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New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices. / Menzhulin, Gennady; Shamshurina, Natalya; Pavlovsky, Artyom; Kogan, Felix.

Use of Satellite and In-Situ Data to Improve Sustainability. ed. / Felix Kogan; Alfred Powell; Oleg Fedorov. 2011. p. 105-112 (NATO Science for Peace and Security Series C: Environmental Security; Vol. 97).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

Harvard

Menzhulin, G, Shamshurina, N, Pavlovsky, A & Kogan, F 2011, New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices. in F Kogan, A Powell & O Fedorov (eds), Use of Satellite and In-Situ Data to Improve Sustainability. NATO Science for Peace and Security Series C: Environmental Security, vol. 97, pp. 105-112. https://doi.org/10.1007/978-90-481-9618-0_12

APA

Menzhulin, G., Shamshurina, N., Pavlovsky, A., & Kogan, F. (2011). New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices. In F. Kogan, A. Powell, & O. Fedorov (Eds.), Use of Satellite and In-Situ Data to Improve Sustainability (pp. 105-112). (NATO Science for Peace and Security Series C: Environmental Security; Vol. 97). https://doi.org/10.1007/978-90-481-9618-0_12

Vancouver

Menzhulin G, Shamshurina N, Pavlovsky A, Kogan F. New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices. In Kogan F, Powell A, Fedorov O, editors, Use of Satellite and In-Situ Data to Improve Sustainability. 2011. p. 105-112. (NATO Science for Peace and Security Series C: Environmental Security). https://doi.org/10.1007/978-90-481-9618-0_12

Author

Menzhulin, Gennady ; Shamshurina, Natalya ; Pavlovsky, Artyom ; Kogan, Felix. / New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices. Use of Satellite and In-Situ Data to Improve Sustainability. editor / Felix Kogan ; Alfred Powell ; Oleg Fedorov. 2011. pp. 105-112 (NATO Science for Peace and Security Series C: Environmental Security).

BibTeX

@inbook{fee6a129e06948bc8e1188bac8e20037,
title = "New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices",
abstract = "In the late 1970s, the first operational weather satellite system had been launched, which showed utility for monitoring land greenness, vigor and vegetation productivity. Currently, 30-year satellite data from the Advanced Very High Resolution Radiometer (AVHRR) are available for monitoring land surface, atmosphere near the ground, natural disasters, and socioeconomic activities. Statistical modeling of agricultural crop yield and production was one of the applications. This paper discusses the topic, how design the new regression models of yield anomaly based on multivariate algorithms and selection of best- fit ensemble of predictors.",
keywords = "Crop yields anomaly, Models, Precipitation, Temperature, Vegetation health indices",
author = "Gennady Menzhulin and Natalya Shamshurina and Artyom Pavlovsky and Felix Kogan",
year = "2011",
doi = "10.1007/978-90-481-9618-0_12",
language = "English",
isbn = "9789048196173",
series = "NATO Science for Peace and Security Series C: Environmental Security",
pages = "105--112",
editor = "Felix Kogan and Alfred Powell and Oleg Fedorov",
booktitle = "Use of Satellite and In-Situ Data to Improve Sustainability",

}

RIS

TY - CHAP

T1 - New Regression Models for Prediction of Grain Yield Anomalies from Satellite-Based Vegetation Health Indices

AU - Menzhulin, Gennady

AU - Shamshurina, Natalya

AU - Pavlovsky, Artyom

AU - Kogan, Felix

PY - 2011

Y1 - 2011

N2 - In the late 1970s, the first operational weather satellite system had been launched, which showed utility for monitoring land greenness, vigor and vegetation productivity. Currently, 30-year satellite data from the Advanced Very High Resolution Radiometer (AVHRR) are available for monitoring land surface, atmosphere near the ground, natural disasters, and socioeconomic activities. Statistical modeling of agricultural crop yield and production was one of the applications. This paper discusses the topic, how design the new regression models of yield anomaly based on multivariate algorithms and selection of best- fit ensemble of predictors.

AB - In the late 1970s, the first operational weather satellite system had been launched, which showed utility for monitoring land greenness, vigor and vegetation productivity. Currently, 30-year satellite data from the Advanced Very High Resolution Radiometer (AVHRR) are available for monitoring land surface, atmosphere near the ground, natural disasters, and socioeconomic activities. Statistical modeling of agricultural crop yield and production was one of the applications. This paper discusses the topic, how design the new regression models of yield anomaly based on multivariate algorithms and selection of best- fit ensemble of predictors.

KW - Crop yields anomaly

KW - Models

KW - Precipitation

KW - Temperature

KW - Vegetation health indices

UR - http://www.scopus.com/inward/record.url?scp=84883074112&partnerID=8YFLogxK

U2 - 10.1007/978-90-481-9618-0_12

DO - 10.1007/978-90-481-9618-0_12

M3 - Chapter

AN - SCOPUS:84883074112

SN - 9789048196173

T3 - NATO Science for Peace and Security Series C: Environmental Security

SP - 105

EP - 112

BT - Use of Satellite and In-Situ Data to Improve Sustainability

A2 - Kogan, Felix

A2 - Powell, Alfred

A2 - Fedorov, Oleg

ER -

ID: 92642401