A new interactive map predicts the density and extent of arbuscular mycorrhizal fungal networks, which exist in symbiosis with land plants. The estimate is based on soil samples and data from previous studies, fed through machine learning models. The extent of the networks comes to something like 110 quadrillion kilometres of hyphae (equivalent to roughly half the distance to most globular clusters). More here; via Wired ( News+).
Save some room on the AI bandwagon for ArcGIS. This seems to be the central message of GeoAI: Artificial Intelligence in GIS, a slim (only 120-page) volume of articles and posts that previously appeared, for the most part, in Esri blogs and publications. They highlight examples and “real-life stories” of how Esri’s machine- and deep-learning tools have been successfully applied in the public, private and non-profit sectors. At a moment when “AI” is invariably a synecdoche for the awfulness that is generative AI, which I will not litigate here, it can be a challenge to remember that machine and deep learning tools, which have been included in ArcGIS since 2008, have all kinds of applications and benefits. (See Esri’s pretrained deep learning models for examples like feature detection, land-cover classification, and object tracking; see also their GeoAI landing page.) Calling these tools “GeoAI” strikes me as a way to package them to appeal to decision makers who are speedrunning their AI rollout, for better or worse. It’s those decision makers that this book is targeted to. Esri has something to sell them: this is the pitch.
I received an electronic review copy from the publisher.
GeoAI: Artificial Intelligence in GIS
ed. by Ismael Chivite, Nicholas Giner and Matt Artz
Esri, 2 Sep 2025, $40
Amazon (Canada, UK), Bookshop
Google Maps imagery updates include improved satellite imagery thanks to an AI model that removes clouds, shadows and haze, plus “one of the biggest updates to Street View yet, with new imagery in almost 80 countries—some of which will have Street View imagery for the very first time.” The web version of Google Earth will be updated with access to more historical imagery and better project and file organization, plus a new abstract basemap layer. [PetaPixel]
Meanwhile, The Verge reports that Google Maps is cracking down on business pages that violate its policy against fake ratings and reviews.
Mapping Fictional Worlds is a project to create maps and virtual spaces from literary texts. This seems to be a machine learning project: using natural language processing to build a world around a text that didn’t necessarily come with a map. One component, highlighted by the Guardian, is LitCraft: creating literary worlds using Minecraft. Such as Treasure Island. More at the project’s Chronotopic Cartographies blog. [David Garcia]
