The coupling relationship and driving mechanism between urbanization and ecosystem services in the Yellow River Basin from a multi-spatial scale perspective.

Rapid urbanization has led to ecological destruction and associated issues. Macro policies wield substantial influence over urbanization and its relationship with the environment. Without considering the differences in scale, macro policies may be ineffective at addressing urbanization's adverse impacts on the environment, and even worsen this relationship. We used data on 622 counties, 76 prefectures, and 7 urban agglomerations in the Yellow River Basin to examine the development level, coupling coordination degree, and spatial patterns of urbanization and ecosystem services at three scales during 2000-2020. Further, we explored the driving mechanisms in the relationship between urbanization and ecosystem services. We found that: First, the coupling coordination was relatively low but showed an upward trend. A sizeable spatiotemporal difference existed, with higher (lower) coordination in the east (west). Second, the coupling coordination of each scale exhibited significant spatial positive correlations. The low-value heterogeneous region was embedded around the agglomeration region, and polarization was significant. The larger the scale, the stronger the agglomeration effect. Further, the coupling coordination spatial agglomeration effect of each scale gradually weakened over time. Third, the spatial and temporal distributions of coupling coordination and its agglomeration characteristics at different scales differed. The urban agglomeration scale showed significant overall coordination or agglomeration characteristics, and prefecture and county regions showed local and unique characteristics within urban agglomerations. Fourth, the dominant factors influencing the spatial patterns of the coupling coordination at the county, prefecture, and urban agglomeration scales differed. The interaction and factor detection showed linear and double-factor enhancements. We find that economic development, government policies, environmental protection, and natural factors are the combined effects of urbanization and ecosystem services. Our research method can provide a reference for other river basins, and the results can help governments in formulating policies for sustainable development at different spatial scales.

Spatiotemporal pattern and coordination relationship between urban residential land price and land use intensity in 31 provinces and cities in China.

The trend towards efficient and intensive use of land resources is an inevitable outcome of current social development. The rational matching of urban land prices and land use intensity has become an important factor under accelerating urbanization, and promotes the healthy development of the social economy. Using data on residential land price and on land use intensity for 31 provinces and cities in China, we employ the E-G cointegration test and quadrant map classification to determine the coordination relationship between land price and land use intensity. We then employ HR coordination to calculate the coordination degree of land price and land use intensity, and classify the coordination type accordingly. Our results are as follows. (1) The spatio-temporal distribution of urban land price shows high variability with multiple maxima, and follows a decreasing trend from the southeast coastal area to the northwest inland area and the northeast. (2) The overall land use intensity is at or above the middle level, and shows large spatial differences between provinces, but the agglomeration between provinces is increasing. (3) From the perspective of the relationship between urban land price and land use intensity at the inter-provincial scale, we find that the land price and land use intensity are well coordinated, and the number of provinces has been dynamically changing during different development periods. There is an east-west difference in the spatial distribution of land price and land use intensity coordination level. Different provinces and cities with the same coordination stage show differences in their land price and land use intensity level.