[HTML][HTML] Space-time landslide predictive modelling
Landslides are nearly ubiquitous phenomena and pose severe threats to people, properties,
and the environment in many areas. Investigators have for long attempted to estimate …
and the environment in many areas. Investigators have for long attempted to estimate …
我国林火发生预测模型研究进展.
高超， 林红蕾， 胡海清， 宋红 - Yingyong Shengtai Xuebao, 2020 - search.ebscohost.com
摘要通过文献回顾, 总结了国内林火发生预测模型的研究现状, 并从林火发生驱动因子,
林火发生概率预测模型, 林火发生频次预测模型和模型检验方法等方面进行归纳分析 …
林火发生概率预测模型, 林火发生频次预测模型和模型检验方法等方面进行归纳分析 …
A new approach of deep neural computing for spatial prediction of wildfire danger at tropical climate areas
Wildfire is an environmental hazard that has both local and global effects, causing economic
losses and various severe environmental problems. Due to the adverse effects of climate …
losses and various severe environmental problems. Due to the adverse effects of climate …
Spatiotemporal wildfire modeling through point processes with moderate and extreme marks
The supplementary material contains the following: a PDF document containing plots for the
inspection of posterior predictive densities, plots showing regionalized predictions, kernel …
inspection of posterior predictive densities, plots showing regionalized predictions, kernel …
Prediction of regional wildfire activity in the probabilistic Bayesian framework of Firelihood
Modeling wildfire activity is crucial for informing science‐based risk management and
understanding the spatiotemporal dynamics of fire‐prone ecosystems worldwide. Models …
understanding the spatiotemporal dynamics of fire‐prone ecosystems worldwide. Models …
Forest-fire-risk prediction based on random forest and backpropagation neural network of Heihe area in Heilongjiang province, China
C Gao, H Lin, H Hu - Forests, 2023 - mdpi.com
Forest fires are important factors that influence and restrict the development of forest
ecosystems. In this paper, forest-fire-risk prediction was studied based on random forest …
ecosystems. In this paper, forest-fire-risk prediction was studied based on random forest …
[HTML][HTML] Insights into the drivers and spatiotemporal trends of extreme mediterranean wildfires with statistical deep learning
Extreme wildfires continue to be a significant cause of human death and biodiversity
destruction within countries that encompass the Mediterranean Basin. Recent worrying …
destruction within countries that encompass the Mediterranean Basin. Recent worrying …
Integrated modeling of waterfowl distribution in western Canada using aerial survey and citizen science (eBird) data
A Adde, C Casabona i Amat, MJ Mazerolle… - …, 2021 - Wiley Online Library
Although the exceptional spatiotemporal extent of the Waterfowl Breeding Population and
Habitat Survey (WBPHS) has substantially contributed to our understanding of the ecology …
Habitat Survey (WBPHS) has substantially contributed to our understanding of the ecology …
Mapping the forest fire risk zones using artificial intelligence with risk factors data
V Sevinç - Environmental Science and Pollution Research, 2023 - Springer
Geographical information system data has been used in forest fire risk zone mapping
studies commonly. However, forest fires are caused by many factors, which cannot be …
studies commonly. However, forest fires are caused by many factors, which cannot be …
Gradient boosting with extreme-value theory for wildfire prediction
J Koh - Extremes, 2023 - Springer
This paper details the approach of the team Kohrrelation in the 2021 Extreme Value
Analysis data challenge, dealing with the prediction of wildfire counts and sizes over the …
Analysis data challenge, dealing with the prediction of wildfire counts and sizes over the …