Baishu Guo

Bio: Baishu Guo is an academic researcher from Hubei University. The author has contributed to research in topics: Agriculture & Agricultural productivity. The author has an hindex of 5, co-authored 5 publications receiving 200 citations.

Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014

Abstract: The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis (SFA) in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt (YREB) and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of additional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a “bar-like” distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran’s I within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association (LISA) statistic has enabled us to quantify characteristics of “small agglomeration and large dispersion”. Thus, “high- high” (H-H) agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by “low-low” (L-L) patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.

Designing a spatial pattern to rebalance the orientation of development and protection in Wuhan

Abstract: Patterns of spatial development and protection form a basic category of geoscience, and redesigning them is a popular subject of research in regional sustainable development that is important for ecological civilization construction. The authors here report a case study of Wuhan city using the circuit theory model and minimum cumulative resistance (MCR) model to rebalance its spatial protection and development. The results show the following: (1) Using the density of the gross domestic product (GDP), density of population, rate of urbanization, and access to transportation as evaluation indicators, seven core areas of development in Wuhan were identified, accounting for 59% of the total number of streets, that exhibited a “circular-satellite” spatial structure. (2) According to the importance of ecosystem services, ecological sensitivity, land use type, and slope of the terrain, the resistance surface of spatial development in Wuhan had a stereoscopic spatial form of an “inverted pyramid,” with high surroundings and a low center. The area of low resistance accounted for 6.64% of the total area of Wuhan. (3) Based on coupling analysis using the MCR and spatial morphological characteristics of current, nine axes of spatial development with a total area of 427.27 km2 and eight key strategic points with a total area of 40.02 km2 were identified. Streets that were prioritized for development accounted for 9.63% of Wuhan’s total area. (4) By combining the characterization of the development axis with the structure of the three-level core area, we extracted the structure of spatial development of “one heart, two wings, and three belts” in Wuhan. The research framework and empirical results can provide scientific guidance for the urban spatial layout, the development of regional linkages, and ecological environmental protection in China.

Analysis on the spatiotemporal patterns and driving mechanisms of China's agricultural production efficiency from 2000 to 2015

Abstract: Agricultural modernization is a key measure for China to promote the quality and efficiency of agricultural production in the new period. It aims to strengthen the basic status of agriculture's national economy and advocate a sustainable path plan for rural revitalization. Systematic analyses of the spatio-temporal evolution, spatial correlation characteristics, and external driving mechanisms of China's agricultural production efficiency is the scientific basis for the layout of agricultural space, the schedules formulation of agricultural modernization, and the implementation of the rural revitalization strategic goals. Based on the data sets of agricultural production, natural conditions, and socio-economic development at the municipal level in China from 2000 to 2015, the basic characteristics of agricultural production in China were explored using stochastic frontier analysis, spatial correlation analysis, and driving mechanism analysis. The results showed that: (1) The agricultural production efficiency has been reduced from 0.715 to 0.648, which has continued to maintain a steady decline, while the agricultural production efficiency has gradually become spatially heterogeneous and presents a significant ‘striped’ distribution. (2) The Moran's I of agricultural production efficiency increased from 0.4834 to 0.4908, and the spatial positive correlation clustering characteristics of H–H and L-L were relatively stable. (3) Differentiation of natural and socio-economic factors affects agricultural production efficiency. Natural conditions such as the diversity index and NDVI, and socio-economic factors such as the proportion of cropland and the proportion of GDP have become the dominant factors determining the agricultural production efficiency.