Spatial Data Science

Spatial Data Science is the study of data that has geographical or spatial components. It involves analyzing and interpreting information related to locations, such as maps, satellite imagery, and sensor data. This field combines traditional data science techniques with geographic considerations, enabling insights into patterns and trends across different areas. For example, it helps cities analyze traffic patterns, plan urban development, and respond to environmental changes. By understanding the relationship between data and place, Spatial Data Science supports decision-making in various sectors, including urban planning, public health, and environmental management.