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承认，利用森林影响碳循环的机制也已到位。这一现象的规模使森林参数的估计和绘图成为全球/国家一级的优先事项。遥感是在相关尺度上提供所需信息的唯一有效手段。过去的研究表明，现有的遥感技术的潜力和局限性的一系列生态系统类型，从茂密的植被和复杂的潮湿的热带森林稀疏的树木分布的稀树草原。在后者中，基于光谱特性的传统技术遇到了区分树木和草信号的问题，这两者在一年中的大部分时间都同时进行光合作用。本研究的目的是探索潜在的图像方向分辨率在提高树木生物量制图精度在稀树草原。该方法利用热带稀树草原中树木的空间排列所产生的突出阴影模式来估计树木密度和大小，并最终将此信息与树木生物量联系起来。该项目为加拿大地理信息产业提供了一个机会，以巩固其在国际一级的领先地位，并为在新的应用领域输出我们的专门知识提供了机会。

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.