## 6 Conclusions
The third level may include the boundaries of the burned areas, which would be valuable for improving and evaluating clustering algorithms in current fire emission products that combine FRP data from different satellites, such as FINN. Secondly, the burn-type differentiation algorithm can be improved by using statistical models or supervised machine learning models when sufficient reliable wildfire data and prescribed burning permit data are available. The occurrence probability of prescribed burns or wildfires could be related to meteorological conditions or locations, which can be utilized for training data-driven models. Furthermore, the algorithms and frameworks in this study can beapplied for agricultural burning and wildfire emissions estimation using corresponding emission factors. The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/rs15112725/s1](https://www.mdpi.com/article/10.3390/rs15112725/s1)]([https://www.mdpi.com/article/10.3390/rs15112725/s1](https://www.mdpi.com/article/10.3390/rs15112725/s1)), Table S1: Duration of prescribed burning: Algorithm S1: Wildfire detection algorithm; Algorithm S2: Nearest distance matching algorithm; Algorithm S3: Relaxation of distance and date matching algorithm; Figure S1: The number of clusters under different distances for clustering for FINN; Figure S2: The number of wildfires (clusters) under different combinations of spatial and temporal clustering distances; Figure S3: Percentage of the records number for different burn types in the southeastern states from FINN, 2013-2020; Figure S4: Statewide matching between FINN and permits in Florida, South Carolina, and Georgia; Figure S5: Daily total burned area in Florida, South Carolina, and Georgia; Figure S6: Matching performance under different selected distance thresholds; Figure S7: Matching performance under different combinations of relaxation date and relaxation distance; Figure S8: The number of matched pairs between FINN and permits under different combinations of relaxation date and relaxation distance; Figure S9: Total grid-based burned area of prescribed burnings from FINN and permit for 2013-2020; Figure S10: Yearly permit-based total CO emission in South Carolina, Georgia, and Florida from 2013-2020; Figure S11: Yearly permit-based total PM\({}_{2.5}\) emission in South Carolina, Georgia, and Florida from 2013-2020; Figure S12: Yearly permit-based total PM\({}_{10}\) emission in South Carolina, Georgia, and Florida from 2013-2020; Figure S13: Yearly adjusted FINN total CO emission in South Carolina, Georgia, and Florida from 2013-2020; Figure S14: Yearly adjusted FINN total PM\({}_{2.5}\) emission in the southeastern U.S. from 2013-2020; Figure S15: Yearly adjusted-FINN total PM\({}_{10}\) emission in southeastern U.S. during 2013-2020; Figure S16: PM\({}_{2.5}\) Emissions comparisons among FINN, FINN, adjusted FINN and NEI for 2014; Figure S17: PM\({}_{10}\) Emissions comparisons among FINN, adjusted FINN and NEI for 2014; Figure S18: CO Emissions comparisons among FINN, adjusted FINN and NEI for 2014; Figure S19: PM\({}_{2.5}\) Emissions comparisons among FINN, adjusted FINN and NEI for 2017; Figure S20: PM\({}_{10}\) Emissions comparisons among FINN, adjusted FINN and NEI for 2017; Figure S21: CO Emissions comparisons among FINN, adjusted FINN and NEI for 2017; Figure S22: Breakdown of total burned area from FINN by different burn types in southeastern states, 2013-2020; Figure S23: Breakdown of total burned area from permits by different burn types in Georgia, Florida, and South Carolina; Figure S24: Comparison between permit and BlueSky prescribed burning emissions with unadjusted FINN burned area in matched grid cells under a 4-km grid definition; Figure S25: States in the southeastern United States included in the study. Conceptualization: Z.L., Y.H., M.T.O., A.G.R., A.V. and S.M.O. ; methodology, Z.L., Y.H., M.T.O. and A.G.R. ; software, Z.L. and S.M.O. ; formal analysis, Z.L. ; investigation, Z.L. and M.T.O. ; supervision, M.T.O. and A.G.R.