Spatial Stack with Matt Forrest

In this episode of the Spatial Stack, Matt sits down with Dr. Chris Tucker, chairman of the American Geographical Society, in the year the AGS turns 175.Chris makes the case that spatial thinking is foundational literacy, on the level of language or math, and that the 4.5 million people who have taken AP Human Geography are already practicing it every day in jobs that never mention geography. He shares how a single question from a CIA veteran, about why we cannot draw a bounding box on a map and pull in everything known about that place at that moment, set the direction for almost thirty years of his career.The conversation also covers what has changed about getting into this work. The advanced degree, the expensive workstation, and the expensive software used to be the price of entry. Free tools and YouTube replaced all three.Chris then takes on a challenge: name five careers that do not sound geographic but where spatial skills give you a real edge. Surveying, the CAD and built environment world, aviation, marine navigation, and conservation all make the list, along with a case for why geography works as both a horizontal and a vertical.We also get into the AGS itself, from the Fliers' and Explorers' Globe signed by Amelia Earhart, Sir Edmund Hillary, and Neil Armstrong, to the geographers at 156th and Broadway who worked on the inquiry behind the Treaty of Versailles.If you have ever struggled to explain what you actually do for a living, this conversation gives you better language for it.Connect with Chris Tucker and the AGS:LinkedIn: https://www.linkedin.com/in/christopher-tucker-5595689/American Geographical Society: https://www.americangeo.orgEmail: [email protected] MOREAGS 175th anniversary campaign: https://www.americangeo.orgThe Fliers' and Explorers' Globe: https://www.americangeo.org/globeGeography 2050 (Africa: Shaping the Future): https://www.geography2050.orgTeen Maptivist: https://teenmaptivists.orgCHAPTERS:00:00:00 – Welcome and Chris Tucker's Background00:01:21 – 4.5 Million AP Human Geography Students00:04:48 – Spatial Thinking as Foundational Literacy00:09:08 – 175 Years of the American Geographical Society00:12:03 – The Fliers' and Explorers' Globe00:15:05 – The AGS and the Treaty of Versailles00:18:02 – The 175th Anniversary Campaign00:21:49 – How Matt and Chris Found Geography00:24:59 – Free Tools and Getting Back Into the Work00:27:07 – Advocating for Geography in Schools00:30:55 – Geography as Horizontal and Vertical00:35:01 – Five Careers Where Spatial Gives You an Edge00:40:34 – Getting Involved with AGS and Geography 2050---📊 FREE: The Modern GIS Skill MapThe 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals.➡ Get the free training + PDF guide: https://forrest.nyc/go/training/📰 Daily modern GIS insights: https://forrest.nycCONNECT WITH ME📸 Instagram:  https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

What does it take to map something you have never seen?In this episode, Matt Forrest sits down with Justin Stewart, quantitative ecologist at SPUN, the Society for the Protection of Underground Networks, to unpack how his team built the first global map of arbuscular mycorrhizal fungi, the soil organisms living in symbiosis with most plants on Earth.Justin walks through the full pipeline, from robotic microscopy of threads two and a half microns wide up to a planetary prediction at one square kilometer resolution. The team assembled 16,000 soil samples from more than 300 studies across 11 languages, trained a random forest on 34 satellite-derived layers in Google Earth Engine, andsummed the result: roughly 110 quadrillion kilometers of fungal thread, about 300 megatons of carbon, six times the biomass of every human alive.The findings were not what anyone expected. The densest networks are under grasslands, not forests. Croplands run about 50 percent sparser. And 90 percent of the biodiversity hotspots for these fungi sit outside any protected area.In this episode, we cover:- Why mapping a symbiosis is harder than mapping an organism- Robotic imaging in the Amolf biophysics lab, and tracking half a million nodes at once- Building a global database from literature in 11 languages- Random forest niche modeling and uncertainty analysis in Google Earth Engine- The effective radius algorithm that turns network length into biomass- Why grasslands, flooded wetlands, and the Tibetan plateau light up on the map- Tilling, fertilizer, and how a 450 million year old symbiosis gets broken- Rights of nature, eDNA, and why predictive maps are not yet admissible evidenceLINKS:Justin StewartSPUN profile: https://www.spun.earth/team-members/justin-stewartLinkedIn: https://www.linkedin.com/in/justin-stewart-70512645/Google Scholar: https://scholar.google.com/citations?hl=en&user=1aqTJIUAAAAJSPUNWebsite: https://www.spun.earthUnderground Atlas: https://a-hidden-infrastructure.spun.earth/story/a-hidden-infrastructureLEARN MOREThe paper: Science, June 11, 2026. DOI 10.1126/science.adu4373Mycorrhizal Biodiversity Map: https://a-hidden-infrastructure.spun.earth/story/a-hidden-infrastructureCHAPTERS:00:00:00 – The largest living network on Earth00:02:15 – Welcome and intro00:03:38 – What the map shows: a partnership, not an organism00:05:48 – Robots, petri dishes, and carbon moving at 400 kilometers an hour00:07:47 – The question that started it: how much is out there?00:09:25 – 110 quadrillion kilometers and six times human biomass00:11:15 – What a quantitative ecologist actually does00:13:53 – Trade, lipids, and 30 percent of a plant's nitrogen00:16:31 – What people get wrong about soil00:18:27 – The pipeline: 34 satellite layers, random forest, Earth Engine00:21:02 – From length to weight: effective radius and the robot named Prince00:25:41 – Croplands and a broken 450 million year symbiosis00:31:40 – Rights of nature and getting predictions accepted as evidence00:37:10 – Where to find SPUN and Justin📊 FREE: The Modern GIS Skill MapThe 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals.➡ Get the free training + PDF guide: https://forrest.nyc/go/training/📰 Daily modern GIS insights: https://forrest.nycCONNECT WITH ME📸 Instagram: https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

What does it actually take for an AI to navigate you through the real world, without a screen and without a camera running the whole time?In this episode of the Spatial Stack, Matt Forrest sits down with Sean Gorman and Pramukta Rao, the co-founders of Zephr, to unpack how they ground large language models in location. Sean and Pramukta spent twenty years building startups together, from GeoIQ to Snap's visual positioning work, and at Zephr they walked away from the camera and went back to the sensors already in your phone.They get into why the blue dot on a map breaks down the moment you stop looking at a screen, why language models are bad at spatial reasoning like left, right, and across the street, and how they fix it by doing the geometry first and handing the model clean language. Instead of training ever-bigger foundation models, they push a small model and well-structured data down to the edge so the conversation stays fast.In this episode, we cover:- Why they left visual positioning and AR cameras behind after Snap- Cooperative positioning: getting survey-grade accuracy out of commodity phones- GNSS and the urban canyon problem (3 meters to 50 meters and back)- Beyond the blue dot: building a first-person, egocentric experience- Why LLMs struggle with geometry, and what context engineering solves- Small models at the edge vs giant foundation models- Overture Maps, GERS IDs, and conflating POIs with imagery to "agree on reality"- The grounding service: MCP, REST, and Opus or Gemma on device- Conversations about place as a new geospatial primitiveWhether you build with spatial data, work on AI navigation, or just want to see where location and LLMs are heading, this conversation is your field guide.Connect with Zephr:Website: https://zephr.xyzSean Gorman (LinkedIn): https://www.linkedin.com/in/sean-gorman-93a79Pramukta Rao (LinkedIn): https://www.linkedin.com/in/pramukta/Zephr (LinkedIn): https://www.linkedin.com/company/zephr-xyz00:00:00 – Intro and twenty years of startups together00:04:05 – Why they walked away from cameras and AR at Snap00:04:54 – Commodity sensors and cooperative positioning00:07:15 – GNSS 101 and the urban canyon problem00:10:56 – Beyond the blue dot: an egocentric experience00:13:37 – Why LLMs are bad at left, right, and across the street00:18:19 – Context engineering and the retrieval problem00:22:03 – Small models at the edge vs giant foundation models00:30:09 – Collective memory: OpenStreetMap, Mapillary, Overture00:32:08 – Conflating POIs with imagery to agree on reality00:35:36 – The grounding service: MCP, REST, Opus or Gemma on device00:38:37 – What's next: conversations as a new geospatial primitive00:42:22 – Where to find Zephr📊 FREE: The Modern GIS Skill MapThe 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals.➡ Get the free training + PDF guide: https://forrest.nyc/go/training/🚀 Join The Spatial Lab:Stop guessing at your career path. Get direct mentorship, advanced training, and a roadmap to these high-value roles inside The Spatial Lab.👉 https://forrest.nyc/spatial-lab/📰 Daily modern GIS insights: https://forrest.nycCONNECT WITH ME📸 Instagram:  https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

In this episode of the Spatial Stack, Matt sits down solo to work through a fight that broke out across Reddit and LinkedIn last week: is GIS dying, or is it just changing its name?It started with a GIS manager who argued the field is alive, pointing to a friend who landed a $200,000 job building autonomous systems, a role where GIS never appeared in the title or the description. The comments pushed back. If the keyword for our whole profession barely returns jobs anymore, is the field really growing?Matt's answer is that both sides are right. The work of spatial is expanding into data engineering, software, and product roles. The GIS title is contracting at the same time. It's one trend seen from two directions, the same way geology departments quietly became geoscience without the work ever changing.He makes the case that the title was never the skill. Spatial intuition is, and it's the thing that transfers into higher-paying roles that don't carry the GIS label. Then he closes with a challenge: describe who you are and what you do without using the words GIS, spatial, or geospatial.Whether you're job hunting, stuck in the technician trap, or an employer who wants this skill set but doesn't know what to call it, this conversation is about how we position the work going forward.---📊 FREE: The Modern GIS Skill MapThe 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals.➡ Get the free training + PDF guide: https://forrest.nyc/go/training/CHAPTERS:00:00:00 – The Reddit post that started it00:01:00 – Two views: the work is growing vs. the title is shrinking00:02:34 – Why "stay positive" doesn't pay the rent00:03:33 – Spatial is special: what actually transfers00:04:53 – The geology-to-geoscience analogy00:05:54 – The title of GIS was never the skill00:07:09 – The technician trap and where the salaries moved00:08:18 – Listener comments: spatial judgment, the map as interface00:10:32 – What to do now: SQL, Python, and cloud-native beyond the toolbox00:11:51 – Building a portfolio on LinkedIn00:13:22 – The Spatial Intuition Challenge00:15:32 – Put your face on it: make it a videoCONNECT WITH ME📸 Instagram:  https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

What does it actually take to make AI useful on location data?In this episode, Matt Forrest sits down with Ryan Urabe, co-founder and CTO of Dataplor, to unpack how AI, embeddings, and agents are changing the way we work with points of interest and places data.Ryan explains why general-purpose models already understand spatial concepts but still struggle to execute them, and why the real unlock is the harness around the model, not a geospatial-specific model. He walks through Dataplor's data-quality philosophy, the category problem (why "supermarket" and "grocery store" have zero string similarity but near-zero conceptual distance), and how embeddings let them measure conceptual distance across 10^9 places and even across languages.Whether you build with spatial data, lead a data team adopting AI, or you are trying to figure out what embeddings actually do, this conversation maps out what is working today and what is still forming.In this episode, we cover:- Why AI is an accelerant for data quality, not a replacement for it- Treating AI like a capable employee on their first day- Where general models fall short on spatial problems- DuckDB as the Swiss Army knife for orchestrating spatial data- The category problem and conceptual vs. semantic distance- How embeddings map 7-Eleven in Tokyo and Tennessee to the same concept- A vision for agentic AI built natively for geospatial- The "end of the scarcity of intelligence" framing for where this is all headingConnect with Ryan:LinkedIn: https://www.linkedin.com/in/rurabe/Website: https://www.dataplor.comEmail: [email protected] MOREDataplor's agentic SaaS product is launching this summer. To start your complimentary trial, contact: [email protected]📊 FREE: The Modern GIS Skill MapThe 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals.➡ Get the free training + PDF guide: https://forrest.nyc/go/training/00:00:00 – Cold open00:01:01 – Welcome and Ryan's background00:03:44 – Why AI still struggles with location00:05:13 – Bringing Dataplor's data into AI, product and team00:08:36 – How technical teams are adopting AI00:10:10 – Treating AI like a capable new employee00:12:20 – Where general models fall short on spatial00:16:44 – DuckDB and opinionated workflows00:18:14 – Data quality as the whole game00:20:58 – The category problem: supermarket vs. grocery store00:27:53 – Embeddings and conceptual space, with a 3D walkthrough00:38:22 – A vision for agentic AI in geospatial00:43:37 – The end of the scarcity of intelligence00:47:25 – Where to find Ryan and Dataplor📰 Daily modern GIS insights: https://forrest.nycCONNECT WITH ME📸 Instagram:  https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc