典型文献
Detecting the linkage between arable land use and poverty using machine learning methods at global perspective
文献摘要：
Eradicating extreme poverty is one of the UN's primary sustainable development goals (SDG). Arable land is related to eradicating poverty (SDG1) and hunger (SDG2). However, the linkage between arable land use and poverty reduction is ambiguous and has seldom been investigated globally. Six indicators of agricultural inputs, crop intensification and extensification were used to explore the relationship between arable land use and poverty. Non-parametric machine learning methods were used to analyze the linkage between agriculture and poverty at the global scale, including the classification and regression tree (CART) and random forest models. We found that the yield gap, fertilizer consumption and potential cropland ratio in protected areas correlated with poverty. Developing countries usually had a ratio of actual to potential yield less than 0.33 and fertilizer consumption less than 7.31 kg/ha. Overall, crop extensification, intensification and agricultural inputs were related to poverty at the global level.
文献关键词：
中图分类号：
作者姓名：
Fuyou Tian;Bingfang Wu;Hongwei Zeng;Gary R Watmough;Miao Zhang;Yurui Li
作者机构：
State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Geosciences,University of Edinburgh,EH89XP Edinburgh,United Kingdom;Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;Key Laboratory of Regional Sustainable Development Modelling,Chinese Academy of Sciences,Beijing 100101,China
文献出处：
引用格式：
[1]Fuyou Tian;Bingfang Wu;Hongwei Zeng;Gary R Watmough;Miao Zhang;Yurui Li-.Detecting the linkage between arable land use and poverty using machine learning methods at global perspective)[J].地理学与可持续性（英文）,2022(01):7-20
A类：
Eradicating,Arable,SDG1,SDG2,extensification
B类：
Detecting,linkage,between,arable,poverty,using,machine,learning,methods,perspective,extreme,is,one,UN,primary,sustainable,development,goals,eradicating,hunger,However,reduction,ambiguous,has,seldom,been,investigated,globally,Six,indicators,agricultural,inputs,intensification,were,used,explore,relationship,Non,parametric,analyze,agriculture,scale,including,classification,regression,tree,CART,random,forest,models,We,found,that,yield,gap,fertilizer,consumption,potential,cropland,ratio,protected,areas,correlated,Developing,countries,usually,had,actual,less,than,Overall,level
AB值：
0.479003
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