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Spatial distribution prediction of agro-ecological parameter using kriging. / Yakushev, Viktor; Petrushin, Aleksey; Mitrofanova, Olga; Mitrofanov, Evgenii; Terleev, Vitaly; Nikonorov, Aleksandr.

в: E3S Web of Conferences, Том 164, 06030, 05.05.2020.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

Harvard

Yakushev, V, Petrushin, A, Mitrofanova, O, Mitrofanov, E, Terleev, V & Nikonorov, A 2020, 'Spatial distribution prediction of agro-ecological parameter using kriging', E3S Web of Conferences, Том. 164, 06030. https://doi.org/10.1051/e3sconf/202016406030

APA

Yakushev, V., Petrushin, A., Mitrofanova, O., Mitrofanov, E., Terleev, V., & Nikonorov, A. (2020). Spatial distribution prediction of agro-ecological parameter using kriging. E3S Web of Conferences, 164, [06030]. https://doi.org/10.1051/e3sconf/202016406030

Vancouver

Yakushev V, Petrushin A, Mitrofanova O, Mitrofanov E, Terleev V, Nikonorov A. Spatial distribution prediction of agro-ecological parameter using kriging. E3S Web of Conferences. 2020 Май 5;164. 06030. https://doi.org/10.1051/e3sconf/202016406030

Author

Yakushev, Viktor ; Petrushin, Aleksey ; Mitrofanova, Olga ; Mitrofanov, Evgenii ; Terleev, Vitaly ; Nikonorov, Aleksandr. / Spatial distribution prediction of agro-ecological parameter using kriging. в: E3S Web of Conferences. 2020 ; Том 164.

BibTeX

@article{1f6e0bc43ee546fd92a3364ffba66ab7,
title = "Spatial distribution prediction of agro-ecological parameter using kriging",
abstract = "In modern agroecology, one of the most pressing problems is the problem of spatial data mapping. The development of information technology opens up a wide range of approaches for solving this problem. One of these approaches is based on the use of geostatistical methods. This study was carried out with the aim of developing ideas about the applicability of the ordinary kriging method for predicting the spatial distribution of the agro-ecological indicator with identifying the boundaries of in-field heterogeneity according to remote sensing data. For the model computational experiment, aerial photographs of the agricultural field in the red and near infrared ranges were used, which made it possible to obtain sets of uniformly distributed values of the vegetative index NDVI that were randomly generated. The high spatial resolution of the images allowed us to analyze the observational data for the studied agricultural field.",
author = "Viktor Yakushev and Aleksey Petrushin and Olga Mitrofanova and Evgenii Mitrofanov and Vitaly Terleev and Aleksandr Nikonorov",
year = "2020",
month = may,
day = "5",
doi = "10.1051/e3sconf/202016406030",
language = "English",
volume = "164",
journal = "E3S Web of Conferences",
issn = "2555-0403",
publisher = "EDP Sciences",
note = "Topical Problems of Green Architecture, Civil and Environmental Engineering 2019, TPACEE 2019 ; Conference date: 19-11-2019 Through 22-11-2019",
url = "https://www.e3s-conferences.org/articles/e3sconf/abs/2020/24/contents/contents.html",

}

RIS

TY - JOUR

T1 - Spatial distribution prediction of agro-ecological parameter using kriging

AU - Yakushev, Viktor

AU - Petrushin, Aleksey

AU - Mitrofanova, Olga

AU - Mitrofanov, Evgenii

AU - Terleev, Vitaly

AU - Nikonorov, Aleksandr

PY - 2020/5/5

Y1 - 2020/5/5

N2 - In modern agroecology, one of the most pressing problems is the problem of spatial data mapping. The development of information technology opens up a wide range of approaches for solving this problem. One of these approaches is based on the use of geostatistical methods. This study was carried out with the aim of developing ideas about the applicability of the ordinary kriging method for predicting the spatial distribution of the agro-ecological indicator with identifying the boundaries of in-field heterogeneity according to remote sensing data. For the model computational experiment, aerial photographs of the agricultural field in the red and near infrared ranges were used, which made it possible to obtain sets of uniformly distributed values of the vegetative index NDVI that were randomly generated. The high spatial resolution of the images allowed us to analyze the observational data for the studied agricultural field.

AB - In modern agroecology, one of the most pressing problems is the problem of spatial data mapping. The development of information technology opens up a wide range of approaches for solving this problem. One of these approaches is based on the use of geostatistical methods. This study was carried out with the aim of developing ideas about the applicability of the ordinary kriging method for predicting the spatial distribution of the agro-ecological indicator with identifying the boundaries of in-field heterogeneity according to remote sensing data. For the model computational experiment, aerial photographs of the agricultural field in the red and near infrared ranges were used, which made it possible to obtain sets of uniformly distributed values of the vegetative index NDVI that were randomly generated. The high spatial resolution of the images allowed us to analyze the observational data for the studied agricultural field.

UR - http://www.scopus.com/inward/record.url?scp=85085242405&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/bff17f20-18ae-35f6-ad21-416b7e8daf8c/

U2 - 10.1051/e3sconf/202016406030

DO - 10.1051/e3sconf/202016406030

M3 - Conference article

AN - SCOPUS:85085242405

VL - 164

JO - E3S Web of Conferences

JF - E3S Web of Conferences

SN - 2555-0403

M1 - 06030

T2 - Topical Problems of Green Architecture, Civil and Environmental Engineering 2019

Y2 - 19 November 2019 through 22 November 2019

ER -

ID: 53701635