Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China
Abstract
:1. Introduction
- (1)
- To construct the best model for predicting topsoil SOC density of coastal wetlands based on 193 sample data and 9 environmental variables;
- (2)
- To discuss the importance of using remote sensing data in predicting topsoil SOC density of coastal wetlands;
- (3)
- To analyze the uncertainty of our method and results.
2. Materials and Methods
2.1. Description of the Study Area
2.2. Soil Sampling and Laboratory Analysis
2.3. Calculation of SOC Density
2.4. Environmental Variables
2.4.1. Remote Sensing Related Variables
2.4.2. Topographic Variables
2.4.3. Climatic Variables
2.5. Prediction Model
2.6. Model Validation
3. Results
3.1. Descriptive Statistics
3.2. Model Performance and Uncertainty
3.3. Importance of Environmental Variables
3.4. Spatial Prediction of SOC Density
4. Discussion
4.1. Importance of Remote Sensing-Related Variables in Predicting SOC Density
4.2. SOC Distribution and Associated Predictors
4.3. Uncertainty in Current Research
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Property | Unit | Min. | Mean | Max. | SD | Skewness | Kurtosis |
---|---|---|---|---|---|---|---|
SOC density | kg m−2 | 0.33 | 11.14 | 28.31 | 0.47 | 0.56 | 2.43 |
SAVI | 0.07 | 0.14 | 0.35 | 0.27 | −0.47 | 1.61 | |
NDVI | 0.02 | 0.08 | 0.33 | 0.04 | −0.31 | 1.73 | |
RVI | 0.36 | 0.76 | 1.12 | 0.34 | −1.24 | 1.22 | |
DVI | 12.76 | 39.43 | 57.23 | 7.72 | 0.39 | 2.33 | |
RDVI | 21.17 | 42.05 | 60.09 | 8.10 | 0.53 | 3.27 | |
Elevation | m | 1 | 2.87 | 12 | 1.12 | 1.13 | 3.24 |
SG | degree | 0 | 0.05 | 2.16 | 0.11 | 0.93 | 0.32 |
SA | degree | 0 | 174.62 | 360 | 92.65 | −0.42 | −0.89 |
TWI | 7.30 | 10.70 | 10.95 | 0.54 | 0.96 | 1.12 | |
MAT | degree Celsius | 9.33 | 9.53 | 9.67 | 0.38 | −1.21 | 2.16 |
MAP | mm | 648.7 | 650.6 | 652.3 | 1.31 | 0.84 | 0.93 |
Property | SOC Density | Elevation | SG | SA | TWI | SAVI | NDVI | RVI | DVI | MAT |
---|---|---|---|---|---|---|---|---|---|---|
Elevation | 0.19 * | |||||||||
SG | 0.13 | 0.33 ** | ||||||||
SA | 0.15 | 0.15 | 0.27 ** | |||||||
TWI | −0.23 ** | −0.23 ** | −0.40 ** | −0.22 ** | ||||||
SAVI | 0.31 ** | 0.19 * | 0.07 | 0.13 | −0.07 | |||||
NDVI | 0.43 ** | 0.21 * | 0.08 | 0.09 | −0.05 | 0.42 ** | ||||
RVI | −0.16 * | −0.16 * | −0.11 | −0.14 | 0.15 | −0.17 ** | −0.28 ** | |||
DVI | 0.21 * | 0.28 ** | 0.17 | 0.17 | −0.08 | 0.17 * | 0.26 ** | −0.32 ** | ||
RDVI | −0.29 ** | −0.25 * | −0.09 | −0.13 | 0.06 | 0.33 ** | 0.37 ** | −0.05 | 0.36 ** | |
MAT | 0.09 | 0.12 | −0.06 | −0.07 | 0.13 * | −0.15 * | −0.10 | 0.06 | 0.13 | |
MAP | 0.11 | −0.13 * | 0.08 | 0.06 | −0.12 * | 0.17 * | 0.19 * | −0.09 | 0.16 | 0.22 ** |
Model | Index | Min. | Median | Mean | Max. |
---|---|---|---|---|---|
MA | MAE | 1.38 | 1.39 | 1.40 | 1.41 |
RMSE | 1.51 | 1.52 | 1.52 | 1.54 | |
R2 | 0.24 | 0.26 | 0.27 | 0.31 | |
LCCC | 0.33 | 0.34 | 0.34 | 0.35 | |
MB | MAE | 1.27 | 1.31 | 1.32 | 1.33 |
RMSE | 1.47 | 1.48 | 1.49 | 1.50 | |
R2 | 0.31 | 0.33 | 0.34 | 0.36 | |
LCCC | 0.37 | 0.38 | 0.39 | 0.40 | |
MC | MAE | 0.87 | 0.88 | 0.89 | 0.91 |
RMSE | 0.96 | 0.97 | 0.97 | 0.98 | |
R2 | 0.53 | 0.55 | 0.57 | 0.59 | |
LCCC | 0.53 | 0.54 | 0.55 | 0.57 |
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Wang, S.; Zhou, M.; Zhuang, Q.; Guo, L. Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China. Remote Sens. 2021, 13, 4106. https://doi.org/10.3390/rs13204106
Wang S, Zhou M, Zhuang Q, Guo L. Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China. Remote Sensing. 2021; 13(20):4106. https://doi.org/10.3390/rs13204106
Chicago/Turabian StyleWang, Shuai, Mingyi Zhou, Qianlai Zhuang, and Liping Guo. 2021. "Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China" Remote Sensing 13, no. 20: 4106. https://doi.org/10.3390/rs13204106
APA StyleWang, S., Zhou, M., Zhuang, Q., & Guo, L. (2021). Prediction Potential of Remote Sensing-Related Variables in the Topsoil Organic Carbon Density of Liaohekou Coastal Wetlands, Northeast China. Remote Sensing, 13(20), 4106. https://doi.org/10.3390/rs13204106