区域建设用地开发强度格局演化及影响因素分析 ——以陕西省为例

区域建设用地开发强度是揭示土地利用效率、社会经济发展水平与国土空间开发状态的 重要指标，对其变化进行监测与管治是优化国土空间开发格局，实现区域可持续发展的重要手 段。构建建设用地开发强度量化模型，以陕西省为例，计算 2000—2015 年县域建设用地开发强度 指数，利用空间自相关分析方法揭示其空间格局和演化特征，并采用最小二乘法（OLS）和地理加权 回归（GWR）模型识别建设用地开发强度格局演化的影响因素。结果表明：（1）2000—2015 年陕西 省建设用地开发强度总体呈现增长态势，内部空间分异显著，高强度区集中在榆林、延安、西安、安 康等地，低强度区集中在咸阳、宝鸡、铜川、商洛、渭南、汉中等地。（2）陕西省建设用地开发强度呈 现出明显的空间集聚状态，热点区稳定分布在西安市辖区及周边区县，冷点区分布在延安南部、咸 阳、铜川、渭南和汉中等部分区域；县域建设用地开发强度逐步提升的同时，区域开发不平衡现象 日益突显。（3）固定资产投资、居民消费水平、财政投入力度、耕地资源和地形条件是影响陕西省建 设用地开发强度空间分异的主要因素，但在不同县域其影响程度大小具有显著差异，且个别因素 的影响具有不稳定性。

Pattern evolution and influencing factors of regional construction land development intensity：A case of Shaanxi Province

The development intensity of regional construction land is an important index to reveal the level of land use, the development of social economy, and the evolution of land spatial pattern. Monitoring and controlling the construction land development intensity can optimize the pattern of land spatial development and realize regional sustainable development. Shaanxi Province is located in the northwest of China, which can be divided into three regions according to its natural geographical characteristics: Loess Plateau, Guanzhong Plain, and Qinling-Daba mountain area. In recent years, there are many problems in the development and utilization of land resources in Shaanxi Province, such as the disordered expansion and extensive utilization of construction land, the idling of rural residential land, the overload of resources and environment in ecologically fragile areas, and the serious soil erosion and environmental pollution caused by overdevelopment. Therefore, this paper scientifically evaluates pattern evolution and influencing factors of construction land development intensity in counties of Shaanxi Province. At the same time, it effectively discriminates the overdevelopment zone and underdevelopment zone in the city. Both of them will have important practical significance for the orderly development and rational utilization of regional construction land. First, based on the land use remote sensing monitoring data and socio-economic statistical data, this paper selects the proportion of construction land (CLP), population carrying capacity (PCS), and economic development intensity (EDI) to calculate the construction land development intensity of counties in Shaanxi Province from 2000 to 2015. A spatial autocorrelation method is then used to reveal its spatial pattern and evolution characteristics. Finally, OLS and GWR models are used to identify the influencing factors of the pattern evolution of construction land development intensity. The results are shown as follows: (1) From 2000 to 2015, the construction land development intensity in Shaanxi Province showed an overall growth trend, but the internal space was significantly different. High-intensity areas were concentrated in the counties of Yulin, Yan’an, Xi’an, and Ankang, while low-intensity areas are concentrated in the counties of Xianyang, Baoji, Tongchuan, Shangluo, Weinan, and Hanzhong. (2) The construction land development intensity shows obvious spatial agglomeration state. Hot spots are stably distributed in Xi’an and surrounding counties, while cold spots are distributed in southern Yan’an, Xianyang, Tongchuan, Weinan, and Hanzhong. The imbalance of regional development is becoming more and more prominent as the construction land development intensity is gradually increasing. (3) Fixed asset investment, household consumption level, financial input, cultivated land resources and topographical conditions are the main factors affecting the spatial differentiation of construction land development intensity in Shaanxi Province. However, the degree of impact varies significantly in different counties, and the impact of individual factors exhibits instability. In addition, the innovation of this paper lies in the following: (1) With the help of remote sensing monitoring data of land use to carry out the long- term evaluation of construction land development intensity of counties, we make up for the deficiency of meso scale research; (2) From the perspective of factors affecting development intensity, OLS and GWR models are used to analyze the spatial heterogeneity of influencing factors, which enriches the research method.