Detecting Spatial-Temporal Changes of Urban Environment Quality by Remote Sensing-Based Ecological Indices: A Case Study in Panzhihua City, Sichuan Province, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data and Pre-Processing
2.3. Construct RSEI
2.3.1. Greenness
2.3.2. Wetness
2.3.3. Dryness
2.3.4. Heat
2.3.5. RSEI and EEQ
2.4. Spatial Autocorrelation Analysis
3. Results
3.1. Comprehensive Evaluation of EEQ of Panzhihua City
3.2. Autocorrelation Analysis
3.3. Detection of Changes of Ecological Environmental Quality
4. Discussion
4.1. Evaluation Method of EEQ
4.2. Suitability of RSEI
4.3. Impact of the Policy on EEQ
4.4. GEE Platform and Time Series Interval
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Region | Year | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | |
---|---|---|---|---|---|---|---|
Baima mine | 1990 | Area (km2) | 53.94 | 45.37 | 33.21 | 25.47 | 17.20 |
Pct./% | 30.79 | 25.90 | 18.96 | 14.54 | 9.82 | ||
1995 | Area (km2) | 33.82 | 41.21 | 39.67 | 35.63 | 24.86 | |
Pct./% | 19.31 | 23.52 | 22.64 | 20.34 | 14.19 | ||
2000 | Area (km2) | 17.41 | 31.39 | 41.52 | 42.01 | 42.87 | |
Pct./% | 9.94 | 17.91 | 23.70 | 23.98 | 24.47 | ||
2005 | Area (km2) | 61.50 | 52.06 | 40.71 | 18.04 | 2.90 | |
Pct./% | 35.10 | 29.71 | 23.23 | 10.30 | 1.65 | ||
2010 | Area (km2) | 61.75 | 54.96 | 36.10 | 18.37 | 4.03 | |
Pct./% | 35.25 | 31.37 | 20.60 | 10.48 | 2.30 | ||
2015 | Area (km2) | 59.66 | 51.40 | 34.82 | 23.17 | 6.14 | |
Pct./% | 34.05 | 29.34 | 19.87 | 13.23 | 3.50 | ||
2020 | Area (km2) | 42.93 | 52.42 | 35.93 | 26.19 | 17.72 | |
Pct./% | 24.50 | 29.92 | 20.51 | 14.95 | 10.12 | ||
Panjiatian mine | 1990 | Area (km2) | 2.13 | 3.86 | 4.87 | 2.53 | 0.55 |
Pct./% | 15.25 | 27.70 | 34.93 | 18.16 | 3.95 | ||
1995 | Area (km2) | 1.96 | 3.33 | 4.28 | 3.22 | 1.16 | |
Pct./% | 14.08 | 23.86 | 30.66 | 23.12 | 8.29 | ||
2000 | Area (km2) | 2.38 | 4.72 | 4.94 | 1.74 | 0.17 | |
Pct./% | 17.07 | 33.82 | 35.41 | 12.47 | 1.23 | ||
2005 | Area (km2) | 2.16 | 5.15 | 4.79 | 1.80 | 0.06 | |
Pct./% | 15.46 | 36.90 | 34.36 | 12.88 | 0.40 | ||
2010 | Area (km2) | 2.31 | 5.46 | 4.59 | 1.56 | 0.03 | |
Pct./% | 16.56 | 39.13 | 32.91 | 11.17 | 0.22 | ||
2015 | Area (km2) | 2.55 | 4.38 | 4.07 | 2.82 | 0.12 | |
Pct./% | 18.31 | 31.41 | 29.15 | 20.24 | 0.89 | ||
2020 | Area (km2) | 3.72 | 3.76 | 2.64 | 2.75 | 1.08 | |
Pct./% | 26.69 | 26.92 | 18.92 | 19.73 | 7.75 | ||
Zhulan mine | 1990 | Area (km2) | 89.20 | 40.57 | 18.62 | 8.28 | 2.77 |
Pct./% | 55.95 | 25.44 | 11.68 | 5.19 | 1.74 | ||
1995 | Area (km2) | 87.99 | 37.85 | 19.02 | 10.11 | 4.46 | |
Pct./% | 55.19 | 23.74 | 11.93 | 6.34 | 2.80 | ||
2000 | Area (km2) | 79.06 | 41.87 | 22.93 | 11.86 | 3.72 | |
Pct./% | 49.59 | 26.26 | 14.38 | 7.44 | 2.33 | ||
2005 | Area (km2) | 92.71 | 41.21 | 19.02 | 5.61 | 0.88 | |
Pct./% | 58.15 | 25.85 | 11.93 | 3.52 | 0.55 | ||
2010 | Area (km2) | 68.81 | 54.83 | 26.24 | 7.78 | 1.79 | |
Pct./% | 43.15 | 34.39 | 16.46 | 4.88 | 1.12 | ||
2015 | Area (km2) | 67.29 | 47.07 | 30.66 | 12.51 | 1.91 | |
Pct./% | 42.20 | 29.52 | 19.23 | 7.85 | 1.20 | ||
2020 | Area (km2) | 46.44 | 51.59 | 35.32 | 18.49 | 7.61 | |
Pct./% | 29.12 | 32.36 | 22.15 | 11.60 | 4.77 |
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Year | Indicators | PC1 | PC2 | PC3 | PC4 |
---|---|---|---|---|---|
1990 | WET | 0.12 | 0.38 | 0.38 | −0.84 |
NDVI | 0.91 | −0.39 | −0.10 | −0.09 | |
NDBSI | −0.29 | −0.37 | −0.71 | −0.53 | |
LST | −0.27 | −0.75 | 0.59 | −0.12 | |
Eigenvalue | 0.01 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 84.32% | 11.00% | 4.08% | 0.61% | |
1995 | WET | 0.17 | 0.43 | 0.87 | −0.19 |
NDVI | 0.96 | −0.29 | −0.05 | −0.04 | |
NDBSI | −0.07 | −0.07 | −0.16 | −0.98 | |
LST | −0.23 | −0.85 | 0.47 | 0.00 | |
Eigenvalue | 0.01 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 89.21% | 7.99% | 2.72% | 0.08% | |
2000 | WET | 0.14 | −0.56 | 0.80 | 0.12 |
NDVI | 0.17 | −0.58 | −0.53 | 0.60 | |
NDBSI | −0.97 | −0.22 | 0.00 | 0.07 | |
LST | −0.07 | 0.54 | 0.28 | 0.79 | |
Eigenvalue | 0.01 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 78.46% | 17.37% | 3.26% | 0.91% | |
2005 | WET | 0.09 | −0.06 | 0.42 | −0.90 |
NDVI | 0.79 | 0.60 | −0.12 | −0.02 | |
NDBSI | −0.13 | −0.02 | −0.90 | −0.42 | |
LST | −0.59 | 0.80 | 0.10 | −0.06 | |
Eigenvalue | 0.01 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 78.78% | 19.02% | 2.03% | 0.17% | |
2010 | WET | 0.13 | −0.01 | 0.90 | −0.41 |
NDVI | 0.48 | 0.87 | −0.08 | −0.07 | |
NDBSI | −0.07 | −0.07 | −0.40 | −0.91 | |
LST | −0.86 | 0.49 | 0.12 | −0.02 | |
Eigenvalue | 0.02 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 84.15% | 14.32% | 1.41% | 0.12% | |
2015 | WET | 0.23 | 0.04 | 0.97 | −0.11 |
NDVI | 0.51 | 0.85 | −0.15 | 0.00 | |
NDBSI | −0.03 | −0.01 | −0.11 | −0.99 | |
LST | −0.83 | 0.53 | 0.18 | 0.00 | |
Eigenvalue | 0.01 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 76.92% | 18.87% | 4.18% | 0.03% | |
2020 | WET | 0.39 | −0.07 | −0.87 | −0.30 |
NDVI | 0.53 | 0.82 | 0.20 | −0.07 | |
NDBSI | −0.17 | −0.03 | 0.26 | −0.95 | |
LST | −0.73 | 0.56 | −0.38 | 0.01 | |
Eigenvalue | 0.02 | 0.00 | 0.00 | 0.00 | |
Percent eigenvalue | 78.05% | 12.84% | 8.57% | 0.54% |
Region | 1990 | 1995 | 2000 | 2005 | 2010 | 2015 | 2020 | Average | |
---|---|---|---|---|---|---|---|---|---|
Baima Mine | Mine Scale/% | 33.30% | 30.36% | 49.18% | 23.85% | 30.63% | 33.75% | 36.96% | 34.00% |
City Scale/% | 68.44% | 52.00% | 41.78% | 11.56% | 11.56% | 24.00% | 39.11% | 35.49% | |
Zhulan Mine | Mine Scale/% | 27.09% | 30.12% | 23.33% | 29.39% | 37.46% | 31.98% | 38.04% | 31.06% |
City Scale/% | 16.34% | 12.87% | 15.35% | 6.44% | 10.40% | 12.87% | 21.29% | 13.65% | |
Panjiatian Mine | Mine Scale/% | 33.22% | 23.98% | 34.88% | 28.73% | 15.70% | 18.36% | 13.44% | 24.05% |
City Scale/% | 91.67% | 100.00% | 4.17% | 45.83% | 54.17% | 83.33% | 70.83% | 64.29% |
Region | Improvement Obvious | Improvement Slight | Invariability | Deterioration Slight | Deterioration Obvious | |
---|---|---|---|---|---|---|
Panzhihua | Area/km2 | 151.73 | 2760.57 | 3315.38 | 1371.91 | 114.42 |
Pct./% | 1.97 | 35.79 | 42.98 | 17.78 | 1.48 | |
Zhulan mine | Area/km2 | 1.70 | 80.79 | 68.15 | 8.64 | 0.16 |
Pct./% | 1.07 | 50.67 | 42.74 | 5.42 | 0.10 | |
Baima mine | Area/km2 | 2.61 | 62.55 | 65.35 | 38.58 | 6.10 |
Pct./% | 1.49 | 35.70 | 37.30 | 22.02 | 3.48 | |
Panjiatian mine | Area/km2 | 0.26 | 4.70 | 3.94 | 4.30 | 0.75 |
Pct./% | 1.86 | 33.68 | 28.25 | 30.84 | 5.37 |
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Shan, Y.; Dai, X.; Li, W.; Yang, Z.; Wang, Y.; Qu, G.; Liu, W.; Ren, J.; Li, C.; Liang, S.; et al. Detecting Spatial-Temporal Changes of Urban Environment Quality by Remote Sensing-Based Ecological Indices: A Case Study in Panzhihua City, Sichuan Province, China. Remote Sens. 2022, 14, 4137. https://doi.org/10.3390/rs14174137
Shan Y, Dai X, Li W, Yang Z, Wang Y, Qu G, Liu W, Ren J, Li C, Liang S, et al. Detecting Spatial-Temporal Changes of Urban Environment Quality by Remote Sensing-Based Ecological Indices: A Case Study in Panzhihua City, Sichuan Province, China. Remote Sensing. 2022; 14(17):4137. https://doi.org/10.3390/rs14174137
Chicago/Turabian StyleShan, Yunfeng, Xiaoai Dai, Weile Li, Zhichong Yang, Youlin Wang, Ge Qu, Wenxin Liu, Jiashun Ren, Cheng Li, Shuneng Liang, and et al. 2022. "Detecting Spatial-Temporal Changes of Urban Environment Quality by Remote Sensing-Based Ecological Indices: A Case Study in Panzhihua City, Sichuan Province, China" Remote Sensing 14, no. 17: 4137. https://doi.org/10.3390/rs14174137
APA StyleShan, Y., Dai, X., Li, W., Yang, Z., Wang, Y., Qu, G., Liu, W., Ren, J., Li, C., Liang, S., & Zeng, B. (2022). Detecting Spatial-Temporal Changes of Urban Environment Quality by Remote Sensing-Based Ecological Indices: A Case Study in Panzhihua City, Sichuan Province, China. Remote Sensing, 14(17), 4137. https://doi.org/10.3390/rs14174137