Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Field and Satellite Data
2.3. Landsat TM Image Analysis
2.4. Biomass Prediction
2.5. Statistical Analyses
3. Results
3.1. Biomass Prediction from Image Texture
3.2. Biomass Prediction in Areas of Forest Disturbance
4. Discussion
4.1. Biomass Prediction from Image Texture
4.2. Texture Analysis for Local Biomass Maps
5. Conclusions
- Biomass models constructed including image texture variables are more strongly correlated with observed biomass than those constructed using physical and spectral information alone.
- Our texture-based biomass model is sensitive to changes in forest biomass following disturbance such as logging and wildfire; the texture-based model we present in this paper is better able to predict the direction and magnitude of biomass change following disturbance than biomass models constructed without the use of image texture.
- Because the Landsat data used to construct this map are available on sub-annual timescales, texture may be an important tool for creating and updating biomass maps following local forest disturbance or land management actions.
- The methods we present here are widely applicable across the US because we use entirely publically available data processed with relatively simple analytical routines.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Parameters | Network Architecture | r | AIC | RMSE | CV-RMSE |
---|---|---|---|---|---|
6, 1, 8, Slope | 4-10-1 | 0.86 | 199.0 | 45.6 | 0.31 |
1, 6, 7, Slope, 8, 5 | 6-9-1 | 0.81 | 204.2 | 52.7 | 0.36 |
1, 8, Slope, 6, 5 | 5-6-1 | 0.84 | 207.4 | 51.9 | 0.36 |
1, Slope, 6 | 3-4-1 | 0.78 | 209.1 | 58.1 | 0.40 |
1, Slope, Aspect, 6, NDVI | 5-9-1 | 0.79 | 211.7 | 56.4 | 0.39 |
Elevation, NDVI, Aspect, Slope | 4-8-1 | 0.57 | 224.9 | 76.5 | 0.53 |
Elevation, Slope, Aspect | 3-3-1 | 0.44 | 224.9 | 79.7 | 0.55 |
Elevation, Aspect, Slope, EVI, Precipitation | 5-9-1 | 0.51 | 226.7 | 76.3 | 0.53 |
Elevation, Aspect, Slope, EVI | 4-5-1 | 0.43 | 227.6 | 80.8 | 0.56 |
Vegetation Type, Aspect, Slope, Elevation | 9-3-1 | 0.34 | 229.5 | 83.9 | 0.58 |
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Kelsey, K.C.; Neff, J.C. Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery. Remote Sens. 2014, 6, 6407-6422. https://doi.org/10.3390/rs6076407
Kelsey KC, Neff JC. Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery. Remote Sensing. 2014; 6(7):6407-6422. https://doi.org/10.3390/rs6076407
Chicago/Turabian StyleKelsey, Katharine C., and Jason C. Neff. 2014. "Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery" Remote Sensing 6, no. 7: 6407-6422. https://doi.org/10.3390/rs6076407