Don Murray is cofounder of Safe Software and has spent his career helping organizations bring life to data to make better decisions. How many times a day do you think about the word "where"? It likely ...

Data is often referred to as the new oil of the digital economy, representing a highly valuable and untapped asset. To fully realize the potential of spatial data, various spatial data marketplace ...

Spatial statistics is a rapidly evolving discipline that blends rigorous statistical methodologies with geospatial data analysis to uncover and interpret spatial patterns and dependencies. This field ...

Don Murray is cofounder of Safe Software and has spent his career helping organizations bring life to data to make better decisions. The world we live in is spatial. Think about how many times you use ...

Image analysis and computer vision / Donald Geman and Basilis Gidas -- Oceanographic and atmospheric applications of spatial statistics and digital image analysis / James J. Simpson -- Spatial ...

Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit NAP.edu/10766 to get more information about this ...

Location data is critical to nearly all state and local government work — whether it’s responding to a public safety call, supporting community planning and development, or maintaining critical ...

Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit NAP.edu/10766 to get more information about this ...

Geospatial engineering combines principles of engineering, geography, and surveying to collect, analyze, and manage spatial data. Geospatial engineering involves surveying. Over time, the field of ...

The Spatial Analysis Lab (the SAL) is a mapping lab dedicated to thoughtful and creative spatial data collection, analysis, and visualization. We strive to promote spatial literacy and spatial justice ...

Foundation models (FMs), which are deep learning models pretrained on large-scale data and applied to diverse downstream ...