| About Me | https://about.me/davidoesch |
| About Me | https://about.me/davidoesch |
The #OGC ran an #AI-#DGGS pilot on disaster management and derived five pillars for geospatial AI readiness from it: tool-ability, machine-readable metadata, guardrails, reproducibility, and trust & security. Among the interesting follow-up work items: enabling non-DGGS clients, treating the time dimension as a first-class topic alongside space, and cataloging which spatial analysis functions should be available in a standardized #DGGS-based manner.
In an upcoming colloquium, #swisstopo offers a look at an operational #EarthObservation pipeline turning #Sentinel-2 data into near #realtime insight for #drought #monitoring in Switzerland. #eo #remotesensing
Ed Parsons’ latest article cautions that while geospatial #embeddings promise analytical power, they risk transparency and interpretability long valued in #remotesensing. The article underscores the need to balance innovation with auditability and compliance in AI-driven #EarthObservation. #EO
David O’Sullivan’s latest post in his “GIS, a Transformational Approach” series explores how geospatial data transitions between continuous #fields and discrete forms like #points, #lines, and #areas. Using #geomorphometry concepts such as surface-specific points, geomorphons, and surface networks as an example, the data transformations are illustrated using #R-based workflows.