Forest remote sensing on the individual tree level by airborne millimeterwave SAR

Abstract

means is an important research topic in the context of sustainable forest management. This holds particularly for sensors and methods which are capable of providing information on the level of individual trees: In many countries, single-tree related parameters are the basis for forest inventory. Until These days, the majority of these parameters are collected manually by measurement of sample plots in cost- and time-intensive field surveys. However, remote sensing-based methods have gained increasing attention during recent decades. A large number of promising approaches for the recognition of individual trees is based on the segmentation of Li- DAR point clouds, e.g. [1]. When it comes to synthetic aperture radar (SAR) remote sensing, however, only recently the potential for single-tree analysis has been discovered: Beginning with the first-ever discussion of the possibilities for the recognition of individual trees by airborne millimeterwave SAR data [2], both amplitude-based and interferometric approaches have been proposed [3]. Finally, in [4] a method for the reconstruction of individual trees from multi-aspect TomoSAR data was described, while [5] presents an investigation towards the exploitation of volumetric millimeterwave SAR tomography for sub-canopy imaging. This paper summarizes the recent developments in this state-of-the-art field.