The County-Scale Economic Spatial Pattern and Influencing Factors of Seven Urban Agglomerations in the Yellow River Basin—A Study Based on the Integrated Nighttime Light Data

Abstract

The integrated night light (NTL) datasets were used to represent the economic development level, and visual analysis was carried out on the evolution characteristics of the economic spatial pattern of various urban agglomerations in the Yellow River Basin (YRB), at a county-scale, in 1992, 2005, and 2018. The Global Moran’s I and the local Getis-Ord G methods were used to explore the overall spatial correlation and local cold–hot spot of economic development levels, respectively. The spatial heterogeneity of the influence of relevant factors on the economic development level at the municipal scale was analyzed by using the multi-scale geographically weighted regression (MGWR) model. The results show that the county-level economic spatial pattern of urban agglomeration in the YRB has an obvious “pyramid” characteristic. The hot spots are concentrated in the hinterland of the Guanzhong Plain, the Central Plains, and the Shandong Peninsula urban agglomeration. The cold spots are concentrated in the junction of urban agglomerations, and the characteristics of “cold in the west and hot in the east” are obvious. Labor input and import and exporthave a positive impact on the economic development level for each urban agglomeration, government force has a negative impact, and education shows both positive and negative polarization on economic development.

Spatiotemporal Dynamic Distribution, Regional Differences and Spatial Convergence Mechanisms of Carbon Emission Intensity: Evidence from the Urban Agglomerations in the Yellow River Basin

“…However, the development basis, development path and strategic positioning of each urban agglomeration in the YRB are different, and the results of carbon emission reduction in recent years are also different. To promote low-carbon transformation and high-quality development in the YRB, it is necessary not only to clarify the overall carbon emission conditions but also to conduct heterogeneity analysis from the perspective of urban agglomeration differences and coordinated development [ 28 , 29 ]. At present, there are few studies on distribution dynamics, differential changes and mechanisms of carbon emission reduction from the perspective of urban agglomerations in the YRB, and there is still a lack of empirical analysis on how to better promote the process of carbon emission reduction in urban agglomerations in the YRB.…”