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[1]HAN Huiqing,WANG Shiyao,MA Geng,et al.Analysis on Spatial Correlation Between Agricultural Carbon Emission Densities and Rural Economy in China[J].Research of Soil and Water Conservation,2018,25(05):269-274,281.

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Analysis on Spatial Correlation Between Agricultural Carbon Emission Densities and Rural Economy in China

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 25 Number of periods: 2018 05 Page number: 269-274,281 Column: Public date: 2018-09-06

Title:: Analysis on Spatial Correlation Between Agricultural Carbon Emission Densities and Rural Economy in China

Author(s):: HAN Huiqing¹, WANG Shiyao², MA Geng¹, ZHANG Xinding¹, BAI Yumei¹; 1. College of Architecture and Urban Planning, Guizhou Institute of Technology, Guiyang 550003, China;
2. College of Public Management, Guizhou University of Finance of Economics, Guiyang 550025, China

Keywords:: spatial correlation; agricultural carbon emissions density; rural economy; China

CLC:: F323

DOI:: -

Abstract:: In order to explore spatial correlation between agricultural carbon emissions density and rural economy in China, we selected chemical fertilizers, pesticides, agricultural films, agricultural diesel, irrigation and ploughing as carbon sources, and set per capita net income of farmers, agricultural GDP and grain yield per unit of arable land as agricultural economic indicators. The spatial correlation between agricultural carbon emission intensities and agricultural economic indexes were analyzed by the method of spatial autocorrelation analysis. The results showed that there was spatial positive correlation between agricultural carbon emission intensities and agricultural economic indexes such as per capita net income of farmers, agricultural GDP and grain yield per unit of arable land in China. High-high and low-low concentration areas were relatively more, while low-high and high-low concentrations areas were less; there was a spatial negative correlation between agricultural carbon intensity changes and per capita net income changes of farmers as well as grain yield changes per unit of arable lands in China while the spatial positive correlation could be found between agricultural carbon intensity changes and agricultural GDP changes per unit of arable land in China from 2001 to 2015. There was spatial heterogeneity in LISA aggregation area between agricultural carbon emission intensity change and agricultural economy index change.

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