Estimating canola phenology using synthetic aperture radar

McNairn, Heather; Jiao, Xianfeng; Pacheco, Anna; Sinha, Abhijit; Tan, Weikai; Li, Yifeng

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Estimating canola phenology using synthetic aperture radar

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dc.contributor.author: McNairn, Heather; Jiao, Xianfeng; Pacheco, Anna; Sinha, Abhijit; Tan, Weikai; Li, Yifeng
dc.date.accessioned: 2023-04-14T16:56:32Z
dc.date.available: 2023-04-14T16:56:32Z
dc.date.issued: 2018-12-15
dc.description.abstract - en: Prolonged periods of wet soil conditions, when present during critical crop development stages, can significantly elevate the risk of some crop diseases. Wet soils in fields of flowering canola are a concern with respect to the development of sclerotinia as this pathogen feeds on the petals of the canola flower. As such, determining if canola is in bloom during periods of high moisture is important in deciding whether to take action to mitigate this disease. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization Synthetic Aperture Radar (SAR) data were used with a novel dynamic filtering framework to estimate canola growth stages. In this process, a new crop growth stage indicator was developed and SAR polarimetric parameters sensitive to changes in phenology were identified. Model development used multi-year SAR satellite and field data for one site in Manitoba, Canada. The crop growth estimator was then tested on unseen data from three sites, one in each of Canada's Prairie provinces. This independent validation established that the growth estimator was able to ac- curately determine canola growth stage and date of flowering with high accuracy. Correlation coefficients (r- values) between observed and estimated phenology ranged from 0.91 to 0.96. Given that this method performed well on test data from other sites and years, this approach could be widely adopted for monitoring the devel- opment of canola over extended regions.
dc.identifier.citation: McNairn, H., Jiao, X., Pacheco, A., Sinha, A., Tan, W., &; Li, Y. (2018). Estimating canola phenology using Synthetic Aperture Radar. Remote Sensing of Environment, 219, 196–205. https://doi.org/10.1016/j.rse.2018.10.012
dc.identifier.doi: https://doi.org/10.1016/j.rse.2018.10.012
dc.identifier.issn: 1879-0704
dc.identifier.uri: https://open-science.canada.ca/handle/123456789/169
dc.language.iso: en
dc.publisher: Elsevier
dc.rights.openaccesslevel - en: Green
dc.rights.openaccesslevel - fr: Vert
dc.subject - en: Agriculture
dc.subject - fr: Agriculture
dc.subject.en - en: Agriculture
dc.subject.fr - fr: Agriculture
dc.title - en: Estimating canola phenology using synthetic aperture radar
dc.title.fosrctranslation - fr: Estimating canola phenology using synthetic aperture radar
dc.type - en: Article
dc.type - fr: Article
local.article.journaltitle: Remote Sensing of Environment
local.article.journalvolume: 219
local.article.pagination: 196-205
local.peerreview - en: Yes
local.peerreview - fr: Oui