Fengjun Zhao
Biographic Data
| ID | 7510635 |
|---|---|
| NAME | Fengjun Zhao |
| GIVEN NAMES | Fengjun |
| FAMILY NAME | Zhao |
| SIGNATURE | ZHAO F |
| AFFILIATIONS | Chinese Academy of Forestry |
| ORCID | 0000-0001-7795-9795 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| 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…
SPPD
As one of China′s most precious cultural relics, the excavation and protection of the Terracotta Warriors pose significant challenges to archaeologists. A fairly common situation in the excavation is that the Terracotta Warriors are mostly found in the form of fragments, and manual reassembly among numerous fragments is laborious and time-consuming. This work presents a fracture-surface-based reassembling method, which is composed of SiamesePoint…
Root system plays an important role in responses of plant to drought in the steppe of China
In the temperate grasslands of northern China, there exists a large range of soil texture. However, previous studies have mainly focused on the effect of climate water deficit on plant traits and have paid little attention to the effect of soil water deficit because grasses tend to use rainfall water directly. We measured eight drought‐related plant traits of 12 widely distributed perennial species in the temperate grassland in northern China and…
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…
Early- and mid-Holocene palaeoenvironments as revealed by mineral magnetic, geochemical and palynological data of sediments from Bai Nuur and Ulan Nuur, southeastern inner Mongolia Plateau, China
How did the forest respond to Holocene climate drying at the forest–steppe ecotone in northern China
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How did the forest respond to Holocene climate drying at the forest–steppe ecotone in northern China
Early- and mid-Holocene palaeoenvironments as revealed by mineral magnetic, geochemical and palynological data of sediments from Bai Nuur and Ulan Nuur, southeastern inner Mongolia Plateau, China
SPPD
As one of China′s most precious cultural relics, the excavation and protection of the Terracotta Warriors pose significant challenges to archaeologists. A fairly common situation in the excavation is that the Terracotta Warriors are mostly found in the form of fragments, and manual reassembly among numerous fragments is laborious and time-consuming. This work presents a fracture-surface-based reassembling method, which is composed of SiamesePoint…
Root system plays an important role in responses of plant to drought in the steppe of China
In the temperate grasslands of northern China, there exists a large range of soil texture. However, previous studies have mainly focused on the effect of climate water deficit on plant traits and have paid little attention to the effect of soil water deficit because grasses tend to use rainfall water directly. We measured eight drought‐related plant traits of 12 widely distributed perennial species in the temperate grassland in northern China and…
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 …
Geology (4 works) · Ecology (3 works) · Environmental Science (3 works) · Fire effects on ecosystems (3 works) · Geography (3 works) · Archaeology (2 works) · Biology (2 works) · Climate change (2 works) · Fire Detection and Safety Systems (2 works) · Fire regime (2 works)