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在多种深度的木质侵占草原中,利用集成的遥感数据在多种深度上建模土壤有机碳

Sfundo Mthiyane¹, Onisimo Mutanga², Trylee Nyasha Matongera³

¹Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg, 3209, South Africa. mxosfundo5@gmail.com.

Environmental monitoring and assessment

|February 28, 2025

概括

木质植物的侵占改变了草原中的土壤有机碳 (SOC). 这项研究有效地利用遥感和地形数据在不同深度模拟了SOC,在较浅的土壤层发现了更高的SOC积累.

科学领域:

土壤科学土壤科学
遥感遥感遥感遥感
生态生态学生态生态学

背景情况:

木质植物侵入草原显著影响土壤的生物地球化学,特别是土壤有机碳 (SOC) 池.
对于管理侵占草原来说,对更深层土壤中的SOC库存进行准确的评估至关重要.
在受木材侵占影响的局部,受保护的草原上,对SOC捕获的理解仍然有限.

研究的目的:

量化 SOC 在多个土壤深度 (30,60 和 100 厘米) 的积累在木质侵占草原.
整合多源卫星图像 (Sentinel-1,Sentinel-2,PlanetScope) 和地形变量用于SOC建模.
评估遥感和机器学习对这些生态系统中SOC库存评估的有效性.

主要方法:

采集了360个土壤样本,使用燃烧损失 (LOI) 方法量化SOC.
采用随机森林 (RF) 算法来建模SOC的空间分布.
综合卫星-1 (SAR),卫星-2,星球镜像和地形变量作为预测因素.

主要成果:

综合模型在预测所有深度的SOC库存方面实现了高准确性 (R2 = 0.79,RMSE = 0.254 t/ha).
发现SOC库存在30厘米深处比60厘米和100厘米深处更高.
最佳预测因素包括Sentinel-1的水平 (VH) 和垂直 (VV) 接收,斜率,地形湿度指数 (TWI) 和Sentinel-2的带11.

结论:

将射频模型与光谱和地形数据集成,可以在木质生态系统中提供准确的SOC建模.
开发的方法为SOC评估和监测提供了一种具有成本效益和劳动效率的方法.
这些发现对于森林侵占草原息地的明智管理策略至关重要.

关键词:

随机的森林随机的森林遥感是一种远程传感.土壤有机碳土壤有机碳伍迪的侵占侵权行为

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