Obsessed with geospatial foundation models, broadcasting in geospatial and compounding via publicly listed geospatial equities.
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October 13, 202647 min
GISMap.online
My guest is Silas Toms , GIS supervisor at PG&E, which covers the largest land area of any utility in California. Silas has 20 years in geospatial, including time at Zillow, and runs GeoMeetup in SF . Yes, he was the one wearing that tracksuit. The next one is tomorrow. We cover why utilities should separate their systems of record, engagement and monitoring, and how AI changes who builds geospatial tools. We also look at GIS Map Online , Silas's open-source, browser-based replacement for Google Earth. Stick around to the end for a 10 minute demo.
October 6, 202648 min
How to Make an ETF with Kevin T Carter, Founder of EMQQ Global and EMXETF
Kevin T. Carter is founder of a couple of investment firms, EMQQ Global and EMXETF . You’ve probably heard of the Magnificent 7. These are stocks from what the West calls Developed Markets. Kevin talked about applying the same idea to emerging markets, he found The MAG 3. Then we moved on to China’s AI Tigers. Kevin challenged our assumptions about US AI leadership with stories from China. Finally, we covered how to create an exchange traded fund or ETF. This matters because there isn’t one for geospatial yet.
October 3, 202651 min
Claude Native GIS with Dekart
Today’s episode is with the founder of Dekart , Volodymyr Bilonenko . We cover WHY he made Dekart, the relationship with Kepler , who he competes with and some discussion of specific geospatial needs of mobility companies like Wayve . He then steps through use of a new Claude skill he made called geoSQL . This skill uses a map in the loop, yes Claude checks images of its own maps in the course of producing a final Dekart output. We finish the discussion by looking at how geospatial business models may evolve in the context of Claude native GIS.
September 21, 2026Episode 4043 min
Mines With PlanetSapling
Ankur Shah, https://www.linkedin.com/in/ankur-s-803497126/ , is founder and CEO of PlanetSapling ( https://planetsapling.com/ ). He talks us through a dataset of 3,000+ mines he's found the location of, and ownership information about, worldwide. He also takes us through related analyses he's been doing, such as with nature data company Cecil ( https://www.linkedin.com/pulse/mineral-supply-chain-nature-risk-screening-cecil-planetsapling-7rqmc/ ). Finally, we turn our attention to the problem of mismanaged mine tailings storage facilities. Or tailings dams. Every year there is a notable collapse of one. An example he gives is from last year where a Sino-Metals Leach Zambia tailings dam collapsed in Zambia. Toxic waste hit the Mwambashi River. This flows into the Kafue River and 60% of Zambians live in its river basin. Roughly 45% of Zambia's population relies directly on the Kafue River for their drinking water. That is 10 million people. Join us today to contribute to the development of a global, authoritative, continuously updated dataset of tailings dam boundaries. Your expertise is sought in creating it, then standing up a tailings dam runout modelling engine. Its outputs regarding predicted lives lost and critical infrastructure damage will incentivise appropriate action by leaders. Or discipline of those leaders by the population.
July 27, 2026Episode 3910 min
GE0500 Weekly Wrap and Starting a New Quant Agri Portfolio
Weekly wrap for 7 days to 7/26/2026 and promo for Quant Agri ( https://quantagri.substack.com/ ) with Ryan Kmetz ( https://www.linkedin.com/in/ryankmetz/ ). I will be incorporating Quant Agri GEOINT-based commodity trading performance going forward, based on a $1,000 starting position.
July 23, 2026Episode 381 hr 0 min
marimo
marimo is the fastest growing Python project with 22,000 Github stars . Fantastic episode today, covering: 0:00 - Intro 0:54 - Favorite keyboard 2:35 - What Coreweave's GPUs mean for marimo, such as solving the Travelling Salesman Problem 8:13 - What is the one thing Jupyter Notebooks always gets wrong, but marimo doesn't? 17:43 - UI elements in marimo library like sliders, cascading updates across cells and marimo notebooks as web apps 20:08 - What marimo means for different modern data team personas 24:39 - Remote storage connections and example of data analyst work 27:15 - How marimo is used by various scientific disciplines and using Anywidget in marimo 31:45 - Use of marimo in an enterprise context for GPU compute, roadmap comments and creative freedom the tool enables 35:37 - Using marimo to defeat the Esri monopoly in geospatial: if you are David, play a different game than Goliath, again the point that marimo/molab offers creative freedom to sponaneously poke around in the data 42:27 - How to use GPUs in marimo, limitations of this 47:55 - Using AI to control marimo 50:30 - Call to action - marimo competition to make coolest notebook from an academic paper 51:20 - Vincent's summary: this is marimo, go and be David, fight Goliath, most of all - creative freedom. [We are trying] to figure out a way for you to be more creatively free. 51:35 - Dice kit 55:48 - More on keyboards. 57:25 - I try pairing Claude and marimo myself. A huge privilege to have Vincent on to tell us all about it. Here are some links to items discussed: marimo joining Coreweave: https://marimo.io/blog/joining-coreweave marimo repo: https://github.com/marimo-team/marimo marimo pair - for helping pair with an AGI: https://github.com/marimo-team/marimo-pair A related blog post: https://marimo.io/blog/claude-code Evidence marimo uses Leafmap: https://docs.marimo.io/api/plotting/?h=map#other-plotting-libraries Anywidget: https://anywidget.dev/ and its dev: https://github.com/manzt Notebooks in Wherobots: https://wherobots.com/blog/wherobots-notebook-environment-getting-started-with-wherobots-cloud-sedonadb-part-2/ Vincent's Wiggly Stuff: https://koaning.github.io/wigglystuff/ marimo recently ended competition: https://marimo.io/pages/events/notebook-competition-2 We are now discussing the next one and adding a geospatial theme to it!
June 23, 2026Episode 3746 min
Mine Tailings Dams with John Metzger of Asset Assurance Monitoring
Guest: John Metzger ( LinkedIn ), Founder of Asset Assurance Monitoring ( Website ). "I don't know how, but I recognized it was one of my children. My friend rescued Nicolas, and I thought: Oh my God, at least I managed to catch one." These were the words of a father fleeing the 2015 Bento Rodrigues (Mariana) dam disaster in Brazil ( O Globo , 08/11/2015). Five days later, his daughter Emanuele was found dead. The collapse killed 19 people and sent a torrent of toxic mine waste 670km down the Doce River to the Atlantic Ocean. It was Brazil’s worst environmental disaster. Four years later, just 70km west, it happened again. The 2019 Brumadinho dam collapse killed 272 people—including an entire family of five and an unborn child—becoming Brazil’s worst industrial disaster. Both mines were owned by corporate giant Vale. When raw ore is extracted, the toxic, liquid byproduct is stored behind massive earthen structures called tailings dams. Globally, there are an estimated 29,000 to 35,000 active, inactive, or abandoned tailings storage facilities (TSFs) holding 223 billion tonnes of waste ( World Mine Tailings Failures ). Active sites account for 85% of all failures. The risk is ongoing: as of late 2025, Brazil alone has 916 dams, with 74 at high risk of collapse and 91 on alert, concentrated heavily in the mining hub of Minas Gerais. When these structures are poorly designed or neglected, they fail. When they fail, the wall of mud obliterates everything in its path. Our guest today, John Metzger, is an expert on the advanced monitoring systems designed to prevent these catastrophes. Having led an incredible, multi-country career, John joins us to explain how real-time data, geotechnical instrumentation, and rigorous telemetry save lives. There were fatal systemic flaws of recent disasters—including why Brumadinho’s emergency warning alarms failed to sound, echoing previous conversations on the show with Floodmapp’s Juliette Murphy on the desperate need for strict flood-alarm regulations ( YouTube Link ). Also corporate failures: reports that Vale knew of automated sensor malfunctions two days before the Brumadinho collapse ( Mining.com Report ) and allegations that safety inspectors felt corporate pressure to sign off on unstable structures. Despite these failures, there are rays of hope. First, the recent establishment of the UN-backed Global Tailings Management Institute ( GTMI ), a new international watchdog tasked with ending corporate negligence in tailings management. Second, I want to honor the legacy of Lindsay Newland Bowker, the actuary behind the vital World Mine Tailings Failures database, who passed away in May 2026. To ensure her work is not lost to time, I have an upcoming conversation with Ankur Shah of PlanetSapling to discuss the future of open-source risk mapping.
June 13, 2026Episode 3637 min
GEO500 Weekly Wrap + Japan Focus
I am joined by Robert Cheatham of Japan Earth Observer (https://www.japanearthobserver.com/) for a GEO500 Weekly Wrap. Provisionally, also the PhysicalAI Weekly Wrap. I'll think about it. GEO500 weekly roundup sheet: https://docs.google.com/spreadsheets/d/1AVbN5pQ9kiRmC0Iw2H8stoPJUngrqntA5DRU3Wll2aE/edit?usp=sharing TacticAI: Google's AI system that can help simulate field scenarios and predict open play dynamics up to 8 seconds in advance. ⚽ https://www.linkedin.com/feed/update/urn:li:share:7470859786159370240/ Google Earth infrastructure layers: https://x.com/googleearth/status/2064752086386930152 Oracle's disastrous quarter: https://www.tradingview.com/news/zacks:a8c6c958c094b:0-oracle-shares-tank-despite-q4-earnings-beat-hold-the-stock-now/ CAD/BIM vertical destruction: Claude Fable 5 has solved CAD: https://x.com/aaronli/status/2064876123109089742?s=46 Nvidia is coming for Autodesk: https://x.com/nvidiartxspark/status/2061825397868630454?s=46 Claud Fable 5 makes 3D/FPS video games in minutes: https://x.com/chrissgpt/status/2065193150222663959?s=46 SpaceX jobs: https://www.spacex.com/careers/jobs
June 8, 2026Episode 3540 min
Japan Earth Observer
Today's guest is Robert Cheatham https://www.linkedin.com/in/rcheetham/ and we are talking about Japan Earth Observer , https://www.japanearthobserver.com/. This is a newsletter on the space, Earth observation, and geospatial industry in Japan. It is based on a fantastic effort by Robert to systematically collate every last company in the space and earth observation supply chain in that country. Naturally I was drawn to it due to my efforts to do this not only for Japan but every country in the world as the GEO500. We got in touch and exchanged our lists which led to the discussion recorded here today. The GEO500 has 56 Japanese companies since inception. 7 of them are delisted. So the index contains 49 live positions for this country. All GEO500 positions start with $100. The entire Japanese part of the GEO500 stands at $AUD13,000. This is because the 56 have compounded at 8% annually since inception. In the case of this country, starting as a position in Fujitsu in 2000. The top three performers in terms of capital growth rate are Terra Drone (125% annually), Synspective (71%) and QPS (59%). The top 3 in terms of value are Sony ($1100 - bear in mind the $100 starting position, equating to a 20% annual growth rate since entering the index in 2013), NEC ($960, 10%) and Raito Kogyo ($760, 11%). Note that the 3 fastest growers are all earth observation companies, and 2 of those are synthetic aperture radar satellite constellations. This is an exciting part of our industry to watch and I have recorded a couple of great episodes on the power of it. For example, - Jamon Van Den Hoek's work as an academic partnering with some of the world's largest media organisations to monitor building destruction in warzones and after fires: https://open.spotify.com/episode/0RQNjzDtTQTNqv8IiMy2SU - Umbra, a pioneering American SAR satellite manufacturer, they also operate their own constellation: https://open.spotify.com/episode/2QM3OeglXI1naiSgrKod17 - Iceye, the equivalent from Finland: https://open.spotify.com/episode/04S3fsdL4cus2tOEbq4KBN - Ursa Space Systems, a commodity intelligence firm that uses SAR to monitor everything from iron ore stockpiles at ports to oil farm tank lids around the world: https://open.spotify.com/episode/3ltO0Bv8Mtq7dgnLhXWGxO - SeerAI, another analytical platform where I coaxed the guest to use SAR as a way to detect surface change on the NEOM excavation, the world's largest (now abandoned) building site: https://www.geospatial.fm/p/seerai-responds-to-johnny-harris But this wasn't just about current companies. We were privileged in this episode to be given a history of Japan's trading houses since the 1860s to today. This led to several insights around the longevity, for example, of the social groups that comprise such firms and how they can persist even through a trust busting effort by the winning country after a world war. Another insight was the benefit to society of trust busting and how it unleashed a wave of new companies and from that household names such as Honda and Sony. Honda recently launched a rocket that was able to land itself. This has relevance to possible future earth observation constellation launches. Sony released LiDAR solution in 2013 and also sells other geospatial products like a GNSS chip. We have come full circle. A final note about Robert himself. We are presented here with a cultivated and successful entrepreneur. He grew a geospatial software development firm to 50 people then sold it. He has learnt a foreign language well enough to spontaneously translate things for me during a podcast recording without warning. He also is able to offer a comprehensive historical view on the emergence, development, setbacks and modern day expression of several dominant companies in a vibrant foreign economy, Japan. He shows us the way, then, on multiple fronts. I am grateful for the chance to put an inspiring industry figure in front of you today. Thanks Robert.
May 29, 2026Episode 3443 min
Listening for Whales with NV5 Geospatial
Mark Baumgartner is a senior scientist at Woods Hole Oceanographic Institution . Back in 2011 he and Sarah Mussoline published a paper on how to use computer science to classify whales from sound recordings . This episode is about an evolution of that software by Atle Borsholm from NV5 Geospatial (https://www.nv5geospatialsoftware.com). At the beginning of the episode you will hear a sound recording. Take a listen and attempt to classify the whale making the calls in it. In my comments at the end of this I’ll tell you what whale that was. It was an easy one to process - the recording was just 7 seconds long and a whale sound was present immediately. Consider if I instead gave you another one lasting a day and most of it was just ocean noise. This leads to the challenge discussed in today’s episode. Imagine I have 100 microphones under the ocean. These are called hydrophones. These hydrophones record for 24 days. The scientists managing them will say they now have 2400 days of data to process. Well, that is nowhere near how big of a challenge this episode is about. The National Oceanic and Atmospheric Administration had 217,197 days of hydrophone recordings going back 20 years. Whilst Mark’s software was available, it needed to be made more efficient to process all this data. It was worth the effort. It turned out that only 24,000, or 11%, of those days involved a whale being detected. All of it is shown on NOAA’s Passive Acoustic Cetacean Map . Atle starts by discussing a web application, Mark’s Robots4Whales website , in our episode today. Links for further reading: NV5 article on Harnessing Data Science for Marine Conservation : https://www.nv5geospatialsoftware.com/Learn/Case-Studies/Case-Studies-Detail/harnessing-data-science-for-marine-conservation NV5 article on IDL® Software Extract Meaningful Visualizations From Complex Numerical Data : https://www.nv5geospatialsoftware.com/Products/IDL Slocum glider from Teledyne Marine : https://www.teledynemarine.com/brands/webb-research/slocum-glider Woods Hole article on whale sound detection and classification : https://www.fisheries.noaa.gov/science-blog/listening-sounds-gulf The whale at the start? It was a humpback whale. Only Gemini managed to classify it correctly. Claude and ChatGPT got it wrong.
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