YAN S, ZHAO Y B, LEI S G, et al.Estimation of dust retention in grassland plant canopy based on UAV hyperspectral remote sensing[J].Journal of Henan Polytechnic University(Natural Science) ,2022,41(6):84-92.

doi:10.16186/j.cnki.1673-9787.2020090070

Received:2020/09/16

Revised:2020/11/10

Published:2022/11/25

Estimation of dust retention in grassland plant canopy based on UAV hyperspectral remote sensing

YAN Shi1, ZHAO Yibo2, LEI Shaogang2, YANG Xingchen2, LI Heng2, GONG Chuangang2

1.Shenhua BeiDIan Shengli Energy Co.， Ltd.， Xilin Hot  026015， Inner Mongolia，China；2.Engineering Research Center of Ministry of Education for Mine Ecological Restoration， China University of Mining and Technology， Xuzhou  221116， Jiangsu，China

Abstract:In order to explore the feasibility of UAV hyperspectral remote sensing to estimate the dust retention content of grassland plant canopy， Baorixile grassland in the Inner Mongolia Autonomous Region was taken as the research area.The dust content was measured with an electronic analytic balance （1/10000g scale） and a leaf area meter.The airborne hyperspectral images were obtained by using an imaging spectrometer.The influence of dust retention on spectral reflectance and trilateral parameters of the canopy was analyzed.The correlation of dust retention content with single-band reflectance and spectral index was explored， and the estimation model of plant canopy dust retention was established based on spectral parameters.The results showed that：（1）With the increase of dust retention content， the reflectance of visible wavelength increased first and then decreased， but the overall change tended to decrease； the reflectance of near-infrared wavelength decreased gradually.The canopy dust had no significant influence on the trilateral position.Still，it was significantly correlated with the yellow edge slope （D_y），red edge slope （D_r），yellow edge area （SD_y），and red edge area （SD_r）；（2）The correlation coefficients between the canopy dust retention content and the original spectral reflectance were negative.The ratio index （RI）， difference index （DI），and normalized difference index （NDI） all enhanced the correlation between the dust retention content and spectral data in varying degrees；（3）The estimation model of plant canopy dust retention constructed through the random forest（RF） had high accuracy with the spectral reflectance of 542 and 969 nm （R542 and R969），DI720，969，NDI725，890，D_y，and D_r as variables.The distribution map of canopy dust retention based on airborne hyperspectral images can better reflect the spatial distribution.The results could provide a theoretical basis and technical support for monitoring the dust retention content of grassland plants.

Key words:grassland plant;canopy dust retention;hyperspectral;spectral analysis;estimation model

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