Contributions of multiangular remote sensing imagery to mapping tree biomass in savannas

世界森林在气候调节中的作用现已得到广泛认可，并建立了利用森林影响碳循环的机制。这一现象的规模使森林参数的估算和测绘成为全球/国家一级的优先事项。遥感是在有关比例尺上提供所需信息的唯一有效手段。过去的研究表明，现有遥感技术对一系列生态系统类型的潜力和局限性，从植被茂密和复杂的湿润热带森林到稀疏的热带稀树分布。在后者中，基于光谱特性的传统技术在区分树木和草的信号方面遇到了问题，这两种信号在一年的大部分时间里都是同时进行光合作用的。本研究的目的是探索图像方向分辨率在提高稀树草原树木生物量制图精度方面的潜力。该方法利用稀树大草原树木空间排列产生的显著阴影模式来估计树木密度和大小，并最终将这些信息与树木生物量联系起来。该项目为加拿大地球测量行业提供了一个巩固其在国际上的领先地位的机会，并为我们在新的应用领域输出我们的专业知识提供了机会。

The role of the World's forests in climate regulation is now widely recognized and mechanisms are in place to use forests in influencing the carbon cycle. The scale of the phenomenon has made the estimation and mapping of forest parameters a global/national level priority. Remote sensing is the only effective means available to provide the needed information at the relevant scales. Past research has shown potentials and limitations of existing remote sensing techniques for a range of ecosystem types, from the densely vegetated and complex humid tropical forest to the sparse tree distribution of savannas. In the latter, traditional techniques based on spectral properties encounter problems differentiating the tree and grass signals, both being simultaneously photosynthetically active throughout most of the year. The objective of this research is to explore the potential of imagery directional resolution in improving tree biomass mapping accuracy in savannas. The proposed approach takes advantage of the prominent shadow patterns created by the spatial arrangement of trees in the savanna to estimate tree density and size, and ultimately link this information to tree biomass. This project represents an opportunity for the Canadian geomatics industry to consolidate its lead position at the international level and provides openings to export our expertise in a new field of application.