A5100409624- Fire effects on ecosystems
- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Fire Detection and Safety Systems
- Plant Water Relations and Carbon Dynamics
- Cryospheric studies and observations
- Climate variability and models
- Meteorological Phenomena and Simulations
- Impact of Light on Environment and Health
- Remote Sensing and LiDAR Applications
Nanjing University of Information Science and Technology
2024
China Meteorological Administration
2023
Chinese Academy of Meteorological Sciences
2023
Northeast Forestry University
2021-2022
The simulation of forest fire spread is a key problem for the management fire, and Cellular Automata (CA) has been used to simulate complex mechanism long time. CA driven by rate (ROS), which hard estimate, because some input parameters current ROS model cannot be provided with high precision, so approach not well applied yet in system date. LSTM-CA using LSTM proposed this paper. Based on interaction between wind S-LSTM proposed, takes full advantage time dependency ROS. estimated...
An in-depth exploration of fractional vegetation coverage (FVC) changes and driving mechanisms in the Yangtze River Delta (YRD) is crucial for maintaining regional ecological health achieving sustainable development. We therefore calculate FVC YRD from 2012 to 2021 based on MODIS NDVI data, analyze its spatiotemporal evolution. Multiple regression residual analysis geographic detector model were used along with various auxiliary data further explore a hierarchical manner. Finally, Hurst...
Modeling forest fire spread is a very complex problem, and the existing models usually need some input parameters which are hard to get. How predict time series of rate based on passed may be key problem break through current technical bottleneck. In process spreading, wind speed would affect each other. this paper, three kinds network Long Short-Term Memory (LSTM) designed rate, exploring interaction between wind. order train these LSTM-based validate their effectiveness prediction, several...
Background: The spread of forest fire is a complex natural phenomenon. cellular automata(CA) common model spread, which fails to combine the unique combustion properties spreading, resulting in inaccurate simulation results. In order improve accuracy simulation, Rothermel rate formula simplified and combined with CA form multi-dimensional automata(MD-CA) different each cell. formulas eight directions are obtained through training datasets, testing datasets used compare results model, MD-CA...