Research on plant health state detection based on two-channel multispectral LiDAR

The Normalized Difference Vegetation Index (NDVI) can effectively reflect the growth state and spatial distribution of vegetation, which can be used to study vegetation growth, regional coverage and drought response. Traditionally, NDVI is acquired using Remote Sensing, which results in limited information. The emergence of Multispectral LiDAR provides a new way to obtain NDVI. It can gain rich spectral alongside three-dimensional spatial information. In this paper, a two-channel Multispectral LiDAR system is constructed, where two wavelengths of 650nm and 800nm laser are used to detect the leaves from various plants in different health states. The echo intensities at these two wavelengths are collected, then, the corresponding NDVI values are calculated. It is found that the longer the leaves are separated from the plants, the closer the NDVI value is to 0. The range of NDVI varies with tree species, but the variation trend is the same, and the highest NDVI of freshly picked leaves is about 0.89. At the same time, this paper uses a multi-channel high-speed acquisition card to collect data, the Time of Flight (TOF) is processed by batch average to obtain the objects’ distance. It can be seen that the two-channel Multispectral LiDAR can realize the detection of plant health state and obtain spatial distance position information simultaneously. This study not only verifies the effectiveness of the two-channel Multispectral LiDAR system to obtain NDVI, but also has constructive significance for the study of short-period vegetation growth status and the application of forest terrain construction. For the keywords, select up to 8 key terms for a search on your manuscript's subject.