Urban Expansion Assessment Based on Optimal Granularity in the Huaihe River Basin of China

Determining the optimal granularity, which has often been ignored in the analysis of urban expansion and its landscape pattern, is the core problem in landscape ecology research. Here, we calculate the optimal granularities for differently sized cities in the Huaihe River Basin of China based on scale transformation and area loss evaluation. Accordingly, we construct a landscape index and urban land density function to analyze urban expansion and landscape pattern. The results can be summarized as follows. (1) Within the first scale domain of the landscape indices, the optimal granularities of Zhengzhou, Xuzhou, Yancheng, Xinyang, and Bozhou are 60 m, 50 m, 40 m, 40 m, and 40 m, respectively, which are the optimal units in the study of urban expansion. (2) The urban land density decreases from the urban center to the outskirts, the urban core of each city is more compact than the outskirts, and the land density curve parameter α of Zhengzhou is the largest at 4.693 and its urban core the most compact. (3) There are significant spatial and temporal differences in the urban land densities of differently sized cities. The urban land density functions of different cities are similar before 2000; after that, they are similar to the standard inverse S-shaped function and the land use density curve of large cities is closer to the standard inverse S-shaped function than that of small- and medium-sized cities. (4) Large cities have faster expansion, much larger land density curve parameter c than medium- and small-cities, stronger linkage development with surrounding areas, and a higher degree of urban centralization. Urban expansion compactness was influenced by urban locations and functions except for urban sizes. This study offers a method for identifying the optimal granularities for differently sized cities and also provides information for the decision-making efforts that concern the rapid urbanization in major grain-producing areas of China.