文章基本信息

标题：Analysing the Recent Dynamics of Agricultural Sustainability in Portugal Using a Compromise Programming Approach
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作者：Xavier, António ; Costa Freitas, Maria de Belém ; Fragoso, Rui 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2022
卷号：14
期号：19
页码：1-16
DOI：10.3390/su141912512
语种：English
出版社：MDPI, Open Access Journal
摘要：Society recognises the importance of agriculture to supply goods, which are essential for human survival and well-being. Sustainable agriculture is an important goal since resources need to be preserved for future generations. The recent agricultural policy orientations towards environmental concerns have also had consequences for Portuguese agriculture. The information provided by the 2019 Agricultural Census offers an opportunity to analyse the recent dynamics and establish rankings of municipalities related to agricultural sustainability. Sustainability in agriculture can be studied using different types of indicators, but its quantification and aggregation into an index is still difficult. This paper proposes an approach based on compromise programming to analyse sustainability considering the dynamics between the 2009 and 2019 Agricultural Census. This approach has three main steps: in the first one, the indicators are selected and a HJ-Biplot and Cluster analysis are carried out to identify groups of municipalities and general dynamics; in the second step, the weights of indicators are defined, and a novel compromise programming model is implemented to define the rankings of sustainability for each year; finally, in the third step, the spatial dynamics of the sustainability rankings are analysed and classified into the clusters of municipalities previously created. The analysis was implemented using data from the 308 Portuguese municipalities for 12 individual indicators encompassing the several dimensions of sustainability. The results were promising since the approach allowed for the identification of the main dynamics and tendencies regarding sustainability.
关键词：agricultural sustainability; agricultural census; HJ-Biplot; cluster analysis; compromise programming