4.6 Article

Measuring Sustainable Intensification Using Satellite Remote Sensing Data

Journal

SUSTAINABILITY
Volume 14, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/su14031832

Keywords

sustainable intensification; Bayesian stochastic frontier analysis; leaf area index

Funding

  1. Agri-Tech in the China: Newton Network+ [WK006]

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Farm-level sustainable intensification metrics are essential for evaluating farm performance and supporting policy-making processes. This study demonstrates how satellite-based remote sensing information combined with farm efficiency analysis can be used to obtain a sustainable intensification indicator. The results show that satellite-based information can account for environmental impacts in agriculture production, and the derived environmental impact metrics can be used to measure farm-level sustainable intensification.
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.

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