为协调生活、生产和生态空间的用地矛盾,解决数据驱动法在识别城市"三生空间"方面存在的判别不准确和数据覆盖范围不够等问题,提出了一种能够精准识别"三生空间"功能的方法.基于数据驱动法,结合POI(point of interest)、AOI(ar-ea of interest)和遥感等多源异构数据的多特征信息,分析在功能评价体系和分类模型中将不同数据源作为特征因子时的识别精度与尺度效应.以高原城市昆明市五华区建成范围为实验对象,研究结果表明:基于多源地理数据的识别准确率达到92％和94％.多源数据的多特征信息能够明显提升城市功能区的识别精度,为城市功能区精准识别提供了新的方法,能够在更小的尺度上为国土空间规划提供数据与方法支撑.
Function Identification of Urban"Living Production Ecology Space"Based on Multi-source Heterogeneous Data
In order to coordinate the land use contradiction between living,production and ecological space,and solve the problems such as inaccurate discrimination and insufficient data coverage in the identification of urban"living production ecology space"by data-driven method,a method that can accurately identify the function of"living production ecology space"was provided.Based on the da-ta-driven method,combining the multi-feature information of multi-source heterogeneous data such as POI(point of interest),AOI(are-a of interest)and remote sensing,the recognition accuracy and scale effect of different data sources were analyzed when they were used as feature factors in functional evaluation system and classification model.Taking Wuhua District of Kunming as the experimental ob-ject,the research results show that the recognition accuracy based on multi-source geographic data reaches 92％and 94％.The multi-feature information of multi-source data can significantly improve the identification accuracy of urban functional areas,provide a new method for accurate identification of urban functional areas,and provide data and method support for territorial spatial planning on a smaller scale.
land usethree-life space function recognitionmulti-source geographic big datadata-driven methodevaluation sys-temmachine learning
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