M. Rautiainen, P. Stenberg, P. Lukeš, M. Mõttus, J. Heiskanen
{"title":"Estimating canopy spectral invariants from ground reference and remote sensing data","authors":"M. Rautiainen, P. Stenberg, P. Lukeš, M. Mõttus, J. Heiskanen","doi":"10.1109/WHISPERS.2010.5594861","DOIUrl":null,"url":null,"abstract":"Physically-based remote sensing methods have progressively become more attractive for monitoring the vertical and horizontal structure of vegetation. A relatively recent development in modeling the radiation field of a vegetation canopy is the spectral invariants theory. The theory states that the radiation budget of a vegetation canopy can be parameterized using only spectrally invariant parameters which depend on canopy structure in a complex manner. In this paper, we briefly review how spectral invariants can be estimated from hyperspectral remote sensing data or in situ vegetation canopy gap fraction measurements.","PeriodicalId":193944,"journal":{"name":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2010.5594861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Physically-based remote sensing methods have progressively become more attractive for monitoring the vertical and horizontal structure of vegetation. A relatively recent development in modeling the radiation field of a vegetation canopy is the spectral invariants theory. The theory states that the radiation budget of a vegetation canopy can be parameterized using only spectrally invariant parameters which depend on canopy structure in a complex manner. In this paper, we briefly review how spectral invariants can be estimated from hyperspectral remote sensing data or in situ vegetation canopy gap fraction measurements.