The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

Ian Schuler is the CEO of Development Seed — the team behind a lot of the open source tooling that quietly holds up the geospatial world. He's been at the helm for over a decade, and in this conversation, we dig into what he calls the great retooling: the idea that cloud-native geospatial is about to flip from an emerging pattern to the dominant one, and that AI is the thing tipping it over the edge. The argument is simple — agents want to discover your data, query it, transform it, and hand back an answer. If your data isn't in a format they can reach, you're simply not part of the conversation anymore. A really enjoyable one. I hope you get as much out of it as I did. Register for the forum 👉 https://2026.cloudnativegeo.org — This episode is sponsored by the Cloud Native Geospatial Forum. The CNG Forum 2026 runs October 6–9 at Snowbird, Utah — three days of real-world cloud-native geospatial (STAC, COGs, GeoParquet, Zarr, and more) with the teams actually building this stuff at scale, plus a hands-on workshop day to kick things off. Register at https://2026.cloudnativegeo.org

AI Slop: An Experiment in Discovery Solo Episode Reflection: I'm back behind the mic after about a year-long break. Producing this podcast takes more time than you might imagine, and I was pretty burnt out. The last year brought some major life events, including moving my family back to New Zealand from Denmark, dealing with depression, burying my father, starting a new business with my wife, and having a teenage daughter in the house. These events took up a lot of space. The Catalyst for Return: Eventually, you figure out how to deal with grief, stop mourning the way things were, and focus on the way things could be. When this space opened up in my life, AI came into the picture. AI got me excited about ideas again because for the first time, I could just build things myself without needing to pitch ideas or spend limited financial resources. On "AI Slop": I understand why some content is called "slop," but for those of us who see AI as a tool, I don't think the term is helpful. We don't refer to our first clumsy experiments with other technologies—like our first map or first lines of code—as slop. I believe that if we want to encourage curiosity and experimentation, calling the results of people trying to discover what's possible "slop" isn't going to help. My AI Experimentation Journey My goal in sharing these experiments is to encourage you to go out and try AI yourself. Phase 1: SEO and Content Generation My experimentation began with generating SEO-style articles as a marketing tool. As a dyslexic person, I previously paid freelancers thousands of dollars over the years to help create content for my website because it was too difficult or time-consuming for me to create myself. Early Challenges & Learning: My initial SEO content wasn't great, and Google recognized this, which is why those early experiments don't rank in organic search. However, this phase taught me about context windows, the importance of prompting (prompt engineering), and which models and tools to use for specific tasks. Automation and Agents: I played around with automation platforms like Zapier, make.com, and n8n. I built custom agents, starting with Claude projects and custom GPTs. I even experimented with voice agents using platforms like Vappy and 11 Labs. Unexpected GIS Capabilities: During this process, I realized you can ask platforms like ChatGPT to perform GIS-related data conversions (e.g., geojson to KML or shapefile using geopandas), repro data, create buffers around geometries, and even upload a screenshot of a table from a PDF and convert it to a CSV file. While I wouldn't blindly trust an LLM for critical work, it's been interesting to learn where they make mistakes and what I can trust them for. AI as a Sparring Partner: I now use AI regularly to create QGIS plugins and automations. Since I often work remotely as the only GIS person on certain projects, I use AI—specifically talking to ChatGPT via voice on my phone—as a sparring partner to bounce ideas off of and help me solve problems when I get stuck. Multimodal Capabilities: The multimodal nature of Gemini is particularly interesting; if you share your screen while working in QGIS, Gemini can talk you through solving a problem (though you should consider privacy concerns). The Shift to Single-Serve Map Applications I noticed that the digital landscape was changing rapidly. LLMs were becoming "answer engines," replacing traditional search on Google, which introduced AI Overviews. Since these models no longer distribute traffic to websites like mine the way they used to, I needed a new strategy. The Problem with Informational Content: Informational content on the internet is going to be completely dominated by AI. The Opportunity: Real Data: AI is great at generating content, but if you need actual data—like contours for your specific plot of land in New Zealand—you need real data, not generated data. New Strategy: My new marketing strategy is to create targeted

Exploring the Evolution and Impact of Mapillary with Ed from Meta. Topics include Ed's journey with Mapillary, the process of uploading and utilizing street-level imagery, and the integration with OpenStreetMap. Ed talks about the challenges of mapping with various devices, the role of community contributions, and future potentials in mapping technology, such as using neural radiance fields (NeRFs) for creating immersive 3D scenes. The episode provides insights into how Mapillary is advancing geospatial data collection and usage. 00:00 Introduction to the Map Scaping Podcast 00:57 Meet Ed: Product Manager at Meta 02:09 Ed's Journey with Mapillary 03:59 What is Mapillary? 07:00 The Evolution of 360 Cameras 09:20 Uploading Imagery to Mapillary 14:10 Building a 3D Model of the World 19:10 Meta's Use of Map Data 21:24 The Importance of Community in Mapping 24:15 The Importance of Authoritative Data 24:49 Meta's Contributions to Open Source Geo World 25:27 Real-World Applications: Vietnam's B Group 28:16 Innovative Mapping in Detroit 31:38 Future of Mapping: Lidar and Beyond 32:20 Exploring Neural Radiance Fields (NeRFs) 35:40 Challenges and Innovations in Mapping Technology 45:25 Community Contributions and Future Directions 46:37 Closing Remarks and Contact Information Previous episodes that you might find interesting https://mapscaping.com/podcast/scaling-map-data-generation-using-computer-vision/ https://mapscaping.com/podcast/the-rapid-editor/ https://mapscaping.com/podcast/overture-maps-and-the-daylight-distribution/

In this week’s episode, I’m thrilled to welcome back Ariel Seidman, founder of HiveMapper. Ariel was my very first podcast guest back in 2019, and HiveMapper has come a long way since then! We explore how HiveMapper has evolved from a drone-based mapping system to a cutting-edge platform collecting street-level data at a global scale. Ariel shares the challenges of scaling large-scale mapping efforts, the pivot to building their own hardware, and the role of blockchain-based incentives in driving adoption. Here are just a few topics we cover: Why HiveMapper shifted focus from drones to street-level mapping. The power of combining hardware and software to solve mapping challenges. How HiveMapper has already mapped 28% of the global road network. The revolutionary edge computing and data filtering techniques driving efficiency. What it takes to compete with industry giants like Google Maps. Whether you're fascinated by the intersection of geospatial technology and innovation or looking for insights into scaling impactful startups, this episode is packed with value. Let me know your thoughts or hit reply if you’d like to discuss the episode! https://beemaps.com/ Connect with Ariel here https://www.linkedin.com/in/aseidman/ PS I have just finished creating a web-based tool that lets you explore and download OpenStreetMap data, It is a bit different from other tools and I would appreciate some feedback. https://mapscaping.com/openstreetmap-category-viewer/

Today's episode touches on some pretty big topics like Imposter Syndrome, Mentorship, Career Progression, Adaptability and Diversity Today you are going to hear two stories from two very different voices. Two brilliant people who happen to be women in geospatial. Ta Taneka https://www.linkedin.com/in/ta-taneka/ Mary Murphy https://www.linkedin.com/in/mary-murphy-12319433/ You can check out the GIS Directions Podcast here: https://esriaustralia.com.au/gis-directions-podcast or search for GIS Directions where every you listen to podcasts Recommended Podcast Episodes Getting where you want to go in your geospatial career Mentorship leadership and career advice Mentorship leadership and career advice

This is the story of Priscilla Cole, and what she did when she discovered that her ambitions were bigger than the tools she was using! Connect with Priscilla here! https://www.linkedin.com/in/priscilla-cole-5892549/ Recommended Listening The Way You Talk About Your Skills Is Costing You Money Geospatial Consulting As A Business And Career Mid-Life Career Change Getting Where You Want To Go In Your Career Applying For A Job, Getting Picked and Negotiating Mentorship Leadership And Career Advice