Hourly biomass burning emissions product from blended geostationary and polar-orbiting satellites for air quality forecasting applications

F Li, X Zhang, S Kondragunta, X Lu, I Csiszar… - Remote Sensing of …, 2022 - Elsevier
Biomass burning influences atmospheric composition and regional air quality. The hourly
biomass-burning emissions are usually required by air quality models, yet most available …

[HTML][HTML] Mitigating underestimation of fire emissions from the Advanced Himawari Imager: A machine learning and multi-satellite ensemble approach

Y Kang, J Im - International Journal of Applied Earth Observation and …, 2024 - Elsevier
The accurate estimation of biomass burning emissions has played a crucial role in air quality
and climate forecast modeling. Satellite-based fire radiative power (FRP) has proven …

A deep learning framework: Predicting fire radiative power from the combination of polar-orbiting and geostationary satellite data during wildfire spread

Z Dong, F Zhao, G Wang, Y Tian… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
Fire radiative power (FRP) is a key indicator for evaluating the intensity of wildfires, unlike
traditional real-time fire lines or combustion areas that only provide binary information, and …

[HTML][HTML] Forest fire risk prediction based on stacking ensemble learning for yunnan Province of China

Y Li, G Li, K Wang, Z Wang, Y Chen - Fire, 2024 - mdpi.com
Forest fire risk prediction is essential for building a forest fire defense system. Ensemble
learning methods can avoid the problem of difficult model selection for disaster susceptibility …

[HTML][HTML] One year of near-continuous fire monitoring on a continental scale: Comparing fire radiative power from polar-orbiting and geostationary observations

K Chatzopoulos-Vouzoglanis, KJ Reinke… - International Journal of …, 2023 - Elsevier
Geostationary and polar-orbiting remote sensors have different opportunities to observe
wildfires. While polar-orbiting sensors have been favoured in wildfire observations …

Real-time wildfire detection algorithm based on VIIRS fire product and Himawari-8 data

D Zhang, C Huang, J Gu, J Hou, Y Zhang, W Han… - Remote Sensing, 2023 - mdpi.com
Wildfires have a significant impact on the atmosphere, terrestrial ecosystems, and society.
Real-time monitoring of wildfire locations is crucial in fighting wildfires and reducing human …

Early stage Forest fire detection from Himawari-8 AHI images using a modified MOD14 algorithm combined with machine learning

N Maeda, H Tonooka - Sensors, 2022 - mdpi.com
The early detection and rapid extinguishing of forest fires are effective in reducing their
spread. Based on the MODIS Thermal Anomaly (MOD14) algorithm, we propose an early …

Key emergency response technologies for abrupt air pollution accidents in China

J Duan, S Mao, P **e, J Lang, A Li, J Tong… - Journal of …, 2023 - Elsevier
Abrupt air pollution accidents can endanger people's health and destroy the local ecological
environment. The appropriate emergency response can minimize the harmful effects of …

Global emissions inventory from open biomass burning (GEIOBB): Utilizing fengyun–3D global fire spot monitoring data

Y Liu, J Chen, Y Shi, W Zheng, T Shan… - Earth System Science …, 2024 - essd.copernicus.org
Open biomass burning (OBB) significantly affects regional and global air quality, climate
change, and human health. It is susceptible to fire types, including forests, shrublands …

Brown Carbon Emissions from Biomass Burning under Simulated Wildfire and Prescribed-Fire Conditions

CK Glenn, O El Hajj, Z McQueen, RP Poland… - ACS Es&t …, 2024 - ACS Publications
We investigated the light-absorption properties of brown carbon (BrC) as part of the Georgia
Wildland-Fire Simulation Experiment. We constructed fuel beds representative of three …