Identification of High-Variation Fields based on Open Satellite Imagery

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Identification of High-Variation Fields based on Open Satellite Imagery. / Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus; Halberg, Anders; Toftegaard, Thomas Skjødeberg.

I: Advances in Animal Biosciences, Bind 8, Nr. 2, 01.06.2017, s. 388-393.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisKonferenceartikelForskningpeer review

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Author

Jeppesen, Jacob Høxbroe ; Jacobsen, Rune Hylsberg ; Nyholm Jørgensen, Rasmus ; Halberg, Anders ; Toftegaard, Thomas Skjødeberg. / Identification of High-Variation Fields based on Open Satellite Imagery. I: Advances in Animal Biosciences. 2017 ; Bind 8, Nr. 2. s. 388-393.

Bibtex

@inproceedings{da6cf73cefb142e9b708681549e4dbd2,
title = "Identification of High-Variation Fields based on Open Satellite Imagery",
abstract = "This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective. The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update of satellite imagery, hence coupling the geospatial data analysis to direct improvements for the farmers, contractors, and consultants.",
author = "Jeppesen, {Jacob H{\o}xbroe} and Jacobsen, {Rune Hylsberg} and {Nyholm J{\o}rgensen}, Rasmus and Anders Halberg and Toftegaard, {Thomas Skj{\o}deberg}",
note = "Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017); European Conference on Precision Agriculture, ECPA ; Conference date: 16-07-2017 Through 20-07-2017",
year = "2017",
month = jun,
day = "1",
doi = "10.1017/S2040470017000693",
language = "English",
volume = "8",
pages = "388--393",
journal = "Advances in Animal Biosciences",
issn = "2040-4700",
publisher = "Cambridge University Press",
number = "2",
url = "https://ecpa.delegate-everything.co.uk/",

}

RIS

TY - GEN

T1 - Identification of High-Variation Fields based on Open Satellite Imagery

AU - Jeppesen, Jacob Høxbroe

AU - Jacobsen, Rune Hylsberg

AU - Nyholm Jørgensen, Rasmus

AU - Halberg, Anders

AU - Toftegaard, Thomas Skjødeberg

N1 - Conference code: 11th

PY - 2017/6/1

Y1 - 2017/6/1

N2 - This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective. The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update of satellite imagery, hence coupling the geospatial data analysis to direct improvements for the farmers, contractors, and consultants.

AB - This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective. The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update of satellite imagery, hence coupling the geospatial data analysis to direct improvements for the farmers, contractors, and consultants.

U2 - 10.1017/S2040470017000693

DO - 10.1017/S2040470017000693

M3 - Conference article

VL - 8

SP - 388

EP - 393

JO - Advances in Animal Biosciences

JF - Advances in Animal Biosciences

SN - 2040-4700

IS - 2

T2 - European Conference on Precision Agriculture

Y2 - 16 July 2017 through 20 July 2017

ER -