Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Permissions
2.2. Field Data and UAS-Derived Canopy Height Model
2.3. Data Processing Overview
2.4. Segmentation Units/Parameters
2.5. Analytical Framework
2.6. Technique Agreement Measures
3. Results
3.1. Random Forest Models
3.2. Classification Approach—Accuracy Assessment
3.3. Site Type Characterization
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Type | Description | References |
---|---|---|
Error matrix | Cross tabulation of n × n array of land-cover classes. Columns represent the reference data; rows denote mapped land-cover class. | [51] |
Omission | Number of reference points left out from the intended mapped land-cover class. | [54] |
Commission | Number of reference points for a given class incorrectly mapped to a different land-cover class in the land-cover output. | [54] |
Agreement | Total number of correctly classified reference points in the final mapped output. | [54] |
Quantity | Amount of absolute difference between the reference map and a comparison map due to the less than perfect match in the proportions of the categories. | [51] |
Exchange | Exchange occurs as a one-to-one difference between two categories. These differences do not reflect the quantity differences of the classes, but rather a spatial mismatch. | [51] |
Shift | Shift represents the leftover disagreement after subtracting quantity and exchange differences from the total. These differences are due to exchanges occurring among >2 map classes. | [51] |
Cohen’s kappa (unweighted) | Measure of agreement between a land-cover map and a set of reference points, corrected for chance uncertainty. | [53] |
(a) Pixel-Based RF (P-RF) | |||||||
Error Matrix Unweighted | |||||||
Other | Shrub | Tree | |||||
Other | 42 | 6 | 0 | ||||
Shrub | 2 | 35 | 5 | ||||
Tree | 0 | 3 | 39 | ||||
Kappa Unweighted | |||||||
Value | ASE | z | Pr(>|z|) | ||||
0.8182 | 0.04253 | 19.24 | 1.79E-82 | ||||
Difference Table | |||||||
Category | Omission | Agreement | Commission | Quantity | Exchange | Shift | |
1 | Other | 2 | 42 | 6 | 4 | 4 | 0 |
2 | Shrub | 9 | 35 | 7 | 2 | 10 | 4 |
3 | Tree | 5 | 39 | 3 | 2 | 6 | 0 |
4 | Overall | 16 | 116 | 16 | 4 | 10 | 2 |
(b) Segment-Based RF (S-RF) | |||||||
Error Matrix Unweighted | |||||||
Other | Shrub | Tree | |||||
Other | 36 | 3 | 2 | ||||
Shrub | 8 | 37 | 10 | ||||
Tree | 0 | 4 | 32 | ||||
Kappa Unweighted | |||||||
Value | ASE | z | Pr(>|z|) | ||||
0.6932 | 0.05247 | 13.21 | 7.69E-40 | ||||
Difference Table | |||||||
Category | Omission | Agreement | Commission | Quantity | Exchange | Shift | |
1 | Other | 8 | 36 | 5 | 3 | 6 | 4 |
2 | Shrub | 7 | 37 | 18 | 11 | 14 | 0 |
3 | Tree | 12 | 32 | 4 | 8 | 8 | 0 |
4 | Overall | 27 | 105 | 27 | 11 | 14 | 2 |
(c) Canopy Height Threshold | |||||||
Error Matrix Unweighted | |||||||
Other | Shrub | Tree | |||||
Other | 43 | 15 | 0 | ||||
Shrub | 1 | 27 | 6 | ||||
Tree | 0 | 2 | 38 | ||||
Kappa Unweighted | |||||||
Value | ASE | z | Pr(>|z|) | ||||
0.7273 | 0.04947 | 14.7 | 6.30E-49 | ||||
Difference Table | |||||||
Category | Omission | Agreement | Commission | Quantity | Exchange | Shift | |
1 | Other | 1 | 43 | 15 | 14 | 2 | 0 |
2 | Shrub | 17 | 27 | 7 | 10 | 6 | 8 |
3 | Tree | 6 | 38 | 2 | 4 | 4 | 0 |
4 | Overall | 24 | 108 | 24 | 14 | 6 | 4 |
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Gaughan, A.E.; Kolarik, N.E.; Stevens, F.R.; Pricope, N.G.; Cassidy, L.; Salerno, J.; Bailey, K.M.; Drake, M.; Woodward, K.; Hartter, J. Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components. Remote Sens. 2022, 14, 551. https://doi.org/10.3390/rs14030551
Gaughan AE, Kolarik NE, Stevens FR, Pricope NG, Cassidy L, Salerno J, Bailey KM, Drake M, Woodward K, Hartter J. Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components. Remote Sensing. 2022; 14(3):551. https://doi.org/10.3390/rs14030551
Chicago/Turabian StyleGaughan, Andrea E., Nicholas E. Kolarik, Forrest R. Stevens, Narcisa G. Pricope, Lin Cassidy, Jonathan Salerno, Karen M. Bailey, Michael Drake, Kyle Woodward, and Joel Hartter. 2022. "Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components" Remote Sensing 14, no. 3: 551. https://doi.org/10.3390/rs14030551