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Lookup NU author(s): Dr Francisco ArealORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Farm-level sustainable intensification metrics are needed to evaluate farm performance and support policy-making processes aimed at enhancing sustainable production. Farm-level sustainable intensification metrics require environmental impacts associated with agricultural production to be accounted for. However, it is common that such indicators are not available. We show how satellite-based remote sensing information can be used in combination with farm efficiency analysis to obtain a sustainable intensification (SI) indicator, which can serve as a sustainability benchmarking tool for farmers and policy makers. We obtained an SI indicator for 114 maize farms in Yangxin County, located in the Shandong Province in China, by combining information on maize output and inputs with satellite information on the leaf area index (from which a nitrogen environmental damage indicator is derived) into a farm technical efficiency analysis using a stochastic frontier approach. We compare farm-level efficiency scores between models that incorporate environmental damage indicators based on satellite-based remote sensing information and models that do not account for environmental impact. The results demonstrate that (a) satellite-based information can be used to account for environmental impacts associated with agriculture production and (b) how the environmental impact metrics derived from satellite-based information combined with farm efficiency analysis can be used to obtain a farm-level sustainable intensification indicator. The approach can be used to obtain tools for farmers and policy makers aiming at improving SI.
Author(s): Areal FJ, Yu W, Tansey K, Liu J
Publication type: Article
Publication status: Published
Journal: Sustainability
Year: 2022
Volume: 14
Issue: 3
Online publication date: 05/02/2022
Acceptance date: 03/02/2022
Date deposited: 05/02/2022
ISSN (electronic): 2071-1050
Publisher: MDPI
URL: https://doi.org/10.3390/su14031832
DOI: 10.3390/su14031832
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