King's College London

Research portal

Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI

Research output: Contribution to journalArticle

Standard

Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI. / Holman, Fenner Howard; Wooster, Martin John; Hawkesford, Malcolm; Riche, Andrew; Castle, March.

In: REMOTE SENSING, Vol. 11, No. 14, 1657, 07.2019.

Research output: Contribution to journalArticle

Harvard

Holman, FH, Wooster, MJ, Hawkesford, M, Riche, A & Castle, M 2019, 'Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI', REMOTE SENSING, vol. 11, no. 14, 1657. https://doi.org/10.3390/rs11141657

APA

Holman, F. H., Wooster, M. J., Hawkesford, M., Riche, A., & Castle, M. (2019). Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI. REMOTE SENSING, 11(14), [1657]. https://doi.org/10.3390/rs11141657

Vancouver

Holman FH, Wooster MJ, Hawkesford M, Riche A, Castle M. Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI. REMOTE SENSING. 2019 Jul;11(14). 1657. https://doi.org/10.3390/rs11141657

Author

Holman, Fenner Howard ; Wooster, Martin John ; Hawkesford, Malcolm ; Riche, Andrew ; Castle, March. / Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI. In: REMOTE SENSING. 2019 ; Vol. 11, No. 14.

Bibtex Download

@article{b86bec39467645a6befa0ac04df14845,
title = "Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI",
abstract = "Vegetation indices, such as the Normalised Difference Vegetation Index (NDVI), are common metrics used for measuring traits of interest in crop phenotyping. However, traditional measurements of these indices are often influenced by multiple confounding factors such as canopy cover and reflectance of underlying soil, visible in canopy gaps. Digital cameras mounted to Unmanned Aerial Vehicles offer the spatial resolution to investigate these confounding factors, however incomplete methods for radiometric calibration into reflectance units limits how the data can be applied to phenotyping. In this study, we assess the applicability of very high spatial resolution (1 cm) UAV-based imagery taken with commercial off the shelf (COTS) digital cameras for both deriving calibrated reflectance imagery, and isolating vegetation canopy reflectance from that of the underlying soil. We present new methods for successfully normalising COTS camera imagery for exposure and solar irradiance effects, generating multispectral (RGB-NIR) orthomosaics of our target field-based wheat crop trial. Validation against measurements from a ground spectrometer showed good results for reflectance (R2 ≥ 0.6) and NDVI (R2 ≥ 0.88). Application of imagery collected through the growing season and masked using the Excess Green Red index was used to assess the impact of canopy cover on NDVI measurements. Results showed the impact of canopy cover artificially reducing plot NDVI values in the early season, where canopy development is low.",
keywords = "Canopy reflectance, Digital cameras, NDVI, Radiometric calibration, Reflectance, Unmanned Aerial Vehicle",
author = "Holman, {Fenner Howard} and Wooster, {Martin John} and Malcolm Hawkesford and Andrew Riche and March Castle",
year = "2019",
month = "7",
doi = "10.3390/rs11141657",
language = "English",
volume = "11",
journal = "REMOTE SENSING",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "14",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Radiometric Calibration of ‘Commercial off the Shelf’ Cameras for UAV-Based High-Resolution Temporal Crop Phenotyping of Reflectance and NDVI

AU - Holman, Fenner Howard

AU - Wooster, Martin John

AU - Hawkesford, Malcolm

AU - Riche, Andrew

AU - Castle, March

PY - 2019/7

Y1 - 2019/7

N2 - Vegetation indices, such as the Normalised Difference Vegetation Index (NDVI), are common metrics used for measuring traits of interest in crop phenotyping. However, traditional measurements of these indices are often influenced by multiple confounding factors such as canopy cover and reflectance of underlying soil, visible in canopy gaps. Digital cameras mounted to Unmanned Aerial Vehicles offer the spatial resolution to investigate these confounding factors, however incomplete methods for radiometric calibration into reflectance units limits how the data can be applied to phenotyping. In this study, we assess the applicability of very high spatial resolution (1 cm) UAV-based imagery taken with commercial off the shelf (COTS) digital cameras for both deriving calibrated reflectance imagery, and isolating vegetation canopy reflectance from that of the underlying soil. We present new methods for successfully normalising COTS camera imagery for exposure and solar irradiance effects, generating multispectral (RGB-NIR) orthomosaics of our target field-based wheat crop trial. Validation against measurements from a ground spectrometer showed good results for reflectance (R2 ≥ 0.6) and NDVI (R2 ≥ 0.88). Application of imagery collected through the growing season and masked using the Excess Green Red index was used to assess the impact of canopy cover on NDVI measurements. Results showed the impact of canopy cover artificially reducing plot NDVI values in the early season, where canopy development is low.

AB - Vegetation indices, such as the Normalised Difference Vegetation Index (NDVI), are common metrics used for measuring traits of interest in crop phenotyping. However, traditional measurements of these indices are often influenced by multiple confounding factors such as canopy cover and reflectance of underlying soil, visible in canopy gaps. Digital cameras mounted to Unmanned Aerial Vehicles offer the spatial resolution to investigate these confounding factors, however incomplete methods for radiometric calibration into reflectance units limits how the data can be applied to phenotyping. In this study, we assess the applicability of very high spatial resolution (1 cm) UAV-based imagery taken with commercial off the shelf (COTS) digital cameras for both deriving calibrated reflectance imagery, and isolating vegetation canopy reflectance from that of the underlying soil. We present new methods for successfully normalising COTS camera imagery for exposure and solar irradiance effects, generating multispectral (RGB-NIR) orthomosaics of our target field-based wheat crop trial. Validation against measurements from a ground spectrometer showed good results for reflectance (R2 ≥ 0.6) and NDVI (R2 ≥ 0.88). Application of imagery collected through the growing season and masked using the Excess Green Red index was used to assess the impact of canopy cover on NDVI measurements. Results showed the impact of canopy cover artificially reducing plot NDVI values in the early season, where canopy development is low.

KW - Canopy reflectance

KW - Digital cameras

KW - NDVI

KW - Radiometric calibration

KW - Reflectance

KW - Unmanned Aerial Vehicle

UR - http://www.scopus.com/inward/record.url?scp=85071560215&partnerID=8YFLogxK

U2 - 10.3390/rs11141657

DO - 10.3390/rs11141657

M3 - Article

VL - 11

JO - REMOTE SENSING

JF - REMOTE SENSING

SN - 2072-4292

IS - 14

M1 - 1657

ER -

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454