空间分析和机器学习预测森林火灾易感性:有效管理和减轻森林火灾的综合方法
Manoranjan Mishra1, Rajkumar Guria1, Biswaranjan Baraj1
1Department of Geography, Fakir Mohan University, Vyasa Vihar, Nuapadhi, Balasore 756089, Odisha, India.
The Science of the total environment
|March 19, 2024
概括
热带森林的森林火灾正在增加,对生态系统和气候构成风险. 这项研究绘制了印度奥迪沙州易发生火灾的地区,使用机器学习指导预防策略.
科学领域:
- 生态与环境科学 生态与环境科学
- 遥感和地理信息系统 (GIS) 的应用
- 气候变化研究 气候变化研究
背景情况:
- 热带季节性森林面临着森林火灾 (FF) 的重大影响.
- 在全球范围内扩大FF频率和强度需要了解其模式和脆弱性.
- 缓解FF对于生物多样性保护和气候变化适应至关重要.
研究的目的:
- 调查印度奥迪沙州的FF趋势,模式和时空分布 (2001-2022年).
- 使用先进的建模技术,划分森林火灾易受影响的区域.
- 为有效的防范和管理战略提供信息.
主要方法:
- 利用MODIS图像进行主动火点数据分析.
- 使用内核密度工具和机器学习算法 (SVM,RF) 进行风险预测.
- 整合了19个因素 (地形,气候,生物物理,人为) 用于敏感性映射,并使用ROC/AUC进行了验证.
主要成果:
- 随机森林 (RF) 模型实现了>94%的精度,超过了SVM模型 (89%).
- RF和SVM分别确定了该地区的20.14%和16.72%为"非常高森林火灾"易感区.
- 观察到FF发生的显著上升趋势 (R2=0.59),在2021年达到顶峰;安古尔地区受到影响最大.
结论:
- 机器学习模型有效地预测森林火灾的易感性.
- 识别高风险区域和趋势对于有针对性的缓解努力至关重要.
- 开发的洞察力支持决策者制定强有力的森林火灾预防和管理计划.
相关概念视频
01:21Manipulation and Analysis
23
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
23
01:29Applications of GIS: Disaster Management and Emergency Response
78
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...
78
01:29Levels of Use of a GIS
50
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
50
01:18Steps in Outbreak Investigation
126
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
126
01:19Survival Tree
84
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
84
01:25Selected Data About Geographic Locations
27
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
27