Topic
Artificial intelligence, machine learning, big data and cloud platforms applied to geospatial problems.
A weighted participation index and incremental algorithm, IM-DFS, detect spatial patterns that intensify over time in changing databases, tested on Beijing and Shanghai data.
Source: Data Science and Engineering (Springer)
NASA and USGS will benchmark EarthDaily Constellation imagery against Landsat standards, testing whether commercial data can extend the 50-year record.
Source: EarthDaily
NASA and USGS will test EarthDaily Constellation data against Landsat standards, exploring AI-ready products and hybrid government-commercial land imaging.
Source: EarthDaily
MAPL-EMIT, trained on 3.6 million simulated plumes, finds about 1.5 times as many plausible methane plumes as analysts in NASA EMIT data, with open outputs.
Source: Google Research / NASA JPL (Batchu et al., PNAS)
Four hands-on workshops on 24 November in Melbourne cover geospatial AI, data automation, cloud-native Earth observation and open-source cloud GIS.
Source: Spatial Source
The EU's MESEO project combines on-board AI and ground processing under one coordination platform, tested on methane detection and crop classification.
Source: CORDIS
NOAA and Cowboy Space will test AI processing of VIIRS data on the Reason-2 satellite, due in 2027, to speed delivery of weather data to forecasters.
Source: NOAA NESDIS
ZenaTech is developing ZenaAI to automate LiDAR point cloud classification and CAD linework, aiming to cut survey post-processing by up to 80%.
Source: ZenaTech
Merlin.01 and three NewSat satellites reached orbit on 1 October, starting a constellation meant to remap Earth daily at 1 m with onboard AI change detection.
Source: Satellogic
NOAA and Cowboy Space will test whether processing VIIRS data in orbit on the Reason-2 satellite, due in 2027, can speed up delivery to forecasters.
Source: NOAA NESDIS