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(2021)
Abstract
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 (r
2
≥ 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.
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Key words
Digital hemispherical photography (DHP),INFORM,LAI,Sentinel-2,validation,vegetation indices
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