Applications and Prospects of Hyperspectral Remote Sensing for Monitoring Plant Species Diversity
Plant diversity plays a crucial role in maintaining ecosystem process,services and functions.In recent years,the rapid advancement of hyperspectral remote sensing technology has provided new data sources for plant diversity investigation and assessment.Monitoring plant species diversity is an important aspect of using remote sensing technology to assess overall plant diversity.Hyperspectral remote sensing can capture abundant spectral and spatial information,which aids in plant species identification and classification,and enhances the accuracy of estimating plant species diversity.Based on literature reviews,this paper summarizes the applications of hyperspectral remote sensing in monitoring plant species diversity and explains the basic principles of using hyperspectral remote sensing for this purpose.It also outlines the main hyperspectral data sources,common spectral transformation techniques,and species classification methods.Finally,the paper discusses future research directions and prospects.The main conclusions are as follows:(1)The applications of hyperspectral remote sensing in monitoring plant species diversity include the extraction of spectral features for plant species,identification and classification of plant species,and estimation of plant species diversity.(2)The spectral variation hypothesis forms an important theoretical basis for monitoring plant species diversity using hyperspectral remote sensing technology.Typically,empirical or semi-empirical methods are used to establish statistical models linking plant species diversity with spectral diversity indicators,which are then used to assess diversity.(3)The hyperspectral data is typically obtained from satellite,aircraft,and ground-based platforms.Common spectral transformation techniques include Savitzky-Golay Smoothing(SG smoothing),envelope removal,derivative transformation,and construction of vegetation indices.Support Vector Machines and Random Forests are widely used for plant species classification in hyperspectral remote sensing applications.This paper recommends strengthening the use of domestic hyperspectral remote sensing data for monitoring plant species diversity,building multi-scale spectral database for plant species,and developing intelligent algorithms for processing and extracting information from hyperspectral data across various platforms to improve the accuracy and efficiency of monitoring plant species diversity.
万方数据
维普
