Assessment of Ecological Cumulative Effect due to Mining Disturbance Using Google Earth Engine
Abstract
:1. Introduction
2. Materials and Methodology
2.1. Study Area
2.2. Data Acquisition and Preprocessing
2.3. Mining Area Identification Based on LandTrendr
2.4. Quantifying ESV in Mining Area
2.5. Evaluation Procession of ECE in Mining Area
2.6. Exploring Trade-Offs and Synergies among Ecosystem Services
3. Results
3.1. Mining Area Identification Based on LandTrendr
3.2. Temporal and Spatial Characteristics of Land Use Types
3.3. The Overall Spatial–Temporal Variations in ECE
3.4. ECE Spatial Characteristics of Individual Ecosystem Service Functions
3.5. Exploring Trade-Offs and Synergies among Ecosystem Services
4. Discussion
4.1. Spatial and Temporal Changes in ECE
4.2. Spatiotemporal Trade-Offs and Synergies among Ecosystem Services
4.3. Mapping of ECE in Surface Mining Area
4.4. Limitations and Future Research Priorities
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Ecosystem Service | Farmland | Forestland | Grassland | Farmland after Reclamation | Forestland after Reclamation | Grassland after Reclamation | Water |
---|---|---|---|---|---|---|---|
Soil formation and protection | 301.3 | 804.9 | 402.5 | 198.5 | 530.3 | 265.2 | 0 |
Water conservation | 640.8 | 3417.9 | 854.5 | 422.1 | 2251.9 | 563.0 | 21,766.2 |
Biodiversity maintenance | 703.9 | 3232.2 | 1080.7 | 436.8 | 2129.5 | 712.0 | 2468.8 |
Climate regulation | 1839.5 | 5580.7 | 1860.3 | 1211.9 | 3676.8 | 1225.6 | 950.7 |
Food production | 1139.1 | 119.3 | 357.9 | 750.5 | 78.6 | 235.8 | 113.9 |
Year | 1986 | 1991 | 1996 | 2001 | 2006 | 2011 | 2016 | 2021 |
---|---|---|---|---|---|---|---|---|
Overall accuracy/% | 82% | 84% | 83% | 85% | 82% | 87% | 91% | 95% |
Kappa coefficient | 0.78 | 0.80 | 0.79 | 0.82 | 0.78 | 0.83 | 0.88 | 0.93 |
ECE | NA | DA | RA | Study Area |
---|---|---|---|---|
Ideal | 1847.69 | 750.11 | 680.01 | 3277.81 |
Real | 1983.32 | 587.47 | 578.24 | 3149.03 |
Effect | 135.63 | −162.64 | −101.77 | −128.78 |
ECE | NA | DA | RA | Study Area | |
---|---|---|---|---|---|
SP | Ideal | 162.93 | 66.04 | 59.53 | 288.50 |
Real | 165.27 | 50.28 | 47.45 | 263.00 | |
Effect | 2.34 | −15.76 | −12.08 | −25.50 | |
WC | Ideal | 345.95 | 140.27 | 126.62 | 612.84 |
Real | 356.62 | 109.80 | 110.87 | 577.29 | |
Effect | 10.67 | −30.47 | −15.75 | −35.55 | |
BM | Ideal | 437.20 | 177.15 | 159.49 | 773.84 |
Real | 438.45 | 134.28 | 130.41 | 703.14 | |
Effect | 1.25 | −42.87 | −29.08 | −70.70 | |
CR | Ideal | 754.33 | 306.20 | 277.46 | 1337.99 |
Real | 806.29 | 238.20 | 235.59 | 1280.08 | |
Effect | 51.96 | −68.00 | −41.87 | −57.91 | |
FP | Ideal | 147.27 | 60.43 | 56.89 | 264.59 |
Real | 216.66 | 54.90 | 53.91 | 325.47 | |
Effect | 69.39 | −5.53 | −2.98 | 60.88 |
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Yang, W.; Mu, Y.; Zhang, W.; Wang, W.; Liu, J.; Peng, J.; Liu, X.; He, T. Assessment of Ecological Cumulative Effect due to Mining Disturbance Using Google Earth Engine. Remote Sens. 2022, 14, 4381. https://doi.org/10.3390/rs14174381
Yang W, Mu Y, Zhang W, Wang W, Liu J, Peng J, Liu X, He T. Assessment of Ecological Cumulative Effect due to Mining Disturbance Using Google Earth Engine. Remote Sensing. 2022; 14(17):4381. https://doi.org/10.3390/rs14174381
Chicago/Turabian StyleYang, Wenfu, Yao Mu, Wenkai Zhang, Wenwen Wang, Jin Liu, Junhuan Peng, Xiaosong Liu, and Tingting He. 2022. "Assessment of Ecological Cumulative Effect due to Mining Disturbance Using Google Earth Engine" Remote Sensing 14, no. 17: 4381. https://doi.org/10.3390/rs14174381