Abstract
Abstract: National land spatial pattern optimization is an important step for the ecological civilization construction, and ecological carrying capacity study plays an indispensable role on spatial pattern optimization. Taking Ezhou City, Hubei Province as a demonstration area, based on the analysis of the characteristics of the resource, environment and socioeconomic state, this research used township as a unit, carried out a comprehensive evaluation and ecological capacity divisions, discussed the city's spatial pattern optimization plan, and put forward the guidelines for each main function zone. Firstly, the ecological capacity comprehensive evaluation model was built. Based on the cognition and analysis on compound ecosystem, this research built the hierarchical index model for the ecological capacity comprehensive evaluation on "capacity on resource environment, ecology elasticity and socioeconomic coordination". A total of 15 support indices and 10 pressure indices were set to reflect the level of each criterion layer, and the space state method was used to show each element state, which were prepared for the interconnection of the 3 criterion layers. Secondly, an empirical research on ecological capacity comprehensive evaluation was made. According to the ecological capacity comprehensive evaluation model, the entropy method and expert scoring method were used to determine the weight of every index. And the space state method counted the number of hierarchical indices and the number of capacity comprehensive indices for each evaluation unit. The results show: From the resource and environment capacity aspect, the low values are distributed in the main urban zone, including 4 administration communities i.e. Gulou, Fenghuang, Xishan, and Fankou, and the maximum value is located in Liangzi Town; from the ecological elasticity aspect, the maximum value is located in 11 towns such as Liangzi, Huahu, and Fenghuang; from the social-economic coordination aspect, the high value is distributed in the towns of Xisan, Fenghuang, Gulou, and so on, and the low value is mainly distributed in the northern Duandian, Huarong, Linjiang, and so on; from the ecological capacity comprehensive index value, the maximum value occurs in Liangzi, and the medium value zone is located in Gulou, Fenghuang, Fankou, and so on. Those areas either have high value in social-economic coordination but medium or low value in source and environment capacity and ecology elasticity, or have high value in source and environment capacity and ecology elasticity but low value in social-economic coordination ability. Thirdly, the relationships framework between ecological capacity comprehensive model and national land spatial pattern distribution optimization was built. According to the ecological capacity, a correlation analysis was made between criterion layers of ecological capacity and main function types, and the results were showed in magic cube: The resource and environment capacity, ecological elasticity, social-economic coordination corresponded to agriculture production zone, ecological protection zone and economic development zone, respectively. Fourthly, a scheme for the national land spatial pattern distribution optimization was put forward. Taking account of the differentiation characteristics of resource and environment capacity, ecology elasticity and social-economics coordinating ability, combining the current situation and development potential of the empirical city, this research finally divided the spatial pattern into 5 parts, including city economic core zone, city economic development zone, agriculture producing zone, ecology conservation zone and forbidden development zone. The conclusions included: The maximum value of comprehensive ecological capacity index was 0.2338, located in Liangzi Town, and the minimum value was 0.0509, located in Linjiang Town; the medium value of ecological capacity comprehensive index was from 0.0768 to 0.1128. This method provides a new feasible thought and effective measure for theory study on the national land spatial development pattern optimization.