Works matching Forest fires
Results: 5000
Forest Fire Patterns and Lightning-Caused Forest Fire Detection in Heilongjiang Province of China Using Satellite Data.
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- Fire (2571-6255), 2023, v. 6, n. 4, p. 166, doi. 10.3390/fire6040166
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我国近年森林火灾情况及森林防火政策措施简析.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 7, doi. 10.3969/j.issn.1002-2511.2023.02.002
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Deep Learning-Based Forest Fire Risk Research on Monitoring and Early Warning Algorithms.
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- Fire (2571-6255), 2024, v. 7, n. 4, p. 151, doi. 10.3390/fire7040151
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Forest Fire Driving Factors and Fire Risk Zoning Based on an Optimal Parameter Logistic Regression Model: A Case Study of the Liangshan Yi Autonomous Prefecture, China.
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- Fire (2571-6255), 2023, v. 6, n. 9, p. 336, doi. 10.3390/fire6090336
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基于VIIRS火点数据和FARSITE系统的 森林火灾蔓延模拟.
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- Journal of Remote Sensing, 2022, v. 26, n. 8, p. 1575, doi. 10.11834/jrs.20219427
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中国林火卫星遥感预警监测技术研究进展.
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- Journal of Remote Sensing, 2020, v. 24, n. 5, p. 511, doi. 10.11834/jrs.20209135
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Framework to Create Inventory Dataset for Disaster Behavior Analysis Using Google Earth Engine: A Case Study in Peninsular Malaysia for Historical Forest Fire Behavior Analysis.
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- Forests (19994907), 2024, v. 15, n. 6, p. 923, doi. 10.3390/f15060923
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Forest Fire Spread Simulation and Fire Extinguishing Visualization Research.
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- Forests (19994907), 2023, v. 14, n. 7, p. 1371, doi. 10.3390/f14071371
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STPM_SAHI: A Small-Target Forest Fire Detection Model Based on Swin Transformer and Slicing Aided Hyper Inference.
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- Forests (19994907), 2022, v. 13, n. 10, p. 1603, doi. 10.3390/f13101603
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Forest Management Units' Performance in Forest Fire Management Implementation in Central Kalimantan and South Sumatra.
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- Forests (19994907), 2022, v. 13, n. 6, p. 894, doi. 10.3390/f13060894
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Forest Fire Causes and Motivations in the Southern and South-Eastern Europe through Experts' Perception and Applications to Current Policies.
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- Forests (19994907), 2022, v. 13, n. 4, p. 562, doi. 10.3390/f13040562
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Spatiotemporal Dynamics and Climate Influence of Forest Fires in Fujian Province, China.
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- Forests (19994907), 2022, v. 13, n. 3, p. 423, doi. 10.3390/f13030423
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Adaptive Forest Fire Spread Simulation Algorithm Based on Cellular Automata.
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- Forests (19994907), 2021, v. 12, n. 11, p. 1431, doi. 10.3390/f12111431
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Human Activity Affects Forest Fires: The Impact of Anthropogenic Factors on the Density of Forest Fires in Poland.
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- Forests (19994907), 2021, v. 12, n. 6, p. 728, doi. 10.3390/f12060728
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Identifying Forest Fire Driving Factors and Related Impacts in China Using Random Forest Algorithm.
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- Forests (19994907), 2020, v. 11, n. 5, p. 507, doi. 10.3390/f11050507
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Characteristics of Korean Forest Fires and Forest Fire Policies in the Joseon Dynasty Period (1392–1910) Derived From Historical Records.
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- Forests (19994907), 2019, v. 10, n. 1, p. 29, doi. 10.3390/f10010029
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Mapping Forest Fire Risk Zones Using Machine Learning Algorithms in Hunan Province, China.
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- Sustainability (2071-1050), 2023, v. 15, n. 7, p. 6292, doi. 10.3390/su15076292
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Modeling human-caused forest fire ignition for assessing forest fire danger in Austria.
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- iForest - Biogeosciences & Forestry, 2013, v. 6, n. 6, p. 315, doi. 10.3832/ifor0936-006
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Forest Fires – Causes, Detection and Impact on Forest Ecosystems.
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- ProEnvironment Promediu, 2012, v. 5, n. 12, p. 210
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Determination of Forest Fire Insurance Rates in Inner Mongolia Based on Regional Division of Risk.
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- Issues of Forestry Economics, 2023, v. 43, n. 2, p. 154, doi. 10.16832/j.cnki.1005-9709.20230012
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Temperal and spatial variation and risk zoning of forest fires in Liangshan Yi Autonomous Prefecture.
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- Journal of Northwest A & F University - Natural Science Edition, 2024, v. 52, n. 11, p. 48, doi. 10.13207/j.cnki.jnwafu.2024.11.006
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Assessment of forest fire danger in a boreal forest environment: description and evaluation of the operational system applied in Finland.
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- Meteorological Applications, 2014, v. 21, n. 4, p. 879, doi. 10.1002/met.1425
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"Progetto Incendi", portale cartografico nazionale del Ministero dell'Ambiente: un esempio di gestione di dati cartografici a supporto dei piani antincendio boschivi nei parchi nazionali.
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- Forest@ - Journal of Silviculture & Forest Ecology, 2010, v. 7, n. 1, p. 13, doi. 10.3832/efor0609-007
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我国林火发生预测模型研究进展.
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- Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao, 2020, v. 31, n. 9, p. 3227, doi. 10.13287/j.1001-9332.202009.014
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基于MODIS卫星火点的浙江省林火 季节变化及驱动因子.
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- Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao, 2020, v. 31, n. 2, p. 399, doi. 10.13287/j.1001-9332.202002.015
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美国林火管理概况及分析.
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- Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao, 2019, v. 30, n. 12, p. 4361, doi. 10.13287/j.1001-9332.201912.005
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Greenhouse gas emission in the whole process of forest fire including rescue: a case of forest fire in Beibei District of Chongqing.
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- Environmental Science & Pollution Research, 2023, v. 30, n. 52, p. 113105, doi. 10.1007/s11356-023-30247-8
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Mapping the forest fire risk zones using artificial intelligence with risk factors data.
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- Environmental Science & Pollution Research, 2023, v. 30, n. 2, p. 4721, doi. 10.1007/s11356-022-22515-w
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浅谈山区基层森林防灭火规范化建设 ——以河源市连平县大湖镇为例.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 54, doi. 10.3969/j.issn.1002-2511.2023.02.013
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加强新形势下森林灭火安全的思考.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 40, doi. 10.3969/j.issn.1002-2511.2023.02.010
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城市消防扑救森林火灾研究.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 36, doi. 10.3969/j.issn.1002-2511.2023.02.009
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森林和草原火灾风险普查可燃物样品处置方法.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 32, doi. 10.3969/j.issn.1002-2511.2023.02.008
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智能头盔在森林火灾扑救中的应用 ——以八达岭林场为例.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 29, doi. 10.3969/j.issn.1002-2511.2023.02.007
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森林火灾区域风险性分析与防范对策 ——以河南省范县为例.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 25, doi. 10.3969/j.issn.1002-2511.2023.02.006
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浅论林火管理发展的三个阶段及工作重心.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 11, doi. 10.3969/j.issn.1002-2511.2023.02.003
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山东省森林火灾时空分布及火源特征研究.
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- Journal of Wildland Fire Science, 2023, v. 41, n. 2, p. 1, doi. 10.3969/j.issn.1002-2511.2023.02.001
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Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment.
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- Processes, 2022, v. 10, n. 3, p. 483, doi. 10.3390/pr10030483
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Determining the most effective way of intervention in forest fires with fuzzy logic modeling : the case of Antalya/Türkiye.
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- Natural Hazards, 2023, v. 116, n. 2, p. 2269, doi. 10.1007/s11069-022-05763-4
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Satellite Remote Sensing False Forest Fire Hotspot Excavating Based on Time-Series Features.
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- Remote Sensing, 2024, v. 16, n. 13, p. 2488, doi. 10.3390/rs16132488
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Machine Learning for Predicting Forest Fire Occurrence in Changsha: An Innovative Investigation into the Introduction of a Forest Fuel Factor.
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- Remote Sensing, 2023, v. 15, n. 17, p. 4208, doi. 10.3390/rs15174208
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Suburban Forest Fire Risk Assessment and Forest Surveillance Using 360-Degree Cameras and a Multiscale Deformable Transformer.
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- Remote Sensing, 2023, v. 15, n. 8, p. 1995, doi. 10.3390/rs15081995
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Effects of Forest Fire Prevention Policies on Probability and Drivers of Forest Fires in the Boreal Forests of China during Different Periods.
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- Remote Sensing, 2022, v. 14, n. 22, p. 5724, doi. 10.3390/rs14225724
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Forest Fire Occurrence Prediction in China Based on Machine Learning Methods.
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- Remote Sensing, 2022, v. 14, n. 21, p. 5546, doi. 10.3390/rs14215546
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Forest Fire Spread Monitoring and Vegetation Dynamics Detection Based on Multi-Source Remote Sensing Images.
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- Remote Sensing, 2022, v. 14, n. 18, p. N.PAG, doi. 10.3390/rs14184431
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Characteristics of Spatiotemporal Changes in the Occurrence of Forest Fires.
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- Remote Sensing, 2021, v. 13, n. 23, p. 4940, doi. 10.3390/rs13234940
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A look at forest fires in Portugal: technical, institutional, and social perceptions.
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- Scandinavian Journal of Forest Research, 2015, v. 30, n. 4, p. 317, doi. 10.1080/02827581.2014.987160
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A hybrid deep learning model by combining convolutional neural network and recurrent neural network to detect forest fire.
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- Multimedia Tools & Applications, 2022, v. 81, n. 27, p. 38643, doi. 10.1007/s11042-022-13068-8
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An Examination of the Leadership and Management Traits and Style in the Forest Fire Incident Command System: The Cyprus Forest Fire Service.
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- Fire (2571-6255), 2025, v. 8, n. 1, p. 6, doi. 10.3390/fire8010006
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Weighing Policy Effectiveness Through Recent Forest Fire Status.
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- Fire (2571-6255), 2024, v. 7, n. 12, p. 432, doi. 10.3390/fire7120432
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Active Fire Clustering and Spatiotemporal Dynamic Models for Forest Fire Management.
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- Fire (2571-6255), 2024, v. 7, n. 10, p. 355, doi. 10.3390/fire7100355
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