Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/55481
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dc.contributor.authorSinha, Priyakanten
dc.contributor.authorLamb, David Wen
dc.contributor.authorRobson, Andrewen
dc.date.accessioned2023-07-28T03:05:59Z-
dc.date.available2023-07-28T03:05:59Z-
dc.date.issued2018-
dc.identifier.urihttps://hdl.handle.net/1959.11/55481-
dc.description.abstract<p>There is currently no operational method of managing irrigation in Australia's sugar industry on the basis of systematic, direct monitoring of sugar plant physiology. Satellite remote sensing systems, having come a long way in the past 10 years now offer the potential to apply the current ground-based 'FAO' or 'crop coefficient (K<sub>c</sub>)' approach in a way that offers a synoptic view of crop water status across fields. In particular, multi-constellation satellite remote sensing, utilising a combination of freely available Landsat and Sentinel 2 imagery, supplemented by paid-for imagery from other existing satellite systems is capable of providing the necessary spatial resolution and spectral bands and revisit frequency. The significant correlations observed between K<sub>c</sub> and spectral vegetation indices (VIs), such as the widely used normalised difference vegetation index (NDVI) in numerous other crops bodes well for the detection and quantification of the spatial difference in evapotranspiration (ET<sub>c</sub>) in sugar which is necessary for irrigation scheduling algorithms. Whilst the NDVI may not serve as the appropriate index for sugarcane, given the potential of the NDVI to saturate at the high leaf area index observed in fully developed cane canopies, other VIs such as the Green-NDVI (GNDVI) may provide the response required. In practise, with knowledge of an appropriate K<sub>c</sub>-VI relationship, K<sub>c</sub> obtained from time-series (weekly) remotely sensed data, integrated with local agrometeorological data to provide ET<sub>o</sub>, would provide estimates of ET<sub>c</sub> from which site-specific irrigated water requirements (IWR) could be estimated. The use of UAVs equipped with multispectral sensors, even active optical sensors (AOS), to 'fill the gaps' in optical data acquisition due to cloud cover is conceivable. Cross calibration of any passive imaging system, as with the multi-constellation satellite data is essential. The use of radar images (microwave remote sensing) (for example, Sentinel 1&2 C-SAR, 5m) offers all weather, day-and-night capabilities although further work is necessary to understand the link between the radar back scatter, which is responding to surface texture, and evapotranspiration (and K<sub>c</sub>). Further R&D in ascertaining the K<sub>c</sub>-VI relationships during crop growth is necessary, as is the testing of multi-sensor cross-calibration and the relationship between radar remote sensing and K<sub>c</sub>. Existing irrigation advisory delivery systems in Australia such as IrriSAT should be investigated for their applicability to the sugar industry. The estimated season cost to a user for a sugarcane irrigation advisory service in Australia, based on the use of data from existing optical satellite imaging systems and utilising the K<sub>c</sub> approach, is likely to be of the order of US$2-3/ha.</p>en
dc.languageenen
dc.publisherPrecision Agriculture Research Group (PARG), School of Science and Technology, University of New Englanden
dc.titleAn assessment of the potential of remote sensing based irrigation scheduling for sugarcane in Australiaen
dc.typeReporten
local.contributor.firstnamePriyakanten
local.contributor.firstnameDavid Wen
local.contributor.firstnameAndrewen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailpsinha2@une.edu.auen
local.profile.emaildlamb@une.edu.auen
local.profile.emailarobson7@une.edu.auen
local.output.categoryR1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeArmidale, Australiaen
local.format.pages77en
local.contributor.lastnameSinhaen
local.contributor.lastnameLamben
local.contributor.lastnameRobsonen
dc.identifier.staffune-id:psinha2en
dc.identifier.staffune-id:dlamben
dc.identifier.staffune-id:arobson7en
local.profile.orcid0000-0002-0278-6866en
local.profile.orcid0000-0002-2917-2231en
local.profile.orcid0000-0001-5762-8980en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/55481en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleAn assessment of the potential of remote sensing based irrigation scheduling for sugarcane in Australiaen
local.output.categorydescriptionR1 Reporten
local.search.authorSinha, Priyakanten
local.search.authorLamb, David Wen
local.search.authorRobson, Andrewen
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2018en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/526e9f7f-c384-4f77-8dca-3a5695ea53f6en
local.subject.for2020300206 Agricultural spatial analysis and modellingen
local.subject.for2020300207 Agricultural systems analysis and modellingen
local.subject.seo2020260607 Sugaren
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeUNE Affiliationen
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