Do Land Use Structure Changes Impact Regional Carbon Emissions? A Spatial Econometric Study in Sichuan Basin, China

Abstract

Human activities are closely related to carbon emissions and the mechanism of land-use structure change on carbon emissions is unclear. In this study, 143 counties in the Sichuan Basin of China were used as sample units, and the land use structure of each sample unit in the Sichuan Basin was measured by applying the information entropy theory, analyzing the spatial and temporal evolutionary characteristics and the influencing relationships of land use structure and carbon emissions in the Sichuan Basin, by spatial econometric analysis of panel data on carbon emissions and information entropy of land use structure over five time periods from 2000 to 2018. The results indicate that: the carbon emission intensity and information entropy of land use in the Sichuan basin are increasing over the years, and the cross-sectional data reflect inconsistent spatial distribution characteristics, with greater changes around large cities; both carbon emissions and land use structure are spatially auto-correlated, the information entropy of land use positively affects carbon emission intensity; carbon emissions have positive spillover effects, and changes in land use structure have no obvious regional impact on surrounding areas; there may be potential threshold areas for the impact of land-use structure change on carbon emissions. This study has certain reference value for land use planning and carbon emission reduction policies.

Land-Use Carbon Emissions in the Yellow River Basin from 2000 to 2020: Spatio-Temporal Patterns and Driving Mechanisms

“…According to this study’s findings, which are consistent with those of earlier studies [ 22 , 46 ], construction land is the primary carbon source, whereas forest lands provide the strongest carbon sequestration processes. This study discovers that net carbon emissions in the Yellow River Basin have an obvious spatial link and that the spatial distribution follows a southeast-to-northwest pattern, which is in accordance with the opinions of academics such as Ma Yuan [ 47 ].…”

Can Mixed Land Use Reduce CO2 Emissions? A Case Study of 268 Chinese Cities

“…Then, the Canadian scholar Thakur applied it into geography [54]. On this basis, scholars used information entropy to analyze the land use structure at different scales [55][56][57]. For example, Fan et al suggested that the volatility of LUCC can be reflected by information entropy [58].…”

Determinants of land-use and cover change: role of natural resources and human activities in spatial-temporal evolution

“…Currently, the use of remote sensing technology to investigate LUCC has been the first option for many academics because continuously developing remote sensing technology offers a new technological means for LUCC research, which is essential in this field 26 – 30 The dynamic degree, 31 – 33 transition matrix model, 34 – 36 land use extent composite index model, 35 , 37 land-use structure information entropy, 38 spatial autocorrelation analysis, 39 – 41 and other indicators and methods have been used to study LUCC. Advancing research can provide a deeper understanding of the evolutionary process of land-use development, with some statistical models that are able to simulate future trends of land-use change emerging, such as future land-use simulation 42 , 43 and land use and its effects 44 , 45 .…”