UAV-based hyperspectral images and monitoring of canopy tree diversity

Abstract

Background & Aims: The species diversity of canopy trees is important for the function and service of natural forest ecosystems. To be able to formulate reasonable biodiversity conservation strategies, it is important to understand patterns of forest canopy diversity through time. However, the development of high-precision forest canopy diversity monitoring at a regional scale is slow due to a limitation in diversity information collection methods. A lot of biodiversity patterns may substantially change due to climate change and human disturbance. However, updating these changes in biodiversity cannot be done in a timely manner. In recent years, the development of canopy hyperspectral image collection based on unmanned aerial vehicle (UAV) and analysis technology has provided an opportunity for the development of new tools for canopy diversity monitoring. Progresses: Here, we propose using the hyperspectral image of forest canopy for biodiversity monitoring and conservation, development of UAV aerial photography and spatial positioning technology, and the development of hyperspectral image processing technology with deep learning. We use the existing literature to discuss the research status, feasibility, advantages, and disadvantages of using UAV hyperspectral imaging for monitoring of species diversity of forest canopy trees. We believe that canopy hyperspectral images provide indispensable and abundant