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在Landsat,Sentinel-2和PlanetScope数据的基础上,在赛季内估计有10米以上的地表生物质

Tianyu Cai¹, Chuchen Chang¹, Yanbo Zhao¹

¹College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China.

Scientific data

|November 23, 2024

概括

这项研究开发了一个随机森林模型,使用和的遥感数据来估计中国草原的月度地面生物量 (AGB). 10米分辨率的地图准确地捕捉了整个生长季节的草原AGB动态.

科学领域:

生态生态学生态生态学
遥感遥感遥感遥感
地理空间分析是什么

背景情况:

在牧场和气候变化等干扰中,季节内地表生物量 (AGB) 的监测对于适应性草原管理至关重要.
准确的AGB数据对于了解草原生态系统的健康和生产力至关重要.

研究的目的:

在中国的三个不同的草地类型中以10米分辨率估计每月的草地AGB.
评估协调远程传感数据在捕获空间和时间AGB动态方面的能力.

主要方法:

使用Landsat,Sentinel-2和Sentinel-1数据与密集的草原样本观测训练了一种随机森林模型.
利用月度平均遥感数据预测温带草原草原,典型草原和沙漠草原的AGB.
在R2 = 0.68和RMSE = 47.87 g/m2的情况下验证了模型性能.

主要成果:

每月生成的AGB估计,关键生长月份 (六月至九月) 的分辨率为10m.
预测的AGB平均值从6月的83.02g/m2到8月的108.49g/m2之间.
与较粗的分辨率或年度产品相比,1000万个月的AGB地图显示出捕捉空间和季节变化的优越能力.

结论:

开发的方法为监测草原AGB动态提供了有价值的工具,具有高度的空间和时间细节.
这种方法支持草原管理和保护工作的知情决策.
和的遥感数据集成为生态监测应用提供了显著的优势.

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