Geospatial knowledge graphs have emerged as a novel paradigm for representing and reasoning over geospatial information. In this framework, entities such as places, people, events, and observations are depicted as nodes, while their relationships are represented as edges. This graph-based data format lays the foundation for creating a "FAIR" (Findable, Accessible, Interoperable, and Reusable) environment, facilitating the management and analysis of geographic information. This entry first introduces key concepts in knowledge graphs along with their associated standardization and tools. It then delves into the application of knowledge graphs in geography and environmental sciences, emphasizing their role in bridging symbolic and subsymbolic GeoAI to address cross-disciplinary geospatial challenges. At the end, new research directions related to geospatial knowledge graphs are outlined.

翻译：地理空间知识图谱已成为表示和推理地理空间信息的新范式。在此框架中，地点、人物、事件和观测等实体被建模为节点，而其关系则表示为边。这种基于图的数据格式为构建“FAIR”（可查找、可访问、可互操作、可复用）环境奠定了基础，从而促进了地理信息的管理与分析。本文首先介绍了知识图谱的核心概念及其相关标准化与工具，随后深入探讨了知识图谱在地理与环境科学中的应用，重点阐述了其在连接符号与亚符号GeoAI、应对跨学科地理空间挑战中的作用。最后，本文展望了地理空间知识图谱的新研究方向。