遥感在热带草原营养估计中的作用:一篇综述
Adeola M Arogoundade1, Onisimo Mutanga2, John Odindi2
1Discipline of Geography, School of Agricultural, Earth and Environmental Sciences, Department of Geography, University of KwaZulu-Natal, Pietermaritzburg, South Africa. aro_ma2006@yahoo.com.
Environmental monitoring and assessment
|July 15, 2023
概括
使用遥感测绘牧场中碳 (C) 与 (N) 的比例,对于理解放牧模式至关重要. 先进的卫星图像和机器学习算法为准确的C:N比率估计提供了新的机会.
科学领域:
- 牧场生态 牧场生态
- 遥感科学 遥感科学
- 营养素循环循环的过程
背景情况:
- 碳 (C) 与 (N) 的比率对于评估牧场的营养物质可用性和限制至关重要.
- 了解草的质量和数量对于预测草食动物分布和放牧模式至关重要.
- 遥感提供了一种可扩展和高效的方法,用于在异质环境中监测叶子生物化学比率.
研究的目的:
- 审查遥感的进步,局限性和机遇,以绘制牧场C:N比率的地图.
- 专注于多光谱和高光谱传感器功能,用于预测草原C:N比率.
- 为了弥合当前遥感技术和草原中C:N比率的确定之间的差距.
主要方法:
- 分析多光谱和高光谱传感器特性和吸收特征.
- 对C:N比率预测的经验和物理方法的研究.
- 从卫星数据估计叶子生物化学比率的算法的评估.
主要成果:
- 预测植物C:N比率的关键光谱带包括近红外,短波红外,红色和红边.
- 最近的多光谱卫星图像 (例如,Sentinel 2) 使用先进的算法显示了改善叶子生物化学比率估计的潜力.
- 遥感技术的潜力与它们在草原C:N比率确定中的当前应用之间存在差异.
结论:
- 自由可用的卫星数据 (Sentinel 2,Landsat 8/9) 与复杂的算法相结合,可以在草原上进行区域C:N比率估计.
- 未来的研究应该利用先进的卫星技术和机器学习来加强草原C:N比率的绘制.
- 改进的C:N比率绘制可以显著帮助牧场管理和了解生态系统动态.
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