Low-cost unmanned aerial vehicle-based digital hemispherical photography for estimating leaf area index: a feasibility assessment

Brown, LA ORCID: https://orcid.org/0000-0003-4807-9056, Sutherland, DH and Dash, J 2020, 'Low-cost unmanned aerial vehicle-based digital hemispherical photography for estimating leaf area index: a feasibility assessment' , International Journal of Remote Sensing, 41 (23) , pp. 9064-9074.

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Abstract

Unmanned aerial vehicles (UAVs) have the potential to provide highly detailed information on vegetation status useful in precision agriculture. However, challenges are associated with existing techniques for UAV-based retrieval of vegetation biophysical variables such as leaf area index (LAI), including variable illumination, bidirectional reflectance effects, and the need for image calibration, mosaicking, and normalization. We investigated an alternative approach that avoids these challenges whilst still providing spatially explicit estimates of LAI, using UAV-based digital hemispherical photography (DHP). LAI estimates were obtained using a low-cost UAV-based DHP system over a winter wheat field in Southern England. Point-based estimates were interpolated to provide spatially continuous datasets, which successfully described patterns of vegetation condition. The UAV-based DHP data were compared to ground-based LAI estimates, demonstrating good agreement (root mean square error (RMSE) = 0.10, normalized RMSE (NRMSE) = 3%).

Item Type:	Article
Schools:	Schools > School of Environment and Life Sciences
Journal or Publication Title:	International Journal of Remote Sensing
Publisher:	Taylor & Francis
ISSN:	0143-1161
Funders:	European Space Agency, University of Southampton Vice-Chancellor’s Scholarship.
Depositing User:	LA Brown
Date Deposited:	28 Oct 2022 09:15
Last Modified:	28 Oct 2022 09:15
URI:	https://usir.salford.ac.uk/id/eprint/65380

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