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

拟议的研究计划的重点是利用遥感工具开发清查或绘制植被生态系统（林地和湿地）的方法。有两个具体目标，其中第一个目标旨在改进现有技术和利用遥感工具发展新的实地测量方法。就地测量方法提供深入的测量，但仅限于有限数量的取样区域。库存数据集经常出现缺口，这提高了利用遥感工具进行新的测量的重要性。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：(1)半球形摄影（HP），(2)陆地激光雷达（TLiDAR），(3)植被冠层结构模型。它们提供了测量细节的分级：HP是冠层极平面的2D表示，TLiDAR是冠层元素的明确3D探测，冠层结构模型是冠层的3D表示，可以扩展遥感传感器的测量。第二个具体目标是开发多尺度数据集成的植被生态系统制图方法。在使用植被生态系统的空间数据集时，尺度的分级通常起作用。在光学传感器的情况下，测量范围从地面绘图到用于地方和区域制图的高空间分辨率图像，并逐渐向用于国家和全球制图的最低空间分辨率方向发展。在我的研究计划中，我优先考虑本地（~10厘米到4米）或区域（~10米到100米）的测绘项目。在使用不同比例尺的空间数据集时，需要解决许多问题：如何最好地使用图数据来训练制图方法？有哪些替代方案可以填补不同规模的数据缺口？如何整合非图像数据来改进生成的地图？除了具体的多尺度项目，我们提出了一个整体框架，以促进制图方法的发展。因此，我的研究项目提供了适用于植被生态系统中各种条件的测量和制图解决方案。

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.