Use of oblique RGB imagery and apparent surface area of plants for an early estimation of above-ground corn biomass

Khun, Kosal; Tremblay, Nicolas; Panneton, Bernard; Vigneault, Philippe; Lord, Etienne; Cavayas, François; Codjia, Claude

Use of oblique RGB imagery and apparent surface area of plants for an early estimation of above-ground corn biomass

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creativework.keywords - en: corn; biomass; precision agriculture; precision farming; low-altitude remote sensing; remote sensing images; drone aircraft
creativework.keywords - fr: maïs; biomasse; préciculture; agriculture de précision; télédétection à basse altitude; images-satellite; drones
dc.contributor.author: Khun, Kosal; Tremblay, Nicolas; Panneton, Bernard; Vigneault, Philippe; Lord, Etienne; Cavayas, François; Codjia, Claude
dc.date.accepted: 2021-10-02
dc.date.accessioned: 2023-06-27T13:21:05Z
dc.date.available: 2023-06-27T13:21:05Z
dc.date.issued: 2021-10-09
dc.date.submitted: 2021-08-13
dc.description.abstract - en: Abstract Estimating above-ground biomass in the context of fertilization management requires the monitoring of crops at early stages. Conventional remote sensing techniques make use of vegetation indices such as the normalized difference vegetation index (NDVI), but they do not exploit the high spatial resolution (ground sampling distance < 5 mm) now achievable with the introduction of unmanned aerial vehicles (UAVs) in agriculture. The aim of this study was to compare image mosaics to single images for the estimation of corn biomass and the influence of viewing angles in this estimation. Nadir imagery was captured by a high spatial resolution camera mounted on a UAV to generate orthomosaics of corn plots at different growth stages (from V2 to V7). Nadir and oblique images (30° and 45° with respect to the vertical) were also acquired from a zip line platform and processed as single images. Image segmentation was performed using the difference color index Excess Green-Excess Red, allowing for the discrimination between vegetation and background pixels. The apparent surface area of plants was then extracted and compared to biomass measured in situ. An asymptotic total least squares regression was performed and showed a strong relationship between the apparent surface area of plants and both dry and fresh biomass. Mosaics tended to underestimate the apparent surface area in comparison to single images because of radiometric degradation. It is therefore conceivable to process only single images instead of investing time and effort in acquiring and processing data for orthomosaic generation. When comparing oblique photography, an angle of 30° yielded the best results in estimating corn biomass, with a low residual standard error of orthogonal distance (RSEOD = 0.031 for fresh biomass, RSEOD = 0.034 for dry biomass). Since oblique imagery provides more flexibility in data acquisition with fewer constraints on logistics, this approach might be an efficient way to monitor crop biomass at early stages.
dc.identifier.citation: Khun, K., Tremblay, N., Panneton, B., Vigneault, P., Lord, É., Cvayas, F., & Codjia, C. (2021). Use of oblique RGB imagery and apparent surface area of plants for early estimation of above-ground corn biomass. Remote Sensing, 13(20), 4032. https://doi.org/10.3390/rs13204032
dc.identifier.doi: https://doi.org/10.3390/rs13204032
dc.identifier.issn: 2072-4292
dc.identifier.uri: https://open-science.canada.ca/handle/123456789/890
dc.language.iso: en
dc.publisher: MDPI
dc.rights - en: Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights - fr: Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights.openaccesslevel - en: Gold
dc.rights.openaccesslevel - fr: Or
dc.rights.uri - en: https://creativecommons.org/licenses/by/4.0/
dc.rights.uri - fr: https://creativecommons.org/licenses/by/4.0/deed.fr
dc.subject - en: Agriculture
dc.subject - fr: Agriculture
dc.subject.en - en: Agriculture
dc.subject.fr - fr: Agriculture
dc.title - en: Use of oblique RGB imagery and apparent surface area of plants for an early estimation of above-ground corn biomass
dc.type - en: Article
dc.type - fr: Article
local.acceptedmanuscript.articlenum: 4032
local.article.journalissue: 20
local.article.journaltitle: Remote Sensing
local.article.journalvolume: 13
local.peerreview - en: Yes
local.peerreview - fr: Oui