Affiliations: [a]
School of Geographic and Environmental Science, Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, China
| [b]
School of Geographic and Environmental Science, Tianjin Normal University, China
Correspondence:
[*]
Corresponding author. Jifa Guo, School of Geographic and Environmental Science, Tianjin Normal University, Binshui West Road, Xiqing District, Tianjin, China. Tel.: +86 02223766313/15900243684; E-mails: [email protected] and [email protected].
Abstract: The division of the internal structure and external space of geographical entities is the premise of the analysis of topological relations and directional relations. Currently, most division methods are crisp, which does not conform to human cognitive habits. Occasionally, users want to integrate their meaning by vague natural language when they understand spatial scenarios; however, natural language suffers from uncertainty due to the effects of individual characteristics and the context of environmental factors. To handle uncertainties in spatial conceptions of regional features, the semantic spatial partitioning model for regions based on computing with words is proposed. The structure of a region is divided into several parts using fuzzy logic according to people’s cognitive habits, and then, a detailed direction model of regions is proposed. The proposed method is applied to understand a remote sensing dataset, and the results show that the proposed method can enrich the understanding of images while conforming to human cognitive habits.
