---|---|---|---|
Initial | ||||||||
2009–2019 (km2) 2009–2015 (%) | urban | 116.09 (39.86) | 47.72 (42.23) | 3.67 (54.50) | 10.67 (49.95) | 13.02 (34.95) | 4.65 (48.82) | |
cropland | 74.67 (63.49) | 223.11 (55.16) | 3.67 (72.16) | 33.75 (53.21) | 30.91 (48.04) | 13.29 (58.62) | ||
water body | 6.01 (80.20) | 7.12 (54.21) | 8.16 (48.41) | 1.70 (47.65) | 1.31 (48.09) | 0.78 (46.15) | ||
forest | 13.79 (39.88) | 27.39 (40.64) | 0.83 (66.27) | 148.87 (50.14) | 7.60 (52.24) | 3.58 (57.82) | ||
grassland | 9.00 (63.33) | 8.98 (32.96) | 1.37 (35.77) | 3.89 (45.76) | 3.63 (49.59) | 0.81 (40.74) | ||
unused land | 15.40 (35.32) | 15.40 (31.10) | 0.65 (46.15) | 6.00 (61.33) | 3.88 (33.25) | 2.30 (43.91) | ||
Area/km2 | 2009 | 80.67 | 214.31 | 14.52 | 97.81 | 16.65 | 13.17 | |
2015 | 115.74 | 166.21 | 10.68 | 104.21 | 13.84 | 27.12 | ||
2019 | 119.93 | 164.63 | 7.93 | 100.67 | 33.39 | 11.62 | ||
Annual change rate (%) | 2009–2015 | 7.24 | −3.74 | −4.41 | 1.09 | −2.82 | 17.64 | |
2015–2019 | 0.91 | −0.24 | −6.44 | −0.85 | 35.31 | −14.29 |
Indicator | PC1 | Mean | ||||
---|---|---|---|---|---|---|
2009 | 2015 | 2019 | 2009 | 2015 | 2019 | |
NDVI | 0.066 | 0.042 | 0.08 | 0.706 | 0.731 | 0.795 |
Wet | 0.457 | 0.272 | 0.96 | 0.463 | 0.516 | 0.507 |
LST | −0.197 | −0.126 | −0.545 | 0.654 | 0.631 | 0.58 |
NDBSI | −0.193 | −0.135 | −0.728 | 0.431 | 0.474 | 0.631 |
Eigenvalues | 0.267 | 0.358 | 0.322 | |||
Eigenvalue contribution (%) | 66.4 | 61.02 | 56.37 | |||
RESI | 0.583 | 0.559 | 0.579 |
RSEI Level | 2009 | 2015 | 2019 | |||
---|---|---|---|---|---|---|
Area/km2 | Proportion/% | Area/km2 | Proportion/% | Area/km2 | Proportion/% | |
Bad (0–0.2) | 109.77 | 25.10 | 136.34 | 31.18 | 122.44 | 28.00 |
Poor (0.2–0.4) | 111.14 | 25.42 | 91.53 | 20.93 | 61.33 | 14.03 |
Medium (0.4–0.6) | 95.87 | 21.92 | 9.79 | 2.24 | 17.86 | 4.08 |
Good (0.6–0.8) | 53.04 | 12.13 | 57.71 | 13.20 | 80.46 | 18.40 |
Excellent (0.8–1.0) | 67.45 | 15.43 | 141.89 | 32.45 | 155.17 | 35.49 |
Change | Level Change | 2009–2015 | 2015–2019 | 2019–2009 | |||
---|---|---|---|---|---|---|---|
Area/km2 | Proportion/% | Area/km2 | Proportion/% | Area/km2 | Proportion/% | ||
Deterioration | −4 | 3.50 | 27.91 | 13.61 | 20.59 | 3.83 | 24.62 |
−3 | 10.94 | 21.53 | 10.48 | ||||
−2 | 36.43 | 12.34 | 32.82 | ||||
−1 | 71.18 | 42.53 | 60.51 | ||||
Invariability | 0 | 150.69 | 34.46 | 212.93 | 48.7 | 136.40 | 31.19 |
Amelioration | 1 | 73.35 | 37.63 | 43.84 | 30.72 | 72.56 | 44.19 |
2 | 45.09 | 35.21 | 62.77 | ||||
3 | 37.01 | 41.77 | 49.14 | ||||
4 | 9.07 | 13.5 | 14.22 |
Year | Pukou District | Nanjing City | |||||
---|---|---|---|---|---|---|---|
Per Capita Disposable Income of Urban Residents (Yuan) | Rural Economic Conditions (10,000 People) | Per Capita Green Area (m2) | Green Coverage Rate in Built-Up Area (%) | Green Coverage Area (hm2) | |||
Total Registered Population | Agriculture, Forestry, Animal Husbandry, and Fishery Employees | Number of Industrial Employees | |||||
2009 | 23,542 | 54.87 | 2.61 | 4.07 | |||
2010 | 13.69 | 44.38 | 84,848 | ||||
2015 | 43,687 | 64.28 | 2.06 | 4.2 | 15.1 | 44.47 | 96,874 |
2019 | 59,807 | 76.49 | 1.71 | 2.79 | 15.7 | 45.16 | 101,327 |
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Shi, F.; Li, M. Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing. Sustainability 2021, 13, 11979. https://doi.org/10.3390/su132111979
Shi F, Li M. Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing. Sustainability. 2021; 13(21):11979. https://doi.org/10.3390/su132111979
Chicago/Turabian StyleShi, Fang, and Mingshi Li. 2021. "Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing" Sustainability 13, no. 21: 11979. https://doi.org/10.3390/su132111979