Deriving leaf area index reference maps using temporally continuous data: a comparison of upscaling approaches

Brown, LA ORCID: https://orcid.org/0000-0003-4807-9056, Ogutu, BO, Camacho, F, Fuster, B and Dash, J 2020, 'Deriving leaf area index reference maps using temporally continuous data: a comparison of upscaling approaches' , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14 , pp. 624-630.

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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.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 1939-1404
Depositing User: LA Brown
Date Deposited: 28 Oct 2022 10:01
Last Modified: 28 Oct 2022 10:15
URI: https://usir.salford.ac.uk/id/eprint/65379

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