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Evaluation of remote sensing approaches to monitor crop conditions under specific input levels and cropping diversity

dc.contributor.authorGuo, X.
dc.contributor.authorZheng, Y.
dc.contributor.authorOlfert, O.
dc.contributor.authorBrandt, S.A.
dc.contributor.authorThomas, A.G.
dc.contributor.authorWeiss, R.M.
dc.contributor.authorSproule, L.
dc.date.accessioned2018-08-29T19:07:24Z
dc.date.available2018-08-29T19:07:24Z
dc.date.issued2004-02-19
dc.description.abstractThis study was conducted as part of the Alternative Cropping Systems (ACS) study at Scott, Saskatchewan. The 18 year study was initiated in 1995 to evaluate the sustainability of nine arable crop production systems. The nine cropping systems, derived from combinations of three input levels (organic, reduced, and high) and three cropping diversity levels (low, diversified annual grains, and diversified annual perennials), were designed to monitor and assess alternative input use and cropping strategies for arable crop production on the Canadian Prairies. Field data including leaf area index (LAI) and spectral reflectance were collected three times during the growing season of 2003: early growing season (June), mid growing season (July) and late growing season (August). LAI was measured with an LAI-2000 plant canopy analyzer. The spectral measurements were made with a handheld ADS spectroradiometer, which covers wavelengths from 350 nm to 2500 nm with 2151 bands. Results showed that remote sensing can be used to indicate different crop conditions. The spectral and LAI differences among input levels were significant at early to mid growing seasons. Mid July was the best season and the red over near infrared spectral ratio as well as the normalized difference vegetation index based on these two bands were the best vegetation indices to use for crop vigor monitoring.en_US
dc.description.versionNon-Peer Reviewed
dc.identifier.urihttp://hdl.handle.net/10388/9634
dc.language.isoenen_US
dc.relation.ispartofSoils and Crops Workshop
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/ca/*
dc.subjectcropsen_US
dc.subjectinput and diversity levelsen_US
dc.subjectleaf area index (LAI)en_US
dc.subjecthyperspectral remote sensingen_US
dc.subjectvegetation indices (VIs)en_US
dc.titleEvaluation of remote sensing approaches to monitor crop conditions under specific input levels and cropping diversityen_US
dc.typePresentationen_US

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