Deriving Leaf Area Index Reference Maps Using Temporally Continuous In Situ Data: A Comparison of Upscaling Approaches

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Fernando Camacho¹  Beatriz Fuster¹  Jadunandan Dash²  Luke A. Brown²  Booker O. Ogutu² 

[1] Earth Observation Laboratory, Paterna, Spain;School of Geography and Environmental Science, University of Southampton, Southampton, U.K.;

关键词: Digital hemispherical photography (DHP);    INFORM;    LAI;    Sentinel-2;    validation;    vegetation indices;   

DOI  :  10.1109/JSTARS.2020.3040080

来源: DOAJ

【 摘 要 】

To further progress the validation of global leaf area index (LAI) products, temporally continuous reference data are a key requirement, as periodic field campaigns fail to adequately characterize temporal dynamics. Progress in cost-effective automated measurement techniques has been made in recent years, but appropriate upscaling methodologies are less mature. Recently, the use of multitemporal transfer functions has been proposed as a potential solution. Using data collected during an independent field campaign, we evaluated the performance of both vegetation index-based multitemporal transfer functions and a radiative transfer model (RTM)-based upscaling approach. Whether assessed using cross validation or data from the independent field campaign, the RTM-based approach provided the best performance (r² ≥ 0.88, RMSE ≤ 0.41, NRMSE <; 13%). For upscaling temporally continuous in situ data, the ability of RTM-based approaches to account for seasonal changes in sun-sensor geometry is a key advantage over vegetation index-based multitemporal transfer functions.

【 授权许可】

Unknown