New methods for remote sensing of vegetated ecosystems: in situ measurement and multi-scale mapping

拟议的研究计划是集中在使用遥感工具的库存或映射植被生态系统（林地和湿地）的方法的发展。有两个具体目标，第一个目标是改进现有技术和利用遥感工具开发新的现场测量方法。现场测量方法提供了深入的测量，但只对有限数量的取样区域进行测量。清单数据集经常出现空白，这就提高了利用遥感工具进行新的替代测量的重要性。在利用遥感测量植被生态系统方面，有三种工具特别有前途和创新性：（1）半球摄影（HP），（2）地面激光雷达（TLiDAR），（3）植被冠层结构模型。它们提供了一个层次的测量细节：HP是一个2D表示在极平面的树冠，TLiDAR是一个明确的3D探测的树冠元素，和树冠结构模型是一个3D表示的树冠，可以扩展从遥感传感器的测量。 第二个具体目标是从多尺度数据的整合中开发植被生态系统的制图方法。在使用植被生态系统空间数据集时，通常会出现尺度分级。在光学传感器的情况下，测量范围从地面绘图到图像，从高空间分辨率到地方和区域制图，再逐渐到最低空间分辨率，以进行国家和全球制图。在我的研究项目中，我优先考虑本地（~ 10厘米至4米）或区域水平（~ 10米至100米）的测绘项目。关于不同尺度的空间数据集的使用，需要解决许多问题：如何最好地使用地块数据来训练映射方法？有哪些替代办法可以填补不同规模的数据空白？如何整合非图像数据以改进生成的地图？除了具体的多尺度项目，我们提出了一个整体框架，以促进映射方法的发展。因此，我的研究计划提供了适用于植被生态系统中存在的各种条件的测量和绘图解决方案。

The proposed research program is centered on the development of methods for inventory or mapping vegetated ecosystems (forestland and wetland) using remote sensing tools. There are two specific objectives targeted where the first one aims at improving existing techniques and developing new in situ measurement methods with remote sensing tools. In situ measurement methods provide in-depth measurements but on a limited number of sampled areas. Frequent gaps in inventory data sets raise the importance of new measurement alternatives with remote sensing tools. Three tools are particularly promising and innovative in the use of remote sensing for measurement of vegetated ecosystems: (1) hemispherical photography (HP), (2) terrestrial LiDAR (TLiDAR), and (3) model of vegetation canopy architecture. They provide a gradation of measurement details: HP is a 2D representation in polar plane of the canopy, TLiDAR is an explicit 3D sounding of canopy elements, and a canopy architecture model is a 3D representation of canopy that can extend the measure from remote sensing sensors. The second specific objective aims at developing mapping methods of vegetated ecosystem from integration of multi-scale data. A gradation of scales is usually at work in the use of spatial data sets for vegetation ecosystems. In the case of optical sensors, measurements span from ground plots towards imagery from high spatial resolution for local and regional mapping, and gradually towards the lowest spatial resolution for national and global mapping. In my research program I priorize mapping projects at either local (~10cm to 4m) or regional levels (~10m to 100m). Many questions need to be addressed concerning the use of spatial data sets at different scale: How best to use plot data to train mapping methods? What are the alternatives to fill data gaps at different scales? How to integrate non image data to improve resulting maps? Aside specific multi-scale projects, we propose an overall framework to facilitate development of mapping methods. My research program thus provides measurement and mapping solutions applicable to a wide range of conditions present in vegetated ecosystems.