目前自上而下的城市系统宏观模拟并不能解决城市这一复杂系统中出现的部分问题，城市系统微观模拟(如多主体系统MAS) 已经成为城市系统模拟的新思路，其主要是基于个体数据(如个人、家庭、公司或建筑物) 开展的。国际国内这方面的应用都受到个体样本稀缺的限制。微观模拟所需要的个体样本数据是原有的统计制度所不能适应的，尤其是在中国，个体样本在统计公报或年鉴中不公开，仅可通过典型调查来补充。本文旨在探索稀疏数据环境下构建城市系统微观模拟的个体样本数据的新方法。该方法基于已有的多源统计数据、典型调查数据以及个体的通用规则，反演出个体样本的属性信息和空间分布，进而可以以GIS图层的形式直接作为微观模拟的数据基础。通过本方法获取的样本，能够符合已有的统计资料，并遵照了样本的基本特征，可以作为现有数据条件下的微观模拟模型的数据输入。同时该方法的应用简单，统计意义上的准确度高，适合我国统计制度下的微观模拟模型的构建。
As the traditional top-bottom based macro-simulation models can not properly adapt to the present research of spatiotemporal dynamic urban system, the bottom-up micro-simulation models using individual data have gradually become a novel perspective for investigating urban systems recently. However, one of the factors restraining the wide application of micro-simulation models is the limited individual data due to the difficulties of data fetching and processing. Such a situation is especially serious in China, where individual dataset is not available from the official census and can only be obtained via various surveys in small scale conducted by separate units. This paper proposes a new solution to retrieve individual dataset from aggregate dataset, e.g. statistical data, for urban micro-simulation under the current sparse-data environment. Based on the existing multi-resource official statistical data, non-official surveys, as well as general relationships among individual attributes, our approach can disaggregate the individual attributions and location obeying the input aggregation observations data. This approach has proved to be significantly accurate at the statistical level, and can be conveniently adopted for urban micro-simulation under the present statistical institutions of China.
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