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使用时间序列卫星数据量化森林火灾破坏后的森林弹性
Sumedha Surbhi Singh1, C Jeganathan2
1Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India.
Environmental monitoring and assessment
|December 8, 2023
概括
这项研究引入了一个新的框架,用卫星数据量化森林弹性,评估干扰后的植被恢复. 这些发现突出了邦达夫加尔国家公园的北部地区.
科学领域:
- 生态生态学 生态生态学
- 遥感 遥感 遥感 遥感
- 环境科学 环境科学
背景情况:
- 森林弹性对生物多样性和生态系统健康至关重要,因为环境变化正在发生.
- 准确测量森林弹性对于可持续森林管理至关重要.
- 使用Landsat数据的现有方法面临着由于云覆盖而导致持续监控的挑战.
研究的目的:
- 开发一个框架来估计干扰后的森林弹性得分.
- 用卫星衍生指数评估植被状况和恢复.
- 调查人类活动与森林弹性之间的关系.
主要方法:
- 使用MODIS16天EVI产品 (2001-2020年) 进行植被健康监测.
- 根据恢复日,现象学性能和绿色水平计算的弹性得分.
- 将框架应用于印度邦达夫加尔国家公园,重点关注2018年森林火灾事件.
主要成果:
- 开发了一种新的弹性指数,包含多个植被指标.
- 确定邦达夫加尔国家公园的北部更容易受到伤害,恢复速度较慢.
- 研究了当地人类人口与森林弹性之间的相关性.
结论:
- 拟议的框架有效量化了森林弹性和干扰后恢复.
- 该研究提供了对森林脆弱性和恢复率的区域差异的见解.
- 了解人类影响对于有效的森林弹性管理至关重要.
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