机构地区:[1]Department of Spatial Information&Digital Engineering,School of Remote Sensing and Information Engineering,Wuhan University,Wuhan,Hubei 430079,China [2]Research Center of Spatial Information and Digital Engineering of the State Bureau of Surveying and Mapping,Wuhan,Hubei 430079,China [3]Institute of Botany,the Chinese Academy of Sciences,Beijing 100093,China [4]Inner Mongolia Institute of Grassland Surveying and Planning,Hohhot 010051,China [5]Key Laboratory of Forage Cultivation,College of Grassland,Resources and Environment,Inner Mongolia Agricultural University,Hohhot 010018,China
出 处:《Journal of Plant Ecology》2019年第3期395-408,共14页植物生态学报(英文版)
基 金:Funding support for this study included the National Natural Science Foundation of China(nos.41871296,41371371 and 41501441);Open Fund of Key Laboratory of Geographic Information Science,Ministry of Education);East China Normal University(no.KLGIS2017A05);Hubei Provincial Natural Science Foundation of China(no.ZRMS2017000737);Large Scale Environment Remote Sensing Platform Project from Wuhan University(nos.16000009,16000011 and 16000012).
摘 要:Aims Remote sensing technology has been proved useful in mapping grass-land vegetation properties.Spectral features of vegetation cover can be recorded by optical sensors on board of different platforms.With increas-ing popularity of applying unmanned aerial vehicle(UAV)to mapping plant cover,the study aims to investigate the possible applications and potential issues related to mapping leaf area index(LAI)through integra-tion of remote sensing imagery collected by multiple sensors.Methods This paper applied the collected spectral data through field-based(FLD)and UAV-borne spectroradiometer to map LAI in a Sino-German experiment pasture located in the Xilingol grassland,Inner Mongolia,China.Spectroradiometers on FLD and UAV platforms were taken to measure spectral reflectance related to the targeted vegetation proper-ties.Based on eight vegetation indices(VIs)computed from the col-lected hyperspectral data,regression models were used to inverse LAI.The spectral responses between FLD and UAV platforms were com-pared,and the regression models relating LAI with VIs from FLD and UAV were established.The modeled LAIs by UAV and FLD platforms were analyzed in order to evaluate the feasibility of potential integra-tion of spectra data for mapping vegetation from the two platforms.Important Findings Results indicated that the spectral reflectance between FLD and UAV showed critical gaps in the green and near-infrared regions of the spec-trum over densely vegetated areas,while the gaps were small over sparsely vegetated areas.The VI values from FLD spectra were greater than their UAV-based counterparts.Out of all the VIs,broadband gen-eralized soil-adjusted vegetation index(GESAVI)and narrow-band nNDVI2 were found to achieve the best results in terms of the accuracy of the inversed LAIs for both FLD and UAV platforms.We conclude that GESAVI and nNDVI2 are the two promising VIs for both platforms and thus preferred for LAI inversion to carry spectra integration of the two platforms.We suggest that accuracy on the LAI inver
关 键 词:GRASSLAND leaf area index unmanned aerial vehicle vegetation index remote sensing
分 类 号:V27[航空宇航科学与技术—飞行器设计]
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