Show simple item record

dc.contributor.authorMaire, Juliette
dc.contributor.authorGibson-Poole, Simon
dc.contributor.authorCowan, Nicholas
dc.contributor.authorReay, Dave S.
dc.contributor.authorRichards, Karl G.
dc.contributor.authorSkiba, Ute
dc.contributor.authorRees, Robert M.
dc.contributor.authorLanigan, Gary J.
dc.date.accessioned2023-06-26T15:27:54Z
dc.date.available2023-06-26T15:27:54Z
dc.date.issued2018-04-25
dc.identifier.citationMaire J, Gibson-Poole S, Cowan N, Reay DS, Richards KG, Skiba U, Rees RM and Lanigan GJ (2018) Identifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systems. Front. Sustain. Food Syst. 2:10. doi: 10.3389/fsufs.2018.00010en_US
dc.identifier.urihttp://hdl.handle.net/11019/2951
dc.descriptionpeer-revieweden_US
dc.description.abstractThe deposition of livestock urine and feces in grazed fields results in a sizable input of available nitrogen (N) in these soils; therefore significantly increasing potential nitrogen pollution from agricultural areas in the form of nitrous oxide (N2O), ammonia (NH3), and nitrate (NO3−). Livestock deposition events contributes to high spatial variability within the field and generate uncertainties when assessing the contribution that animal waste has on nitrogen pollution pathways. This study investigated an innovative technique for identifying the spatial coverage of urine deposition in grasslands without the need for manual soil measurements. A Remotely Piloted Aircraft System (RPAS) using a twin camera system was used to identify urine patches in a 5 ha field, which had been grazed by sheep 3 weeks previous to measurements. The imagery was processed using Agisoft Photoscan (Agisoft LLC) to produce true and false color orthomosaic imagery of the entire field. Imagery of five areas (225 m2) within the field were analyzed using a custom R script. For a total of 1,125 m2 of grassland, 12.2% of the area consisted of what was classified as urine patch. A simple up-scaling method was applied to these data to calculate N2O emissions for the entire field providing an estimate of 1.3–2.0 kg N2O-N ha−1 emissions from urine and fertilizer inputs.en_US
dc.language.isoenen_US
dc.publisherFrontiers Media SAen_US
dc.relation.ispartofseriesFrontiers in Sustainable Food Systems;Vol 2
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectRPASen_US
dc.subjectUAVen_US
dc.subjectimage analysisen_US
dc.subjectfeature detectionen_US
dc.subjecturineen_US
dc.subjectnitrous oxideen_US
dc.subjectgrasslanden_US
dc.titleIdentifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systemsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.3389/fsufs.2018.00010
dc.contributor.sponsorWalsh fellowship program by Teagascen_US
dc.contributor.sponsorBBSRC–Newton project UK-China Virtual Joint Centre for Improved Nitrogen Agronomy (CINAG)en_US
dc.source.volume2
refterms.dateFOA2023-06-26T15:27:56Z
dc.source.journaltitleFrontiers in Sustainable Food Systems


Files in this item

Thumbnail
Name:
fsufs-02-00010.pdf
Size:
2.386Mb
Format:
PDF
Description:
main article

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-ShareAlike 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International