摘 要
森林火灾作为全球性生态问题，对生态系统平衡和人类社会安全构成重大威胁，因此构建高效预警系统至关重要。本研究旨在评估现有森林火灾预警系统的效能，并提出优化建议以提升其预测精度与响应能力。通过整合多源遥感数据与气象观测资料，采用机器学习算法对历史火灾数据进行建模分析，同时引入动态风险评估指标体系以量化系统性能。研究结果表明，传统预警模型在复杂地形和极端气候条件下的适应性不足，而基于深度学习的混合模型能够显著提高预警准确率，平均提前预警时间延长约20%。此外，本研究创新性地提出了分布式节点监测网络架构，有效弥补了单一传感器覆盖范围有限的问题。最终结论显示，结合人工智能技术与优化监测布局可大幅提升预警系统的整体效能，为森林火灾防控提供了科学依据和技术支持，具有重要的实践意义与推广价值。关键词：森林火灾预警; 深度学习模型; 动态风险评估; 分布式监测网络; 遥感数据整合
Abstract
Forest fires, as a global ecological issue, pose significant threats to the balance of ecosystems and the safety of human society, making the construction of an efficient early warning system critical. This study aims to evaluate the effectiveness of existing forest fire warning systems and propose optimization recommendations to enhance their predictive accuracy and responsiveness. By integrating multisource remote sensing data with meteorological observation records, machine learning algorithms were employed to model and analyze historical fire data, while a dynamic risk assessment index system was introduced to quantify system performance. The results indicate that traditional warning models exhibit insufficient adaptability under complex terrains and extreme climatic conditions, whereas hybrid models based on deep learning can substantially improve the accuracy of warnings, extending the average lead time by approximately 20%. Additionally, this study innovatively proposes a distributed node monitoring network architecture, effectively addressing the limitations of coverage range associated with single sensors. The final conclusion demonstrates that the combination of artificial intelligence technologies and optimized monitoring layouts can significantly enhance the overall efficiency of warning systems, providing scientific evidence and technical support for forest fire prevention and control, with important practical implications and potential for widespread application.Key words:Forest Fire Early Warning; Deep Learning Model; Dynamic Risk Assessment; Distributed Monitoring Network; Remote Sensing Data Integration
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、森林火灾预警系统效能评估框架 2
1.1、预警系统效能评估指标体系 2
1.2、评估方法与技术路径选择 2
1.3、数据来源与样本分析 3
第2章、现有预警系统效能问题分析 4
2.1、技术局限性及其影响 4
2.2、数据采集与处理瓶颈 4
2.3、用户反馈与实际需求偏差 4
第3章、预警系统优化策略研究 6
3.1、核心技术升级方向 6
3.2、数据融合与智能化改进 6
3.3、系统集成与协同能力提升 6
第4章、优化方案实施与效果验证 8
4.1、实施路径与资源保障 8
4.2、模拟测试与案例分析 8
4.3、效果评估与改进建议 8
结 论 10
参考文献 11
