Chunquan Fan

According to our database1, Chunquan Fan authored at least 10 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Incorporating fire spread simulation and machine learning algorithms to estimate crown fire potential for pine forests in Sichuan, China.
Int. J. Appl. Earth Obs. Geoinformation, 2024

2023
Quantification of Climate-Wildfire Relationships Taking Into of Spatiotemporal Heterogeneity at Regional Scale: The Subtropical China Case.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Extraction of Row Centerline at the Early Stage of Corn Growth Based on UAV Images.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Rice False Smut Extraction Based on the Combination of Instability Index Between Classes and Correlation Coefficient of UAV Hyperspectral Band Selection.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Estimation of Live Fuel Moisture Content Based on A Machine Learning Approach.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Global Live Fuel Moisture Content Dynamic Monitoring Based on Modis Data Observation.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Forecasting Dead Fuel Moisture Content at Spatial Scales Using a Process-Based Model with Global Forecast System Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Estimation of Probability Density of Potential Fire Intensity Using Quantile Regression and Bi-Directional Long Short-Term Memory.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Modeling Potential Wildfire Behavior Characteristics Using Multi-Source Remotely Sensed Data: Towards Wildfire Hazard Assessment.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2021
Predicting 1-H Dead Fuel Moisture Content at Regional Scales Using Machine Learning from Himawari-8 Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021


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