Topic
Artificial intelligence, machine learning, big data and cloud platforms applied to geospatial problems.
NASA has announced a delay for the A.14 Atmosphere Research Program proposal due date to December 2, 2026. The amendment also clarifies guidelines regarding the use of Generative AI in proposals and updates the related FAQ.
Source: NASA Science
Australia's Disaster Assistance Response Team (DART) deployed to Nepal, utilizing drones equipped with AI and 3D mapping capabilities to assess flood damage and provide crucial aerial intelligence for relief efforts in areas too dangerous for ground crews.
Source: Spatial Source
The World Geospatial Industry Council (WGIC) has released a new report, 'Data to Decisions,' addressing the critical need to restore trust in decision-grade geospatial data amidst the rise of AI-generated inferences. The report outlines four foundational elements—provenance, governance, metadata…
Source: Spatial Source
CSDILA researchers have developed an AI process that integrates vision models, language agents, and learned surrogates to automate and accelerate complex geospatial analysis. This innovative approach aims to transform real-world spatial assignments, from asset identification to flood simulations…
Source: Spatial Source
scFormer is a new AI-powered graph tool that identifies rare cell states in single-cell RNA sequencing and spatial transcriptomic data. It uses a novel cell-gene graph approach to overcome limitations of traditional methods, improving accuracy and robustness in biological discovery.
Source: Bioengineer.org
A new review highlights how deep learning can integrate social media posts with satellite and drone imagery to fundamentally transform disaster response. This fusion aims to provide a more comprehensive, real-time understanding of evolving disaster scenarios, enhancing rescue efforts.
Source: Bioengineer.org
Lunit and 10x Genomics are integrating Lunit's AI pathology platform, Lunit SCOPE IO, with 10x Genomics' spatial molecular data for advanced cancer biomarker discovery. This collaboration aims to link tumor morphology with underlying biology to identify treatment response and resistance biomarkers.
Source: Koreabiomed
Adelaide-based researchers have developed STELLA, an AI-powered navigation system that uses lunar craters for precise positioning during long-duration mapping missions. This technology achieves metre-level accuracy, crucial for future lunar exploration and resource identification.
Source: Spatial Source
Loft Orbital, Marlan Space, and partners are investing $1 billion to develop a 50-satellite AI constellation. This Earth Observation network will serve France, Europe, and the UAE, providing in-orbit data processing for applications like disaster response and maritime awareness.
Source: Via Satellite
The USDA is expanding its use of satellite data and artificial intelligence, partnering with NASA to enhance crop estimates. This initiative aims to improve the accuracy and transparency of agricultural statistics, crucial for global grain and oilseed markets, by leveraging advanced monitoring and…
Source: Ukragroconsult