Examining the Driving Factors of SOM Using a Multi-Scale GWR Model Augmented by Geo-Detector and GWPCA Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources and Index Selection
2.3. Methods
2.3.1. Geo-Detector
2.3.2. Geographically Weighted Principal Component Analysis (GWPCA)
2.3.3. Geographically Weighted Regression and Multi-Scale Geographically Weighted Regression (GWR and MGWR)
3. Results and Discussion
3.1. Global Statistics
3.2. Local Statistics
3.3. Geographical Detector
3.4. Geographically Weighted Principal Analysis
3.5. Modeling Comparison
3.6. Analysis of Coefficient Spatial Pattern
3.7. Limitations of the Study
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variables | q-Value | VIF | Reference |
---|---|---|---|
STN | 0.74 *** | 3.30 | [53] |
County administrative division | 0.58 *** | 3.08 | [55] |
Annual sunshine hours | 0.42 *** | 15.56 | [56] |
Annual precipitation | 0.37 *** | 12.57 | [49,56] |
Annual mean temperature | 0.35 *** | 6.61 | [57] |
Soil Subtype | 0.34 *** | 13.57 | [6] |
Soil Type | 0.32 *** | 14.63 | [6] |
Geomorphic types | 0.27 *** | 2.04 | [9] |
Cropping system | 0.26 *** | 1.49 | [58,59] |
C/N ratio | 0.25 *** | 1.99 | [60] |
Total Agricultural Machinery Power | 0.23 *** | 2.58 | [37] |
Rate of Compound Fertilizer Application | 0.22 *** | 5.31 | [58] |
pH | 0.22 *** | 2.77 | [2] |
Rate of Fertilizer Application | 0.21 *** | 8.77 | [58] |
AICc | R2 | RSS | MAE | |
---|---|---|---|---|
GWR | −8978.85 | 0.97 | 28.81 | 0.09 |
MGWR | −8360.19 | 0.97 | 36.91 | 0.25 |
GWPCA-GWR | −56.67 | 0.87 | 189.51 | 0.04 |
GWPCA-MGWR | 405.87 | 0.83 | 205.79 | 0.001 |
Model | Nugget | Sill | Nugget/Sill | Range (km) | |
---|---|---|---|---|---|
SOM | Gaussian | 0.08 | 0.91 | 8.84 | 835 |
GWR | Gaussian | 0.004 | 0.02 | 20.90 | 1093 |
MGWR | Gaussian | 0.01 | 0.02 | 59.81 | 980 |
GWPCA-GWR | Gaussian | 0.03 | 0.06 | 47.17 | 835 |
GWPCA-MGWR | Gaussian | 0.04 | 0.08 | 49.50 | 799 |
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Wang, Q.; Jiang, D.; Gao, Y.; Zhang, Z.; Chang, Q. Examining the Driving Factors of SOM Using a Multi-Scale GWR Model Augmented by Geo-Detector and GWPCA Analysis. Agronomy 2022, 12, 1697. https://doi.org/10.3390/agronomy12071697
Wang Q, Jiang D, Gao Y, Zhang Z, Chang Q. Examining the Driving Factors of SOM Using a Multi-Scale GWR Model Augmented by Geo-Detector and GWPCA Analysis. Agronomy. 2022; 12(7):1697. https://doi.org/10.3390/agronomy12071697
Chicago/Turabian StyleWang, Qi, Danyao Jiang, Yifan Gao, Zijuan Zhang, and Qingrui Chang. 2022. "Examining the Driving Factors of SOM Using a Multi-Scale GWR Model Augmented by Geo-Detector and GWPCA Analysis" Agronomy 12, no. 7: 1697. https://doi.org/10.3390/agronomy12071697