Unmanned aerial vehicles (UAVs), commonly known as drones, have revolutionized spatial data collection in recent years by offering flexible, low-cost platforms for aerial imagery and remote sensing.

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

Our thoughts are specified by our knowledge and plans, yet our cognition can also be fast and flexible in handling new information.

In the race to deliver faster, smarter, and more resilient networks, CSP and telco leaders are finding a powerful ally in ...

Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep ...

The OPC Foundation said its new OPC UA companion specification for asset identification and location, based on the open locating standard omlox, has been developed to establish the foundation for a ...

Abstract: This paper addresses the two-view geometric model fitting problem on the multi-structural data with severe outliers for providing reliable and consistent fitting results. The key idea is to ...

Few things generate as much data as simply observing Earth from above. But Ryan Abernathey and Joe Hamman very quickly realized that all that data still wasn’t enough for their startup to thrive.

This tip was performed on an iPhone 15 Pro running iOS 26. Find out how to update to the latest version of iOS. So, what are spatial photos on the iPhone? With iOS 26, spatial photos give your ...

The Earth is awash in data about itself. Every day, satellites capture around 100 terabytes of imagery. But making sense of it isn’t always easy. Seemingly simple questions can be fiendishly complex ...

The landscape of foundation models is extending to consider use-cases that do not involve text but images as input/output data. A notable example is Prithvi, a geospatial foundation model developed ...