GIS and mapping

There is an urgent need to evaluate the negative effects and risks associated with coastal artificial structures around the world, especially as climate change makes sea-level rise more extreme.

This review examines flood risk delineation and assessment in Nigeria within a broader Global South perspective, synthesising evidence from peer-reviewed studies that employ remote sensing, GIS-based techniques, and multi-criteria decision analysis.

More than 750,000 New Zealanders live in locations exposed to flooding from one-in-100-year rainfall flooding events.

Korean and Pacific institutions entered into a four-year agreement to enhance earth observation data-driven decision-making capabilities to support coastal and marine spatial planning (CMSP).

This research introduces an automated method for mapping glacial lakes in Himachal Pradesh based on multi-source remote sensing data and a random forest (RF) classifier.

Machine learning is expanding scientists’ catalogs of quakes and refining maps of underground faults. It also promises to improve quake forecasts.

This study provides geographic information system (GIS) data and a multimodal dataset from a systematic infrastructure vulnerability assessment in the urban road networks of Turin and Naples, Italy.

This study contributes to the understanding of the complex interplay between climate change, urban infrastructure, and autonomous vehicle systems, as well as the necessity of using higher resolution data for this type of analysis.