Exploring the changes of ecosystem services value caused by land use transformation driven by urbanization is crucial for ensuring the safety of the regional ecological environment and for enhancing the value of ecosystem services. Based on the land use remote sensing data during the rapid urbanization development period of Hubei Province from 1995 to 2015, this study analyzed the characteristics of land use/land cover change and land use transformation. The spatial–temporal response characteristics and evolution of ecosystem services value (ESV) to land use transformation driven by urbanization were measured by equivalent factor method, spatial autocorrelation analysis, hot spot analysis and gravity model. We found that: (1) Driven by urbanization, the most significant feature of land use transformation in Hubei Province was the expansion of the built-up land and the significant reduction of cropland and forest, among which 90% of the new built-up land was converted from cropland and forest. (2) This land use transformation became the main source of ESV losses. Especially, the sharp increase of the built-up land from 2010 to 2015, occupying cropland and forest, resulted in ESV losses of nearly USD 320 million. The service capacity of climate regulation, soil conservation, gas regulation and food production undertaken by cropland and forest decreased. (3) The ecosystem services value in the study area showed spatial distribution characteristics of high in the west and low in the middle and east regions. The center of gravity of ESV shifted from northwest to southeast. Due to the sharp increase of the built-up land from 2010 to 2015, the center of gravity shift rebounded. This study can help policymakers better understand the trade−offs between land use transformation and ecosystem services driven by urbanization.
Agriculture is the foundation of the national economy, and achieving high-quality agricultural development is an important support for strong economic development in the post-pandemic era. Based on the new development philosophy of the Chinese government, this study constructs an evaluation framework of “innovation-coordination-green-openness-sharing” for high-quality agricultural development, and quantitatively assesses the level of high-quality agricultural development in China's Yangtze River Economic Belt with a systematic integration model, and explores the spatial evolution characteristics and obstacles of the level of high-quality agricultural development in Yangtze River Economic Belt. It reveals that the level of high-quality agricultural development in the Yangtze River Economic Belt shows a fluctuating upward trend in general, but there is variability among regions. The green dimension has the fastest development rate, followed by innovation and sharing. In terms of spatial characteristics, it gradually shows a pattern dominated by high levels and shows the characteristics of agglomeration, but the spatial correlation is not high. In terms of obstacle factors, openness and coordination are the main obstacle factors. Considering the different agricultural development models, it is suggested that international cooperation, new agricultural cooperation, and differentiated policies can be considered to promote high-quality agricultural development. This study provides a more complete evaluation framework for government policy-making authorities to measure the level of regional agricultural development and help regional agriculture achieve sustainable development at a higher quality level.
Real estate investment has been an important driving force in China’s economic growth in recent years, and the relationship between real estate investment and PM2.5 concentrations has been attracting widespread attention. Based on spatial econometric modelling, this paper explores the relationships between real estate investment and PM2.5 concentrations using multi-source panel data from 30 provinces in China between 1987 and 2017. The results demonstrate that compared with static spatial panel modelling, using a dynamic spatial Durbin lag model (DSDLM) more accurately reflects the influences of real estate investment on PM2.5 concentrations in China, and that PM2.5 concentrations show significant superposition effects and spillover effects. Moreover, there is an inverted U-shaped relationship between real estate investment and PM2.5 concentrations in the Eastern and Central Regions of China. At the national level, the impacts of real estate investment on land urbanization and PM2.5 concentrations first increased and then decreased over time. The key implications of this analysis are as follows. (1) it highlights the need for a unified PM2.5 monitoring platform among Chinese regions; (2) the quality of population urbanization rather than land urbanization should be given more attention; and (3) the speed of construction of green cities and building of green transportation systems and green town systems should be increased.
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