Research news on geospatial analysis

Geospatial analysis is a collection of quantitative and computational methods for examining data that are explicitly referenced in geographic space, typically using coordinate-based representations such as vector (points, lines, polygons) and raster (grids) models. It encompasses spatial statistics, spatial autocorrelation assessment, geostatistics (e.g., kriging), network and proximity analysis, spatial interpolation, and spatial-temporal modeling, often implemented within Geographic Information Systems (GIS) and spatial databases. These methods exploit spatial relationships—distance, adjacency, containment, and topology—to detect patterns, model processes, and support inference and prediction across domains such as environmental science, epidemiology, transportation, and urban planning.

The importance of data choice in effective flood insurance

In a world covered with sensors and satellites, access to high-quality data that can help solve problems and improve systems is more widespread than ever. But with such a wealth of information at our disposal, how do we know ...

Mapping an entire subcontinent for sustainable development

Using the first complete dataset of more than 415 million buildings across 50 countries in sub‐Saharan Africa, researchers at the University of Chicago created an unprecedented approach to urban development, down to each ...

Tracking macroplastics leaching into rivers from space

Scientists have developed a new method to identify and map plastic waste in urban areas using satellite imagery, offering new hope for tracking pollution and improving waste management in cities worldwide.

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