Recovering forecast distributions of crop composition: Method and application to kentucky agriculture

Gwan Seon Kim; Mehdi Nemati; Steven Buck; Nicholas Pates; Tyler Mark

doi:10.3390/su12072917

Recovering forecast distributions of crop composition: Method and application to kentucky agriculture

Gwan Seon Kim
, Mehdi Nemati
, Steven Buck
, Nicholas Pates
, Tyler Mark

Producción científica: Article › revisión exhaustiva

2 Citas (Scopus)

Resumen

This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.

Idioma original	English
Número de artículo	2917
Publicación	Sustainability (Switzerland)
Volumen	12
N.º	7
DOI	https://doi.org/10.3390/su12072917
Estado	Published - abr 1 2020

Nota bibliográfica

Publisher Copyright:
© 2020 by the authors.

Financiación

Funding: This research was funded by National Science Foundation (NSF), grant number 1355438.

Financiadores	Número del financiador
National Science Foundation Arctic Social Science Program	1355438

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Affordable and clean energy
Life on land

ASJC Scopus subject areas

Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Management, Monitoring, Policy and Law

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title = "Recovering forecast distributions of crop composition: Method and application to kentucky agriculture",

abstract = "This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.",

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AU - Kim, Gwan Seon

AU - Nemati, Mehdi

AU - Buck, Steven

AU - Pates, Nicholas

AU - Mark, Tyler

PY - 2020/4/1

Y1 - 2020/4/1

N2 - This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.

AB - This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.

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KW - Multinomial logit model

KW - Simulation

KW - Transition probability

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VL - 12

JO - Sustainability (Switzerland)

JF - Sustainability (Switzerland)

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Recovering forecast distributions of crop composition: Method and application to kentucky agriculture

Resumen

Nota bibliográfica

Financiación

ODS de las Naciones Unidas

ASJC Scopus subject areas

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