Estimation and Influencing Factors of Green Utilization Efficiency of Cultivated Land in Northeast China
Promoting the green utilization of cultivated land in Northeast China is an important way to practice the concept of green development and promote the protection of black land.The super efficiency SBM model including non-expected output and the Tobit model were comprehensively used to quantitatively measure the spatial and temporal distribution pattern and influencing factors of green utilization efficiency of cultivated land in 40 prefecture-level cities,Northeast China from 2012 to 2021.The results show that ① from 2012 to 2021,the overall green utilization efficiency of cultivated land in Northeast China is relatively high,while the efficiency of each region in Northeast China begins to fluctuate and decline after 2018,and then rebounds after 2020;② the spatial difference of green utilization efficiency of cultivated land in Northeast China is significant,and its distribution pattern gradually changes over time,showing the evolution characteristics of"high in the east and low in the west","high around,low in the middle",and"high in the north and south,low around"during the study period;③ the proportion of grain crop rotation area and the total power of agricultural machinery per unit of crop sown area have a significant negative impact on the green utilization efficiency of cultivated land in Northeast China,and the level of scientific and technological development has a significant positive impact;however,the influence intensities of factors are different in different regions.The suggestions should be standardized and guided in policies and institutions,technical support and empowerment should also be provided,so as to improve the green utilization efficiency of cultivated land in Northeast China through practical measures and realize the sustainable use of black land.
cultivated landgreen utilization efficiencysuper efficiency SBM modelTobit modelinfluencing factorblack land protectionNortheast China
NETL
NSTL
万方数据
