Geographically Weighted Regression Enhances Spectral Diversity–Biodiversity Relationships in Inner Mongolian Grasslands
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Analysis Framework
2.3. In Situ Biodiversity Survey
2.4. Drone Multispectral Data Acquisition
2.5. Spectral Diversity (SD) Metrics
2.6. Statistical Analysis
2.6.1. Global Linear Statistical Analysis
2.6.2. Spatial Statistical Analysis
3. Results
3.1. Global Linear Regression Modeling Results
3.2. Geographically Weighted Regression (GWR) Modeling Results
3.3. Predicted Biodiversity Indices Derived from Geographically Weighted Regression
4. Discussion
4.1. GWR Model Improved the Performance of Predicting Biodiversity Using SD Metrics
4.2. Complexity of Spectral Diversity
4.3. Future Work
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Experimental Areas | Administrative Region | Grassland Type | Coordinates | Orientation | Size (L × W, m) | Area (m2) |
---|---|---|---|---|---|---|
CQ | Hulunbuir | meadow steppe | 49.57966° N, 118.93102° E | 27° NE | 290 × 80 | 23,200 |
DQ | Hulunbuir | meadow steppe | 49.88535° N, 119.31487° E | 0° NE | 300 × 98 | 29,400 |
HZ | Hulunbuir | meadow steppe | 49.30057° N, 119.99951° E | 86° NW | 490 × 67 | 32,830 |
MD | Xilingol | typical steppe | 44.26940° N, 116.33487° E | 15° NW | 302 × 88 | 26,576 |
XZ | Xilingol | meadow steppe | 43.38046° N, 116.20906° E | 87° NW | 317 × 96 | 30,432 |
XJ | Xilingol | typical steppe | 44.06262° N, 116.86243° E | 77° NW | 224 × 82 | 18,368 |
Biodiversity Indices | Definition | Equation |
---|---|---|
Species richness (Richness) | The number of species in the community [42]. | The number of species in the community. |
Shannon–Wiener diversity index (Shannon) | An index considering species richness and relative abundance [45]. | , where is the relative abundance of the i-th species. |
Margalef richness index (Margalef) | A normalized measure of species richness that incorporates abundance [46]. | , where N is the total species abundance in the community. |
SD Metrics | Definition |
---|---|
Coefficient of variation | The average coefficient of variation in the band values in the quadrat [50,51]. |
Spectral angle mapper | The angle between the multidimensional vector of the pixel reflectance and the average spectral vector [52]. |
Standard deviation of NDVI | The standard deviation of the normalized difference vegetation index (NDVI) [53]. |
Spectral centroid distance | The average of the Euclidean distance from all spectral vectors to the mean spectral reflectance in the quadrat [54]. |
Spectral information divergence | The spectral information divergence compares the similarity between two pixels by measuring the probability difference between two corresponding spectral features [55]. |
Convex hull volume | The volume of the convex hull of the first three principal components of the pixels in the quadrat in a three-dimensional space [56,57]. |
Convex hull area | The area enclosed by the smallest convex polygon of the mean band reflectance and the corresponding pixel reflectance values in the quadrat [42]. |
Response Variables | Explanatory Variables | Pearson’s r | Linear Regression | GWR | ||
---|---|---|---|---|---|---|
R2 | R2 | R2 Adjusted | AICc | |||
Margalef | Convex hull area | 0.29 *** | 0.09 | 0.59 | 0.50 | 285.31 |
Convex hull volume | 0.25 *** | 0.06 | 0.56 | 0.50 | 282.01 | |
Coefficient of variation | 0.31 *** | 0.10 | 0.57 | 0.50 | 282.14 | |
Standard deviation of NDVI | 0.21 *** | 0.04 | 0.55 | 0.48 | 288.48 | |
Spectral angle mapper | 0.22 *** | 0.05 | 0.55 | 0.48 | 287.41 | |
Spectral centroid distance | 0.23 *** | 0.05 | 0.43 | 0.40 | 300.91 | |
Spectral information divergence | 0.24 *** | 0.06 | 0.54 | 0.47 | 290.34 | |
Richness | Convex hull area | 0.21 *** | 0.05 | 0.57 | 0.49 | 777.89 |
Convex hull volume | 0.20 *** | 0.04 | 0.56 | 0.50 | 774.32 | |
Coefficient of variation | 0.23 *** | 0.05 | 0.57 | 0.50 | 774.41 | |
Standard deviation of NDVI | 0.16 ** | 0.02 | 0.55 | 0.48 | 780.94 | |
Spectral angle mapper | 0.16 ** | 0.03 | 0.55 | 0.48 | 779.66 | |
Spectral centroid distance | 0.20 *** | 0.04 | 0.42 | 0.38 | 797.82 | |
Spectral information divergence | 0.16 ** | 0.02 | 0.54 | 0.47 | 783.34 | |
Shannon | Convex hull area | 0.21 *** | 0.05 | 0.55 | 0.48 | 118.50 |
Convex hull volume | 0.17 ** | 0.03 | 0.56 | 0.50 | 109.55 | |
Coefficient of variation | 0.23 *** | 0.05 | 0.56 | 0.49 | 114.74 | |
Standard deviation of NDVI | 0.17 ** | 0.03 | 0.52 | 0.45 | 124.68 | |
Spectral angle mapper | 0.17 ** | 0.03 | 0.53 | 0.46 | 123.34 | |
Spectral centroid distance | 0.18 ** | 0.03 | 0.42 | 0.39 | 132.16 | |
Spectral information divergence | 0.18 ** | 0.03 | 0.52 | 0.45 | 125.05 |
Variable | Moran I | Z-Score | p-Value |
---|---|---|---|
Species richness | 0.47 | 14.90 | 0.00 |
Shannon–Wiener diversity index | 0.47 | 15.00 | 0.00 |
Margalef richness index | 0.47 | 14.98 | 0.00 |
Coefficient of variation | 0.74 | 23.23 | 0.00 |
Spectral angle mapper | 0.70 | 22.09 | 0.00 |
Standard deviation of NDVI | 0.66 | 21.01 | 0.00 |
Spectral centroid distance | 0.79 | 25.03 | 0.00 |
Spectral information divergence | 0.59 | 18.61 | 0.00 |
Convex hull area | 0.71 | 22.51 | 0.00 |
Convex hull volume | 0.64 | 20.24 | 0.00 |
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Dai, Y.; Wan, H.; Lu, L.; Wan, F.; Duan, H.; Xiao, C.; Zhang, Y.; Zhang, Z.; Wang, Y.; Shi, P.; et al. Geographically Weighted Regression Enhances Spectral Diversity–Biodiversity Relationships in Inner Mongolian Grasslands. Diversity 2025, 17, 541. https://doi.org/10.3390/d17080541
Dai Y, Wan H, Lu L, Wan F, Duan H, Xiao C, Zhang Y, Zhang Z, Wang Y, Shi P, et al. Geographically Weighted Regression Enhances Spectral Diversity–Biodiversity Relationships in Inner Mongolian Grasslands. Diversity. 2025; 17(8):541. https://doi.org/10.3390/d17080541
Chicago/Turabian StyleDai, Yu, Huawei Wan, Longhui Lu, Fengming Wan, Haowei Duan, Cui Xiao, Yusha Zhang, Zhiru Zhang, Yongcai Wang, Peirong Shi, and et al. 2025. "Geographically Weighted Regression Enhances Spectral Diversity–Biodiversity Relationships in Inner Mongolian Grasslands" Diversity 17, no. 8: 541. https://doi.org/10.3390/d17080541
APA StyleDai, Y., Wan, H., Lu, L., Wan, F., Duan, H., Xiao, C., Zhang, Y., Zhang, Z., Wang, Y., Shi, P., & Sun, X. (2025). Geographically Weighted Regression Enhances Spectral Diversity–Biodiversity Relationships in Inner Mongolian Grasslands. Diversity, 17(8), 541. https://doi.org/10.3390/d17080541