A Review of Forest Height Inversion by PolInSAR: Theory, Advances, and Perspectives

Abstract

Forests cover approximately one-third of the Earth’s land surface and constitute the core region of the carbon cycle on Earth. The paramount importance and multi-purpose applications of forest monitoring have gained widespread recognition over recent decades. Polarimetric synthetic aperture radar interferometry (PolInSAR) has been demonstrated as a promising technique to retrieve the forest height over large areas with a limited cost. This paper presents an overview of forest height inversion (FHI) techniques based on PolInSAR data. Firstly, we introduce the basic theories of PolInSAR and FHI procedures. Next, we review the established data-based algorithms for single-baseline data and describe innovative techniques related to multi-baseline data. Then, the model-based algorithms are also introduced with their corresponding forest scattering models under multiple data acquisition modes. Subsequently, a case study is presented to demonstrate the applicable scenarios and advantages of different algorithms. Model-based algorithms can provide accurate results when the scene and forest properties are well understood and the model assumptions are valid. Data-based algorithms, on the other hand, can handle complex scattering scenarios and are generally more robust to uncertainties in the input parameters. Finally, the prospect of forest height inversion was analyzed. It is our hope that this review will provide guidelines to future researchers to enhance further FHI algorithmic developments.

Influence of VF and SOR-Filtering Methods on Tree Height Inversion Using Unmanned Aerial Vehicle LiDAR Data

“…Forest structural parameters such as canopy cover, tree density, diameter at breast height, and tree height serve as important criteria characterizing the growth status of a forest, determining the rationality of the forest spatial structure, and evaluating the ecological functions of a forest. Tree height stands out as one of the most important forest structural parameters, and it is widely used to estimate terrestrial forest carbon reserves, as well as in biomass monitoring and forest health assessment [6][7][8].…”