多模态地理大数据时空分析旨在融合地理大数据的多模态信息发现有价值的时空分布规律,
异常表现, 关联模式与变化趋势, 是全空间信息系统的核心研究内容, 并有望成为推进地理学人地 …

The presence of global spatial autocorrelation usually leads to the spurious identification of
spatial hotspots and hinders the identification of local hotspots. Despite the use of statistical …

Identifying clusters from individual origin–destination (OD) flows is vital for investigating
spatial interactions and flow mapping. However, detecting arbitrarily-shaped and non …

As the map scale decreases, conflicts can appear among polygonal features such as water
areas and buildings. Aggregation is usually employed to clearly represent polygonal …

Spatial clustering is a widely used data mining method for discovery of spatial aggregation
pattern. However, existing methods often neglect scale dependence, impeding the full …

空间聚类是探索性空间数据分析的有力手段, 不仅可以直接用于发现地理现象的分布格局与分布
特征, 亦可以为其他空间数据分析任务提供重要的预处理步骤. 空间聚类有望成为大数据认知的 …

Identifying anomalies from geochemical data by modeling of the background and statistical
evaluation of anomalies is a major concern in geochemical exploration. This study …

Recognition of building groups is a critical step in building generalization. To find building
groups, various approaches have been developed based on the principles of grouping (or …

Spatial clustering analysis is an important issue that has been widely studied to extract the
meaningful subgroups of geo-referenced data. Although many approaches have been …

Urban black holes and volcanoes are typical traffic anomalies that are useful for optimizing
urban planning and maintaining public safety. It is still challenging to detect arbitrarily …