Lifu Shu
Biographic Data
| ID | 7991868 |
|---|---|
| NAME | Lifu Shu |
| GIVEN NAMES | Lifu |
| FAMILY NAME | Shu |
| SIGNATURE | SHU L |
| AFFILIATIONS | Chinese Academy of Forestry |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A hybrid deep learning model for cross-seasonal forecasting of forest fire occurrence from long-term survey data
Climate change is exacerbating global forest fire regimes, creating an urgent demand for sophisticated predictive modeling tools. Focusing on the climatically sensitive and ecologically critical Daxing'anling Mountains in China, this study develops a hybrid deep learning framework termed CNN-ATT-SYNERGY. This model integrates Convolutional Neural Networks (CNN) with attention mechanisms to fuse multi-source environmental covariates, encompassing …
Disparities in wildfire regimes across China's borders
Border zones between countries are among the world regions with large spatial variability in wildfires. However, our understanding of fire regimes in these areas, particularly quantitative assessments of cross-border fire risk, remains limited. This study examines fire regimes and their driving factors along China's extensive land borders, which encompass the world's longest border and the second-highest number of neighboring countries. Utilizing…
Previous Atlantic Multidecadal Oscillation (AMO) modulates the lightning-ignited fire regime in the boreal forest of Northeast China
Lightning-ignited fire is sensitive to climatic change and responsible for large fires in boreal forests. In addition to global-warming caused fire increase, large-scale climate oscillations have significantly contributed to fire variability. However, the leading climate oscillation driving lightning-ignited fire and the mechanisms connecting regional and large-scale climate in the boreal forest of Northeast China, the most fire-prone biome of Ch…
Significantly lower summer minimum temperature warming trend on the southern Tibetan Plateau than over the Eurasian continent since the Industrial Revolution
Summer temperature dominates environmental degradation and water resource availability on the Tibetan Plateau (TP), affecting glacier melting, permafrost degradation, desertification and streamflow, etc. Extending summer temperature records back before the instrumental period is fundamentally important for climatic and environmental studies over long timescales. By pooling 39 tree-ring width records from the TP that show significant ( P < 0.05) c…
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Significantly lower summer minimum temperature warming trend on the southern Tibetan Plateau than over the Eurasian continent since the Industrial Revolution
Summer temperature dominates environmental degradation and water resource availability on the Tibetan Plateau (TP), affecting glacier melting, permafrost degradation, desertification and streamflow, etc. Extending summer temperature records back before the instrumental period is fundamentally important for climatic and environmental studies over long timescales. By pooling 39 tree-ring width records from the TP that show significant ( P < 0.05) c…
Previous Atlantic Multidecadal Oscillation (AMO) modulates the lightning-ignited fire regime in the boreal forest of Northeast China
Lightning-ignited fire is sensitive to climatic change and responsible for large fires in boreal forests. In addition to global-warming caused fire increase, large-scale climate oscillations have significantly contributed to fire variability. However, the leading climate oscillation driving lightning-ignited fire and the mechanisms connecting regional and large-scale climate in the boreal forest of Northeast China, the most fire-prone biome of Ch…
Disparities in wildfire regimes across China's borders
Border zones between countries are among the world regions with large spatial variability in wildfires. However, our understanding of fire regimes in these areas, particularly quantitative assessments of cross-border fire risk, remains limited. This study examines fire regimes and their driving factors along China's extensive land borders, which encompass the world's longest border and the second-highest number of neighboring countries. Utilizing…
A hybrid deep learning model for cross-seasonal forecasting of forest fire occurrence from long-term survey data
Climate change is exacerbating global forest fire regimes, creating an urgent demand for sophisticated predictive modeling tools. Focusing on the climatically sensitive and ecologically critical Daxing'anling Mountains in China, this study develops a hybrid deep learning framework termed CNN-ATT-SYNERGY. This model integrates Convolutional Neural Networks (CNN) with attention mechanisms to fuse multi-source environmental covariates, encompassing …
Climate change (3 works) · Fire effects on ecosystems (3 works) · Atmospheric sciences (2 works) · Climate variability and models (2 works) · Climatology (2 works) · Environmental Science (2 works) · Fire Detection and Safety Systems (2 works) · Fire regime (2 works) · Geography (2 works) · Geology (2 works)