A Linear Regression Model for Live Fuel Moisture Content Estimation during the Fire Season in Shrub Areas of the Province of Valencia in Spain Using Sentinel-2 Remote Sensing Data †
Abstract
:1. Introduction
2. Methods
2.1. Study Area
2.2. Field Data
2.3. Spectral Indices, Meteorological Parameters and Static Variables
2.4. Multivariate Linear Regression Models
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Model | Variable | Coefficient | p-Values | VIF | R2adj | RMSE | MAE |
---|---|---|---|---|---|---|---|
MLR_19_20_21 | Intercept | 124.222 | 0.519 | 11.13 | 8.54 | ||
sin_DOY | −12.3636 | <0.00 | 1.18564 | ||||
p60 | 0.066198 | <0.00 | 1.34219 | ||||
TCARI_OSAVI | −93.5614 | <0.00 | 1.70399 | ||||
VARI | 110.723 | <0.00 | 3.24571 | ||||
Mean_VARI | −120.596 | <0.00 | 2.97184 | ||||
Range_NDVI | −44.4529 | <0.00 | 1.08075 | ||||
MLR_19 * | Intercept | 191.091 | 0.658 * | 8.83 * | 6.52 * | ||
t60 | −2.55324 | <0.00 | 1.35301 | ||||
NDMI | 153.357 | <0.00 | 3.39691 | ||||
Mean_NDMI | −91.9045 | 0.0001 | 3.31885 | ||||
W7 | −4.72606 | <0.00 | 1.16423 |
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Pachacama-Vallejo, K.; Balaguer-Beser, Á. A Linear Regression Model for Live Fuel Moisture Content Estimation during the Fire Season in Shrub Areas of the Province of Valencia in Spain Using Sentinel-2 Remote Sensing Data. Environ. Sci. Proc. 2023, 28, 12. https://doi.org/10.3390/environsciproc2023028012
Pachacama-Vallejo K, Balaguer-Beser Á. A Linear Regression Model for Live Fuel Moisture Content Estimation during the Fire Season in Shrub Areas of the Province of Valencia in Spain Using Sentinel-2 Remote Sensing Data. Environmental Sciences Proceedings. 2023; 28(1):12. https://doi.org/10.3390/environsciproc2023028012
Chicago/Turabian StylePachacama-Vallejo, Kenneth, and Ángel Balaguer-Beser. 2023. "A Linear Regression Model for Live Fuel Moisture Content Estimation during the Fire Season in Shrub Areas of the Province of Valencia in Spain Using Sentinel-2 Remote Sensing Data" Environmental Sciences Proceedings 28, no. 1: 12. https://doi.org/10.3390/environsciproc2023028012