准确量化中国建设用地空间结构是衡量建设用地生态环境影响和制定区域规划的重要依据。目前，已有一些研究分析了中国建设用地的空间格局和规模分布。研究发现建设用地空间格局朝更分散、更破碎和更复杂的方向发展，而规模分布则朝着更加均衡的趋势发展。但是，这些研究大多基于30米及以上空间分辨率的数据展开，分析也大多仅从某一尺度或依赖于某一指标。基于更精细分辨率数据的多尺度和多指标的建设用地空间结构研究还很少。为此，本文采用“国家-经济区-城市群”多尺度的研究思路，结合多种景观指数和规模分布指数，定量评估了中国2012年建设用地的空间格局和规模分布特征，以期为推动区域建设用地合理的发展提供科学参考依据。 本研究的主要工作包括两部分。 第一，基于多尺度和多指标的思路，定量评估了中国2012年的建设用地的空间格局。首先，基于全球城市足迹数据获取了中国2012年的建设用地信息。其次，依次在国家、经济区和城市群三个尺度上，结合建设用地面积（CA）、建设用地占比（PLAND）、建设用地斑块数量（NP）、建设用地斑块密度（PD）、建设用地景观形状指数（LSI）和建设用地平均最近邻距离（ENN_MN）六个景观指数来剖析2012年中国建设用地的空间组成和空间配置。最后，探讨包括总人口、城市人口、城镇化率、国内生产总值、第二产业生产总值、第三产业生产总值和固定资产总值在内的7个社会经济指标及包括高程、坡度、距一般公路的距离、距河流的距离、距铁路的距离、距地级市中心的距离、距县级市中心的距离、多年平均降水和多年平均气温在内的9个地理区位要素对空间格局形成的影响。 第二，基于多尺度和对比研究的思路，揭示了中国2012年的建设用地规模分布特征。首先，分别在国家、经济区和城市群三个尺度上，基于首位度、帕累托系数和基尼系数的计算来量化中国2012年建设用地规模分布特征。在此基础上，分析美国城市群2012年的建设用地规模分布，并将中美城市群的建设用地规模分布和建设用地利用效率进行了对比，剖析产生差异的原因。 主要的结果包括以下四点。 第一，中国2012年建设用地总面积达到1.7×105 km2，约占中国土地总面积的1.8%。少数经济区和城市群集中着大部分的建设用地。2012年，北部沿海经济区、黄河中游经济区和东部沿海经济区的建设用地总面积为9.4×104 km2，共占中国建设用地总面积的一半以上。同时，中国14个城市群的建设用地面积之和高达9.7×104 km2，约占中国建设用地总面积的60%。此外，建设用地破碎度在城市群尺度上最高。2012年，相比国家尺度建设用地的斑块密度0.7个/km2，城市群尺度的均值为2.5个/km2，后者是前者的3.5倍。 第二，社会经济发展和地理区位要素是影响建设用地空间格局的重要因素。通过相关分析得出城市人口、国内生产总值和固定资产投资与建设用地空间格局呈显著正相关关系（P<0.05），相关系数范围在0.55到0.94之间。Logistic回归分析表明距市中心的距离和距铁路的距离的增加会减少建设用地出现的概率，其让步比分别为5.8×10-9和0.2。未来，针对建设用地空间格局破碎的现象，应推行建设用地的紧凑发展，提高土地的利用效率。 第三，中国2012年城市群尺度上的建设用地分布比国家尺度的分布更为均衡。城市群尺度上建设用地规模分布的帕累托系数和基尼系数的均值为1.16和0.40，分别是国家尺度均值的2.0倍和0.7倍。相比于美国城市群，中国城市群的建设用地规模也更均衡。中国城市群2012年的2城市首位度和基尼系数均值为1.96和0.40，比美国低12.5%和43.7%。同时，中国城市群的城市规模帕累托系数均值为1.16，比美国的均值高56.9%。中国的城市规划政策是造成中国城市群建设用地分布均衡的重要原因之一。自1990年之后中国政府开展了一系列措施限制大城市规模，鼓励中小城市发展，造成中国城市群的城市规模分布总体呈现均衡化的趋势。 第四，中国城市群在建设用地的经济效率上也远低于美国城市群。中国2012年的单位建设用地的经济产值仅为美国城市群均值的25%。而且，中国城市群建设用地的集聚效益也低于美国。在相似的建设用地规模下，京津冀城市群的经济产值仅为Midwest城市群产值的27.8%。因此，未来中国需要借鉴美国城市群的发展有益经验，进一步提高城市群大城市的辐射和带动作用。

Accurately quantifying the spatial characteristics of the built-up areas in China is an important basis for assessing the ecological and environmental impacts of the built-up areas and formulating regional planning. At present, some studies have analyzed the spatial patterns and size distributions of the built-up areas in China. It is found that the spatial patterns of built-up areas tended to be dispersed, fragmented and complex, while the size distribution of built-up areas tended to be evenly distributed. However, most of these studies were based on data with a spatial resolution of 30 meters or below, and most of the analyses were based on a certain scale or a given index. Few studies on the spatial structure of the built-up areas at the national level were conducted with a finer spatial resolution data using multiple scales and multiple indices. Therefore, this thesis quantitatively evaluates the spatial patterns and size distribution of the built-up areas in China in 2012 on three scales, i.e., national, economic zone, and urban agglomeration scales, combining with various landscape metrics and size distribution indices, in order to provide scientific reference for promoting a rational development of the built-up areas. The main work of this study includes two parts. First, based on the multi-scale and multi-index framework, the spatial patterns of the built-up areas in China in 2012 were quantified. The built-up areas of China in 2012 were extracted based on the Global Urban Footprint data. Then, the spatial composition and configuration of the built-up areas were analyzed in China in 2012 on three scales, i.e., national, economic zone and urban agglomeration scales, by combining six landscape indices, which are the total area of the built-up area (CA), percentage of the built-up area of the landscape (PLAND), number of patches (NP), patch density (PD), landscape shape index (LSI) and mean Euclidean nearest-neighbor distance (ENN_MN). Finally, the influences on the spatial patterns of the built-up areas of the seven social-economic drivers, including total population, urban population at the end of the year, urbanization ratio, GDP, GDP of the secondary industry, GDP of the tertiary industry and investment of fixed assets, and nine topographic factors, including elevation, slope, distance to general highway, distance to rivers, distance to railway, distance to city center , distance to county center, annual average precipitation, and annual average temperature, were discussed. Second, based on the framework of multi-scale and comparative study, this thesis revealed the size distribution of built-up areas in China in 2012. First, the size distribution of the built-up areas in China in 2012 was measured based on the Law of the primate city, Pareto coefficient and Gini coefficient on three scales, i.e., national, economic zone and urban agglomeration scales. On this basis, the size distributions of the built-up areas in the United States at the national and urban agglomeration scales in 2012 were analyzed. At last, the size distribution and economic efficiency of the built-up land between China and the USA was compared at the urban agglomerations scale. The main findings can be summarized as follows. First, the results showed that the built-up areas were 1.7×105 km2 in 2012, accounting for 1.8% of the total land area in China. China’s Built-up areas were concentrated in a few economic zones and urban agglomerations. In 2012, more than half of the built-up areas in China were concentrated in the Northern Coastal, the Middle Reaches of the Yellow River and the Eastern Coastal Economic zones, which had a total areas of built-up land of 9.4×104 km2. Meanwhile, the total built-up areas of the 14 urban agglomerations in China were 9.7×104 km2, accounting for 60% of the total built-up areas in China. In addition, the built-up land at the urban agglomeration scale had the highest degree of fragmentation. In 2012, the mean patch density at the national scale was 0.7 per km2, while the averaged value at the urban agglomeration scale was 2.5 per km2; the latter was 3.5 times more than the former. Second, social-economic and topographic factors affected the spatial patterns of the built-up areas in China. Correlation analysis showed that urban population, gross domestic product and fixed asset investment were significantly positive correlated with landscape indices of the built-up areas in China (P<0.05), and the correlation coefficients were between 0.55 and 0.94. Logistic regression showed that with the increase in the distance to city center and the distance to the railway, the built-up areas would likely to disappear, and the concession ratio were 5.8×10-9 and 0.2, respectively. In the future, because of the fragmentation of the built-up areas, place-based measures should be taken to encourage the compact development of the built-up areas in China. Third, the size distribution of the built-up areas at the urban agglomeration scale was more even than the national average in China in 2012. The average values of the Pareto coefficient and the Gini coefficient of the built-up areas at the urban agglomerations in China were 1.16 and 0.40, respectively, which were 2.0 times and 0.7 times of those at the national scale. Compared to the results among urban agglomerations in America, the size distribution of the built-up areas in China’s urban agglomerations was more even. The average values of the primacy ratio and the Gini coefficient in China in 2012 were 1.96 and 0.40, respectively, which were 12.5% and 43.7% lower than those in the USA. In addition, the average Pareto coefficient of urban agglomerations in China was 1.16, which was 56.9% higher than that in the USA. Urban planning policy was one of the important reasons for the even distribution of the built-up areas in China among urban agglomerations. Since 1990, government has released a series of policies to constrain the size of large cities and encourage the development of small and medium-sized cities. As a result, the sizes of the built-up areas among urban agglomerations in China was evenly distribution. Fourth, the economic efficiency of the built-up areas among urban agglomerations in China was much lower than that in the United States. The per unit economic output of the built-up areas in China in 2012 was only 25% of the average value of the American urban agglomerations. Moreover, the agglomeration effect of the built-up areas among urban agglomerations in China was also lower than that of the American urban agglomerations. Under a similar amount of the built-up areas, the economic output in the Beijing-Tianjin-Hebei urban agglomeration was only 27.8% of that in the Midwest urban agglomeration. Therefore, China needs to learn the development experiences of the built-up areas among urban agglomerations in the United States in the future, and further improve the radiation and driving roles of the large cities in urban agglomerations.