Algorithms and Application for Spatiotemporal Data Processing

Dear Colleagues,

With the continuous advancement of instrument science and sensor technology, spatiotemporal data are demonstrating more diverse types, more complex acquisition environments, and a dramatic increase in data volume. For the field of surveying and mapping, which emphasizes precision and reliability, the selection and improvement of algorithms have become particularly critical. The current challenges include, but are not limited to, the following: (1) data from different sources exhibit significant differences in format, accuracy, spatiotemporal resolution, physical meaning, and mathematical relationships, which poses the challenge of effectively fusing multi-source heterogeneous spatiotemporal data; (2) faced with massive data, traditional algorithms struggle to meet real-time demands, thereby highlighting the need for improvements in processing speed; (3) under extreme or harsh conditions, the data obtained is limited in quantity and uneven in quality, making the challenge of reliably extracting and interpreting necessary information particularly daunting; (4) traditional algorithms often require a significant manual intervention to process complex data, and how to enhance the intelligence level of data processing should be explored.

We invite high-quality, original research and review articles that delve into the latest advancements in spatiotemporal algorithms, their practical applications, and enhancements to current methodologies. We are particularly eager to receive contributions that showcase the implementation of these techniques in addressing complex systems across diverse fields.

Prof. Dr. Di Zhang
Guest Editor

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