Recent advancements in deep learning have revolutionised the processing and analysis of geospatial data, fuelling a new era of mapping and landscape analysis. By leveraging state‐of‐the‐art neural ...

I have devoted a significant portion of my career to applying geospatial technology to solve challenges related to climate change – an issue that rises in importance each year for utilities that face ...

Ordnance Survey’s CTO, Manish Jethwa, gives his predictions for 2026 and his views on turning location data into actionable ...

Every piece of land carries a story of development, transformation, and human impact. From expanding urban centers to shifting agricultural zones, land use plays a crucial role in shaping both local ...

The minor in Geospatial Analysis provides students with a hands-on and theoretical understanding of the uses and applications of geospatial analysis. Geospatial analysis is the process of gathering, ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Journal of Transport and Land Use, Vol. 17, No. 1 (2024), pp. 143-161 (19 pages) Human mobility datasets, such as traffic flow data, reveal the connections between urban spaces. A novel framework is ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.