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Updated: Jul 2, 2025

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基于卫星的集体智能方法用于预测森林火灾:伊朗赫尔卡尼亚森林的案例

Seyed Babak Haji Seyed Asadollah1, Ahmad Sharafati2,3, Davide Motta4

  • 1Department of Environmental Resources Engineering, State University of New York College of Environmental Science and Forestry, Syracuse, NY, 13210, USA.

Environmental science and pollution research international
|February 27, 2024
PubMed
概括

机器学习模型预测了伊朗的森林火灾. 虽然中等信心火灾可能会减少,但高信心火灾预计将增加,特别是在夏季,影响戈勒斯坦省.

关键词:
预测 预测 预测 预测森林大火 森林大火一般流通的模型.机器学习 机器学习

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Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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