Publication

Quan X, Chen R, Yebra M, Riaño D, de Dios VR, Li X, He B, Nolan RH, Griebel A, Boer MM, Sun Y. Sub-daily live fuel moisture content estimation from Himawari-8 data[J]. Remote Sensing of Environmental, 2024, 308: 114170

Li Y, Zhang Y, Quan X, He B, Veraverbeke S., Liao Z, Janssen T. A.J., Estimating forest litter fuel load by integrating remotely sensed foliage phenology and modeled litter decomposition[J]. Remote Sensing of Environmental, 2025, 317: 114526

Fan C, He B, Yin J, Chen R, Zhang H. Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation[J]. GIScience & Remote Sengsing, 2024, 61(1):2324556

Chen R, He B, Li Y, Zhang Y, Liao Z, Fan C, Yin J, Zhang H. Incorporating fire spread simulation and machine learning algorithms to estimate crown fire potential for pine forests in Sichuan, China[J]. International Journal of Applied Earth Observation and

Chen R, He B, Quan X, Lai X, Fan C. Improving wildfire probability modeling by integrating dynamic-step weather variables over Northwestern Sichuan, China[J]. International Journal of Disaster Risk Science, 2023, 14(2): 313-325.

何彬彬; 陈瑞; 全兴文; 姚劲松; 殷长明; 王子励; 张启明; 杨帅. 森林草原火灾遥感监测预警技术及示范应用[J]. 电子科技大学学报, 2024,53(5): 698-705.

1 Forest fire Quan X, Chen R, Yebra M, Riaño D, de Dios VR, Li X, He B, Nolan RH, Griebel A, Boer MM, Sun Y. Sub-daily live fuel moisture content estimation from Himawari-8 data[J]. Remote Sensing of Environmental, 2024, 308: 114170 2025-04-18
2 Forest fire Li Y, Zhang Y, Quan X, He B, Veraverbeke S., Liao Z, Janssen T. A.J., Estimating forest litter fuel load by integrating remotely sensed foliage phenology and modeled litter decomposition[J]. Remote Sensing of Environmental, 2025, 317: 114526 2025-04-18
3 Forest fire Fan C, He B, Yin J, Chen R, Zhang H. Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation[J]. GIScience & Remote Sengsing, 2024, 61(1):2324556 2025-04-18
4 Forest fire Chen R, He B, Li Y, Zhang Y, Liao Z, Fan C, Yin J, Zhang H. Incorporating fire spread simulation and machine learning algorithms to estimate crown fire potential for pine forests in Sichuan, China[J]. International Journal of Applied Earth Observation and 2025-04-18
5 Forest fire Chen R, He B, Quan X, Lai X, Fan C. Improving wildfire probability modeling by integrating dynamic-step weather variables over Northwestern Sichuan, China[J]. International Journal of Disaster Risk Science, 2023, 14(2): 313-325. 2025-04-18
6 Forest fire 何彬彬; 陈瑞; 全兴文; 姚劲松; 殷长明; 王子励; 张启明; 杨帅. 森林草原火灾遥感监测预警技术及示范应用[J]. 电子科技大学学报, 2024,53(5): 698-705. 2025-04-18
7 Earthquake Ding, Y., Wang, Z., Qi, Y. et al. Characteristics and mechanism of MBT anomaly of Karakum desert related with the Hindu Kush earthquake. npj Nat. Hazards 2, 10 (2025). https://doi.org/10.1038/s44304-025-00060-z 2025-04-16
8 Earthquake 丁逸凡，吴立新，齐源，毛文飞.2024.2022年6月阿富汗帕克提卡M6.0级地震前微波亮温异常的多态性及其归因辨析.遥感学报，28（10）： 2621-2631 DOI： 10.11834/jrs.20243019. 2025-04-16
9 Flood Jiao Z, Zhang Z, Wu L. Knowledge-Driven Intelligent Extraction of Dynamic Flood Information Using SAR Image[C]/IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024: 3203-3206. 2025-04-15
10 Flood Jiao Z, Zhang Z, Zhang A, et al. Modified Multiple Spectrum-based Vegetation Index (MMSVI): A reflectance index with high spatio-temporal generalization ability[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024. 2025-04-15
11 Flood Jiao Z, Zhang Z, Wu L. SAR-based dynamic information retrieving of the Beijing-Tianjin-Hebei flood-inundation happened in July 2023, North China[J]. Geomatics, Natural Hazards and Risk, 2024, 15(1): 2366361. 2025-04-15
12 Flood Huang N, Fu S, Chen B, et al. Assessing the Performance of Water Vapor Products from ERA5 and MERRA-2 during Heavy Rainfall in the Guangxi Region of China[J]. Atmosphere, 2024, 15(3): 306. 2025-04-15
13 Flood ​吴皓, 陈必焰, 黄宁, 等. 湖南省大区域三维水汽层析反演及降雨预报应用[J]. 中国防汛抗旱, 2024, 34(4): 8-16. 2025-04-15
14 Landslide ​Yang Y, Miao Z, Zhang H, et al. Lightweight attention-guided YOLO with level set layer for landslide detection from optical satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17: 3543-3559. 2025-04-15
15 Landslide Yang Y, Miao Z, Li X, et al. LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction[J]. GIScience & Remote Sensing, 2024, 61(1): 2416727. 2025-04-15
16 Landslide ​Chen S, Wu L, Miao Z. Regional seismic landslide susceptibility assessment considering the rock mass strength heterogeneity[J]. Geomatics, Natural Hazards and Risk, 2023, 14(1): 1-27. 2025-04-15
17 Landslide Feng H, Miao Z, Hu Q. Study on the uncertainty of machine learning model for earthquake-induced landslide susceptibility assessment[J]. Remote Sensing, 2022, 14(13): 2968. 2025-04-15
18 Landslide Miao Z, Peng R, Wang W, et al. Integrating data modality and statistical learning methods for earthquake-induced landslide susceptibility mapping[J]. Applied Sciences, 2022, 12(3): 1760. 2025-04-15
19 Landslide Chen S, Miao Z, Wu L, et al. A one-class-classifier-based negative data generation method for rapid earthquake-induced landslide susceptibility mapping[J]. Frontiers in Earth Science, 2021, 9: 609896. 2025-04-15
20 Volcano Mao, W., Wu, L., Xu, Y., Yao, R., Lu, J., Sun, L., & Qi, Y. (2022). Pressure-stimulated rock current as loading diorite to failure: Particular variation and holistic mechanisms. Journal of Geophysical Research: Solid Earth, 127, e2022JB024931. https://doi 2025-04-04
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