{"title":"OVERVIEW OF LAI/FPAR RETRIEVAL FROM REMOTELY SENSED DATA","authors":"Wu Bing-fang, Zeng Yuan, Huang Jin-liang","doi":"10.11867/J.ISSN.1001-8166.2004.04.0585","DOIUrl":null,"url":null,"abstract":"Vegetation biophysical variables, LAI and FPAR, are the most important terrestrial properties. For acquiring these variables in local scale, the most effective approach is by remote sensing models combined with the ground-based validation. Spectral index model and radiant transmission model are two kinds of key methods. Through the precise radiometric and atmospheric correction, it is possible to obtain the LAI/FPAR products with a high accuracy. There are several factors influencing the accuracy of these products, such as the pixel heterogeneity, vegetation types and growing seasons. LAI and FPAR have the compact relationship with crop yield and they are also the basic variables of many crop growth models. Using them could realize the true yield prediction, especially for estimating the production in the global scale.","PeriodicalId":415150,"journal":{"name":"Advance in Earth Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advance in Earth Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11867/J.ISSN.1001-8166.2004.04.0585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Vegetation biophysical variables, LAI and FPAR, are the most important terrestrial properties. For acquiring these variables in local scale, the most effective approach is by remote sensing models combined with the ground-based validation. Spectral index model and radiant transmission model are two kinds of key methods. Through the precise radiometric and atmospheric correction, it is possible to obtain the LAI/FPAR products with a high accuracy. There are several factors influencing the accuracy of these products, such as the pixel heterogeneity, vegetation types and growing seasons. LAI and FPAR have the compact relationship with crop yield and they are also the basic variables of many crop growth models. Using them could realize the true yield prediction, especially for estimating the production in the global scale.