Advanced Technologies in Spatial Data Collection and Analysis (Volume II)

Dear Colleagues,

In recent years, the fields of data science and geo-analytics have undergone significant changes, primarily due to the advancements of machine learning, artificial intelligence, natural language processing and the availability of massive pre-trained AI models, such as multimodal foundation models for joint reasoning from vision (audio, images, and videos) and language. Such models, tools, and techniques can help to solve tasks in different domains, and can be leveraged to advance GeoAI in the near future.

Additionally, the rapid development of new hardware, software, and cloud computing technologies have revolutionized the collection and analysis of geographic data to provide state-of-the-art solutions to current issues of grave importance. Examples of such technologies include the integration of global satellite navigation systems (GNSS) into mobile devices, mobile apps for the collection and sharing of volunteered geographic information, geospatial augmented reality, the Internet of Things (IoT), digital twins, immersive technologies, connected vehicles, real-time traffic monitoring, ridesharing systems, and artificial intelligence and deep learning for applications such as disaster monitoring or event prediction.

This Special Issue calls for research contributions presenting novel analysis techniques, applications, sensors, devices, and technologies for the collection of spatial or spatio-temporal data, and effective processing of such data (including big data) through the development or use of new algorithms, software packages, high-performance computing infrastructures or large-scale training models. This Special Issue also welcomes discussion and reviews of previously underexplored open spatial data sets that are of relevance to the geo-science community. We invite contributions from a wide array of academic disciplines including geodesy, geo-information science, computer science, cartography, geography, transportation, environmental science, and health.

Prof. Dr. Hartwig H. Hochmair
Dr. Gerhard Navratil
Prof. Dr. Haosheng Huang
Guest Editors

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