使用人工智能对森林覆盖面的动态进行时间评估,以应对森林火灾和其他环境影响
Shehla Noor1, Rafia Mumtaz2, Muhammad Ajmal Khan1
1School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad, 44000, Pakistan.
Environmental monitoring and assessment
|September 4, 2024
概括
森林火灾和降雨量减少显著减少森林覆盖,影响生态系统. 这项研究使用了Sentinel-2图像和聚类来分析汶莱达鲁萨拉姆的这些变化,识别了火灾热点.
科学领域:
- 环境科学 环境科学
- 遥感 遥感 遥感 遥感
- 林业林业 林业 林业 林业
背景情况:
- 由于森林砍伐,气候变化和人类活动,森林覆盖面的减少是全球主要关注的问题.
- 森林火灾频率和强度的增加对生态系统,经济,野生动物和人类安全构成重大威胁.
- 准确监测大规模森林覆盖变化对于可持续森林管理至关重要.
研究的目的:
- 分析森林火灾对森林覆盖面随时间变化的影响.
- 确定森林火灾的热点,并调查影响森林覆盖面的环境因素.
- 为保护和造林战略提供数据.
主要方法:
- 利用 Sentinel-2 卫星图像对 2017 年至 2022 年的文莱达鲁萨拉姆的森林覆盖面进行分析.
- 采用基于对象的简单非代集群 (SNIC) 方法,使用NDVI值.
- 分析了集群区域与火灾发生率和降水水平相关的变化.
主要成果:
- 确定了与火灾发生率和降雨量减少相关的集群面积减少.
- 在2017年至2022年间,观察到集群区域的显著变化,从66.11%到78.70%不等.
- 确定了贝莱特地区作为每年森林火灾的经常性热点.
结论:
- 森林火灾和降雨量下降是森林覆盖面丧失的主要驱动因素.
- 这些发现支持有针对性的保护和植树努力的必要性.
- 遥感和集群技术是监测森林动态的有效工具.
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