Cultivated Land Green Use Efficiency and Its Influencing Factors: A Case Study of 39 Cities in the Yangtze River Basin of China

Qiaowen Lin, Siran Bai and Rui Qi ()
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Qiaowen Lin: School of Economic and Management, China University of Geosciences, Wuhan 430074, China
Siran Bai: School of Economic and Management, China University of Geosciences, Wuhan 430074, China
Rui Qi: School of Economic and Management, China University of Geosciences, Wuhan 430074, China

Sustainability, 2023, vol. 16, issue 1, 1-14

Abstract: In recent years, the Chinese government has been paying more and more attention to agricultural development and ecological protection. Improving cultivated land green use efficiency (CLGUE) is becoming a crucial issue in promoting the sustainable development of agriculture. This study aims to study the current situation and influencing factors of agricultural production from the perspective of green utilization efficiency of cultivated land. It takes 39 cities in the upper, middle and lower reaches of the Yangtze River basin in China as an example. The CLGUE values in those 39 cities from 2011 to 2020 were specifically measured, using the Super-SBM model, kernel density estimation and geographic detector method. Their temporal and spatial heterogeneity was described, and the influencing factors were detected at both single and interactive levels. The results showed that (1) from 2011 to 2020, the green utilization efficiency value of cultivated land in the Yangtze River basin showed an upward trend on the whole; (2) there is clear spatial heterogeneity between CLGUE values in the Yangtze River basin cities, and the distribution is as follows: downstream region > midstream region > upstream region; (3) cultivated land resource endowment, socioeconomic development and agricultural production technology are important factors affecting the variability in CLGUE values. However, there are some differences in the degree and direction of influence of different influencing factors on different sample subgroups.

Keywords: CLGUE; kernel density estimation; geographic detector method; Yangtze River basin; regional differences (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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