Geospatial Query Processing for Big Spatial Data: Spatial Analytics (Published)
The increasing availability of large-scale geospatial data has created opportunities and challenges in the field of spatial analytics. This abstract provides an overview of the key concepts and challenges in geospatial query processing for big spatial data. Geospatial data, which includes location-based information from various sources such as GPS devices, social media, remote sensing, and urban sensors, has grown at an unprecedented rate. This wealth of geospatial information presents opportunities to gain valuable insights into various domains, including urban planning, environmental monitoring, logistics, and business intelligence. However, the sheer volume and complexity of big spatial data demand advanced techniques for efficient and effective query processing. This abstract highlights the following key points: Spatial Data Challenges, Query Processing Techniques, Spatial Analytics, Scalability, Privacy and Security. This abstract provides a high-level overview of the challenges and opportunities in geospatial query processing for big spatial data. The full paper explores these topics in greater detail and offers insights into the state-of-the-art techniques and emerging trends in the field of spatial analytics.
Keywords: Big Spatial Data, Geospatial Data, Indexing, Query Processing, Spatial, Spatial Analytics, scalability