An Analysis of Prescribed Fire Activities and Emissions in the Southeastern United States from 2013 to 2020
<p>Percentages of the burned area from FINN for different burn types in southeastern states from FINN, 2013–2020. (State abbreviations: AL: Alabama; AR: Arkansas; GA: Georgia; FL: Florida; KY: Kentucky; LA: Louisiana; MS: Mississippi; NC: North Carolina; SC: South Carolina; TN: Tennessee; VA: Virginia; WV: West Virginia).</p> "> Figure 2
<p>Percentages of the burned area and number of records from permits for different burn types in southeastern states. Georgia permits cover 2015–2020. Florida and South Carolina permits cover 2013–2020. (State abbreviations: GA: Georgia; FL: Florida; SC: South Carolina).</p> "> Figure 3
<p>Statewide matching between FINN and permits in Florida, South Carolina, and Georgia. A linear regression with an intercept was conducted to fit the FINN burned area and permits burned area. The numbers of matching days were indicated as N values. Uncertainty of linear regression parameters was reported with a 95% confidence interval. Florida and South Carolina permits cover 2013–2020. Georgia permits cover 2015–2020. (State abbreviations: GA: Georgia; FL: Florida; SC: South Carolina).</p> "> Figure 4
<p>The total grid-based burned area from FINN and permit. FINN covered prescribed burns from 2013 to 2020. Georgia permits included records from 2015 to 2020. South Carolina and Florida permits included records from 2013 to 2020. Federal land boundaries are shown in blue. (State abbreviations: GA: Georgia; FL: Florida; SC: South Carolina).</p> "> Figure 5
<p>A linear regression between the FINN burned area and permitted burn area (unit: acres) of prescribed burns matched over 4 km grid cells in Florida, Georgia, and South Carolina. The black line is a 1:1 line and the red line is the regression line. Uncertainty of linear regression parameters was reported with a 95% confidence interval.</p> "> Figure 6
<p>A comparison between estimated FINN and BlueSky daily total prescribed burning emissions in the southeastern United States. The black line is a 1:1 line and the red line is the regression line. Uncertainty of the linear regression parameters was reported with a 95% confidence interval.</p> "> Figure 7
<p>A comparison between estimated FINN and BlueSky prescribed burning emissions for each record in FINN. The black line is a 1:1 line and the red line is the regression line. Uncertainty of the linear regression parameters was reported with a 95% confidence interval.</p> "> Figure 8
<p>A statewide comparison between estimated FINN and BlueSky prescribed burning emissions under 4 km grid definition. The black line is a 1:1 line and the red line is the regression line. Uncertainty of the linear regression parameters was reported with a 95% confidence interval.</p> "> Figure 9
<p>A comparison between permit and adjusted FINN daily total prescribed burning emissions in Florida, South Carolina, and Georgia. The black line is a 1:1 line and the red line is the regression line. Uncertainty of the linear regression parameters is reported with a 95% confidence interval.</p> "> Figure 10
<p>A comparison between permit and adjusted FINN-prescribed burning emissions in matched grid cells under a 4 km grid definition. The black line is a 1:1 line and the red line is the regression line. Uncertainty of the linear regression parameters was reported with a 95% confidence interval.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. State-Prescribed Burning Permit Records
2.2. Fire INventory from NCAR (FINN)
2.3. BlueSky Smoke Modeling Framework
3. Methods
3.1. Burn-Type Differentiation
3.1.1. Agricultural Burning Identification
3.1.2. Wildfire Detection Algorithm
3.2. Matching FINN-Prescribed Burning Records with Permits
3.2.1. Statewide Matching
3.2.2. Fire-to-Fire Matching
3.2.3. Grid-Based Burned Area Matching
4. Results
4.1. Burn-Type Differentiation
4.1.1. Agricultural Burning Identification
4.1.2. Wildfire Detection
4.1.3. Burn Types in FINN and Permits
4.2. Matching Prescribed Burning Records in FINN with Permits
4.3. Prescribed Burning Emissions
4.3.1. Emission Comparison between FINN and BlueSky
4.3.2. Prescribed Burning Emissions from Adjusted FINN Burned Area and Permits
4.3.3. Emissions Comparison with NEI
5. Discussion
5.1. Burn-Type Differentiation
5.2. Matching Prescribed Burning Records in FINN with Permits
5.3. Prescribed Burning Emissions
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Li, Z.; Maji, K.J.; Hu, Y.; Vaidyanathan, A.; O’Neill, S.M.; Odman, M.T.; Russell, A.G. An Analysis of Prescribed Fire Activities and Emissions in the Southeastern United States from 2013 to 2020. Remote Sens. 2023, 15, 2725. https://doi.org/10.3390/rs15112725
Li Z, Maji KJ, Hu Y, Vaidyanathan A, O’Neill SM, Odman MT, Russell AG. An Analysis of Prescribed Fire Activities and Emissions in the Southeastern United States from 2013 to 2020. Remote Sensing. 2023; 15(11):2725. https://doi.org/10.3390/rs15112725
Chicago/Turabian StyleLi, Zongrun, Kamal J. Maji, Yongtao Hu, Ambarish Vaidyanathan, Susan M. O’Neill, M. Talat Odman, and Armistead G. Russell. 2023. "An Analysis of Prescribed Fire Activities and Emissions in the Southeastern United States from 2013 to 2020" Remote Sensing 15, no. 11: 2725. https://doi.org/10.3390/rs15112725