多元信息综合的市县国土空间规划空间功能识别方法

空间功能识别是确定国土空间规划空间开发保护格局的关键环节,理论和实践意义重大。基于土地利用和地表覆盖现状、精细化DEM、地形单元等基础地理信息,水、生态、环境、灾害等专题数据,社会统计数据等多元信息,利用空间分析、多元统计、计量模型、基于规则的分类模型等技术方法,从多元信息综合集成和自动分类识别的角度,研究构建了一套市县国土空间规划空间主导功能识别的关键技术与方法,并对榆林市域进行空间功能分区。研究表明：本文方法有效将地理实体单元、功能评价指标综合于统一的地域单元,保证了空间功能分类识别的准确性;通过自动分类算法建模,实现空间功能识别的自动化,提高了国土空间规划的客观性和工作效率。

Spatial function identification of city- and county-level land spatial planning based on information integration

Spatial function identification plays a major part in land spatial planning, which is of important theoretical and practical significance. The data sources in this article come from multivariate information, such as land use and cover status data, refined DEM data, terrain and landform data, and other types of basic geographic information; water, ecology, environment, disaster and other types of special survey research data; population, economy, transportation and other types social statistics data. From the perspective of multivariate information integration and automatic classification, we used GIS spatial analysis, multivariate statistical analysis, measurement model, rule-based classification model and other technical methods, to build a set of key technologies and methods for realizing spatial function identification for land spatial planning in city and county scales. Finally, we conducted an empirical study with the above research methods in Yulin city. The empirical study shows that the method in this paper effectively integrates geographic entity units, functional evaluation indicators and other element characteristics into unified regional units, which indirectly guarantees the accuracy of spatial function classification and identification. In addition, through classification algorithm, we can realize automated spatial function identification, which improves the objectivity and work efficiency for land spatial planning.