Spatial Stack with Matt Forrest

In this episode of the Spatial Stack, Matt sits down with Maggie Ma, tech content creator at @maggieindata and former geospatial data scientist.Maggie left her corporate data science role last year to become a full-time content creator across Instagram, YouTube, LinkedIn, and TikTok. She's a 3x LinkedIn Learning instructor and an AI educator helping people break into data science, learn coding, and stay current with AI.We dig into the GIS title trap (and why the same job pays less under a different title), the seven internships that got Maggie into geospatial data science, cold-emailing professors and police departments, and how she positioned herself as the spatial person on non-spatial teams. We also cover the push and pull factors that led to her quitting corporate, what day in the life looks like as a full-time creator, and how she actually uses AI in her workflow today.Whether you're a GIS analyst wondering if you're underpaid, a geography student trying to land your first role, or a working data scientist thinking about going full-time creator, this conversation is full of specific tactics and honest reflections.Connect with Maggie:Instagram: https://www.instagram.com/maggieindataYouTube: https://www.youtube.com/@maggieindataLinkedIn: https://www.linkedin.com/in/maggieindataTikTok: https://www.tiktok.com/@maggieindataCHAPTERS:00:00:00 – Intro00:01:08 – Welcome and Maggie's Background00:03:26 – Statistics, Psychology, and Discovering Human Geography00:06:39 – First Job: Geospatial Data Scientist in Logistics00:08:08 – The GIS Title Trap and Salary Bands00:11:33 – Cold Emailing Into Crime Analytics and Hospital Research00:14:16 – Starting to Create Content as a Working Data Scientist00:18:50 – Push and Pull Factors for Leaving Corporate00:21:28 – Adjusting to Life Without a Job as Input00:27:33 – Vibe Coding: Lovable, Warp, and Claude Code00:29:08 – The Hidden Risks of Vibe Coding (Security, Data Leaks)00:32:08 – Using AI in Content Workflows00:36:19 – Final Advice and Where to Find Maggie📊 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/CONNECT WITH ME📸 Instagram: https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

The future is spatial, but how do we actually make sense of the data? In this episode, we sit down with Emily Lisle from Dataplor to discuss the current state of location intelligence and how to overcome the biggest location intelligence challenges facing businesses today.We dive into the data foundation, exploring the massive complexities of scaling geospatial data, consumer data, and POI data on a global level. Emily breaks down the gap between simply having access to millions of rows of location intelligence data and actually turning it into actionable business strategies.To solve this, Dataplor launched a new location intelligence platform. By making it easy to visualize location data, non-technical teams can finally execute complex spatial analysis in gis without waiting on a data scientist.We also explore powerful location intelligence use cases and location intelligence applications. Learn how real estate investors and CPG brands are using this data to fuel their global expansion strategy and retail expansion strategy by identifying market gaps and tracking competitors.Finally, Emily shares how AI location data integration and AI analysis location data are changing the game, and why establishing a verified "ground truth" is more important than ever.LEARN MORE ABOUT DATAPLORLearn More: https://www.dataplor.com/solutions/global-platform/Follow Dataplor on LinkedIn: https://www.linkedin.com/company/dataplor/Book a Demo: https://www.dataplor.com/contact/Key Takeaways- The End of the CSV: How the industry is moving from massive, hard-to-process spreadsheets to visual spatial analysis software that answers specific business questions instantly.- Finding "Ground Truth": Why relying on a single mobility signal isn't enough anymore, and how layering alternative consumer data ensures high-quality insights.- Winning Global Expansion Strategy: Real-world examples of how CPG brands and real estate investors use location intelligence platforms to spot market gaps and track global competitors.- The AI Data Revolution: How AI location intelligence and the Model Context Protocol (MCP) are transforming how we consume and personalize geospatial data00:00 Introduction to the State of Location Intelligence & Its Challenges 03:14 The Foundation: Scaling Geospatial Data & POI Data Globally 06:48 Bridging the Gap: Location Intelligence Solutions & Analytics 09:06 Overcoming Location Intelligence Data Privacy Roadblocks 14:50 Building a Location Intelligence Platform to Visualize Location Data22:42 Location Intelligence Use Cases: Global Retail Expansion Strategy28:44 Validation in Spatial Analysis Software: Finding the "Ground Truth"34:37 The Future: AI Location Intelligence & Model Context Protocol (MCP) 41:42 How to Connect with 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

If you are still trying to run your entire geospatial workflow on a local desktop, you are fighting a losing battle. The "Modern GIS Stack" looks chaotic at first glance with dozens of logos, cloud formats, and new databases. But once you strip away the noise, there are actually only a few key layers you need to master to make it all work.🚀 Don't navigate this shift alone. Join the Spatial Lab: https://forrest.nyc/spatial-lab/In this video, I break down the architecture that is replacing the traditional GIS model. We move beyond Shapefiles and Geodatabases into the world of Cloud-Native Geospatial, showing you exactly how Storage, Compute, and Analytics have separated—and how you can use them to scale your career.📰 Daily modern GIS insights: https://forrest.nyc00:00 - The Modern GIS Chaos 00:34 - The Shift to Cloud-Native Formats 01:14 - Why Storage Buckets Replaced Hard Drives 02:07 - Essential Formats: GeoParquet, COGs & Zarr 03:57 - Adding Intelligence: STAC & Iceberg Catalogs 06:07 - Transformation & Orchestration (GDAL, dbt, Airflow) 08:30 - The 3 Engines of Modern GIS 08:48 - Engine 1: The Processing Layer (Sedona, Wherobots) 11:19 - Engine 2: The Transactional Layer (PostGIS) 12:38 - Engine 3: The Analytical Layer (BigQuery, Snowflake, DuckDB) 14:54 - Mapping Modern Layers to Traditional GIS 16:29 - The Application Layer: Analytics & BI 17:35 - Connecting QGIS & Python to the Cloud 18:30 - Modern Web Maps (Felt, Mapbox, DeckGL) 20:24 - Conclusion: You Don't Need to Learn EverythingCONNECT 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 with Kyle Walker, Professor of Geography at TCU and the creator of popular R packages like tigris and tidycensus.Kyle dives into why he views US Census data as critical infrastructure and how open data is fundamentally transforming decision-making across industries like real estate and energy. He shares the origin story of his open-source work, explaining why he champions the R programming language for full-stack geospatial analysis. The conversation also covers the evolution of web mapping, from the laborious process of rendering dot-density maps to the blazing-fast performance of modern tools like PMTiles.Finally, Kyle reveals how generative AI specifically Claude Code and the Zed editor is serving as his ultimate coding assistant, allowing him to rapidly build complex projects like the mapgl package and turn his ideas into reality faster than ever.Connect with Kyle:X/Twitter: https://x.com/kyle_e_walkerLinkedIn: https://www.linkedin.com/in/walkerke/Bluesky: https://bsky.app/profile/kylewalker.bsky.social00:01:00 – Welcome and Kyle Walker’s Background at TCU 00:06:18 – Why US Open Data is Critical Infrastructure 00:09:20 – Demystifying Census Data with tigris and tidycensus 00:15:48 – Applied Spatial Data: Real Estate and Forecasting Models 00:18:28 – The Evolution of High-Resolution Dot Density Maps 00:23:48 – The Human Element: How People React to Seeing Data Maps 00:29:14 – R vs. Python: Why R is a Geospatial Powerhouse 00:37:44 – Accelerating Development: Using Claude and AI for Coding 00:43:40 – The Future of Mapping: PMTiles, Segment Anything, and LLMs 00:48:18 – Where to Find Kyle’s Book, Tools, and Workshops---🚀 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

There are trillions of dollars invested in the physical world every da: infrastructure, supply chains, and our planet.Yet many of these massive decisions are made without the data to back them up. For too long, geospatial analytics has been gated behind specialized teams and siloed technology, treated as "spatial is special" rather than just another data type.In this episode, we sit down with Damian Wiley from Wherobots to break down how cloud architecture is finally closing this gap. With a heavy-hitting background from AWS EC2 and Databricks, Damian explains the shift from transactional databases to the Lakehouse architecture and why "Zero ETL" is the holy grail for data engineering. We dive deep into why spatial data shouldn't be gated, how open table formats like Iceberg are changing the game, and why the future involves AI agents that can directly query the physical world.If you are a data engineer, developer, or leader looking to unlock location intelligence without the headache of complex infrastructure, this conversation is for you.✅ Sign Up for Wherobots: https://wherobots.com/✅ Learn more about Apache Sedona: https://wherobots.com/apache-sedona/✅ What is Apache Sedona: https://wherobots.com/blog/what-is-apache-sedona/✅ Test out SedonaDB: https://sedona.apache.org/sedonadb/latest/✅ Connect with Jia on LinkedIn: https://www.linkedin.com/in/wyliedamian/00:00 - The Trillion Dollar Data Gap: Investing in the physical world without intelligence 02:15 - From AWS EC2 to Geospatial: Damian’s journey from cloud infrastructure to spatial data 06:40 - "Spatial is Special" No More: Breaking down silos and making spatial data "just data" 09:00 - The Lakehouse Advantage: Decoupling storage and compute for economic agility 12:15 - Fragmented History: Why geospatial tech became so compartmentalized 17:30 - Real-World Impact: Optimizing supply chains and climate response with frequent data 22:45 - The Economics of Analytics: Lowering the Total Cost of Ownership (TCO) for pipelines 28:30 - AI Agents & The Physical World: Connecting LLMs to ground-truth reality 37:00 - Compute Strategy: When to use OLAP vs. OLTP for spatial workloads 46:00 - Zero ETL & The Future: How Iceberg and open standards enable interoperability 51:20 - Getting Started with SedonaDB: Vibe coding and the future of spatial queries📰 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 1963, the US Postal Service introduced "Mr. Zip" to make mail delivery faster. They never intended for those five digits to determine your insurance premiums, your home value, or your health outcomes.In this short deep-dive, we explore how an arbitrary logistical tool became a shorthand for community and why that’s dangerous. From the misleading boundaries of Dallas, Texas, to the tragic data failures during the Flint water crisis, we uncover the real story behind the map.Listen in to learn why it's time to move beyond the zip code and start looking at the details that actually matter.---Whenever you’re ready, here are 3 ways I can help you:🎓 Modern GIS Accelerator: The step-by-step roadmap to master Python, Spatial SQL & Cloud workflows. Stop just "making maps" and start building spatial solutions. 👉 https://forrest.nyc/accelerator/🧪 The Spatial Lab: Join the top 5% of geospatial professionals in our private community. Get access to exclusive courses, mentorship, and the network you need to level up. 👉 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

We have an incredible amount of public geospatial data—high-resolution elevation, weather forecasts, floodplain maps, real-time sensors—yet most people still can’t easily answer a simple question:“What’s my flood risk right here, right now?”In this episode, I’m joined by Kevin Bullock, an aerospace engineer and remote sensing expert at Development Seed, to talk about how he turned years of geospatial expertise into Hydra Atlas, a mobile app designed to make flood risk understandable and accessible for everyday users.We explore why so much critical data remains difficult to use, how Kevin pulled together datasets from FEMA, NOAA, and USGS, and why mobile—not web—was the right platform for this problem. Kevin also shares what it was like building a geospatial app with Swift, testing real-world use cases, and designing an interface that prioritizes clarity over complexity.This conversation goes beyond flooding. It’s about modern GIS, product thinking, open data, and what happens when geospatial professionals stop building tools for other experts and start building tools for people.If you’re interested in geospatial product development, public data, mobile mapping, or turning complex systems into usable software, this episode is for you.Download HydraAtlas: https://apps.apple.com/us/app/hydraatlas/id6749492232Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevbullock/---Whenever you’re ready, here are 3 ways I can help you:🎓 Modern GIS Accelerator: The step-by-step roadmap to master Python, Spatial SQL & Cloud workflows. Stop just "making maps" and start building spatial solutions. 👉 https://forrest.nyc/accelerator/🧪 The Spatial Lab: Join the top 5% of geospatial professionals in our private community. Get access to exclusive courses, mentorship, and the network you need to level up. 👉 https://forrest.nyc/spatial-lab/🧭 Career Compass: Not sure where to start? Get the fast, practical steps to land the GIS role you actually want. 👉 https://forrest.nyc/career-compass/📰 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

GeoPandas is one of the most important tools in modern GIS, but many people still aren’t sure when to use it, why it matters, or where it fits alongside tools like PostGIS, DuckDB, Apache Sedona, and cloud-native data formats.In this video, I break down GeoPandas from the ground up: what it is, how it works under the hood, its strengths and limitations, and when to choose something else. If you’ve ever worked in ArcGIS or QGIS and wondered how to bring those same workflows into Python, this is the perfect place to start.What we cover in this video:- What GeoPandas actually does (How it extends Pandas, adds geometry types, reads vector formats, and integrates tools like Shapely, Fiona, PyProj, GeoArrow, and GeoParquet)- Why GeoPandas matters in modern GIS- When GeoPandas is the right tool- When NOT to use GeoPandas- How GeoPandas fits into the modern stack (How it pairs with DuckDB, SedonaDB, PostGIS, Apache Sedona (Spark), data lakes, Iceberg, and cloud-native geospatial)- How to actually get startedThis video is for you if you are a:• GIS professionals moving into Python• Data scientists adding spatial capabilities• Engineers exploring geospatial data stacks• Anyone who wants a modern alternative to desktop GIS workflowsResources from the video- My GeoPandas Course: https://www.youtube.com/watch?v=0mWgVVH_dos- GeoPandas Documentation: https://geopandas.org/en/stable/getting_started/introduction.html- Dr. Qiusheng Wu's New Book on Geospatial Python: https://www.amazon.com/dp/B0FFW34LL3---🚀 Ready to move beyond desktop GIS?Step into the Spatial Lab: a global community for ambitious geospatial professionals who want to break out of outdated workflows and join the top 5% of the field.👉 Join Spatial Lab: https://forrest.nyc/spatial-lab/🎓 Want structured, career-changing learning?🚀 Modern GIS Accelerator: https://forrest.nyc/accelerator/ — master Python, Spatial SQL & cloud workflows in 2 weeks🧭 Career Compass: https://forrest.nyc/career-compass/ — fast, practical steps to land the GIS role you want🪄 AI Copilot for GIS: https://forrest.nyc/ai-copilot-for-gis/ — learn to integrate AI into your geospatial workflows & boost your productivity📰 Weekly modern GIS insights: https://forrest.nyc⚡️ Spots for the next live cohort and mentorship cycle are closing soon, join now to lock in your place and momentum.0:00 Intro to GeoPandas0:35 What is GeoPandas2:54 Why should you care about GeoPandas?5:12 Do you need to use GeoPandas?8:22 How do you use GeoPandas?10:59 Pitfalls of GeoPandas13:06 When NOT to use GeoPandas?14:50 Where to learn about GeoPandas?CONNECT WITH ME📸 Instagram: https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

ArcGIS Pro has been the center of GIS workflows for decades but how does it hold up in a world moving toward open, cloud-native, and AI-powered geospatial tools? In this video, I break down what ArcGIS Pro actually is, where it shines, where it struggles, and how it fits into the modern GIS ecosystem. Whether you’re doing personal GIS projects, running a small team, or architecting enterprise-scale systems, this deep dive will help you understand when ArcGIS Pro is the right choice and when alternatives like QGIS, GeoPandas, DuckDB, PostGIS, Sedona, or cloud-native stacks might serve you better.What You’ll Learn- What ArcGIS Pro is and how it fits into Esri’s ecosystem- Its strengths in cartography, desktop analysis, 3D tools, enterprise integration, and data management- Newer support for modern formats like GeoParquet, COGs, STAC, and DuckDB- Where ArcGIS Pro begins to struggle (big data, cloud workflows, Python lock-in, cost/licensing)- How it compares to open tools like QGIS, GeoPandas, and modern geospatial data platforms- My honest assessment of whether YOU should be using ArcGIS Pro across personal, team, and enterprise use cases---🚀 Ready to move beyond desktop GIS?Step into the Spatial Lab: a global community for ambitious geospatial professionals who want to break out of outdated workflows and join the top 5% of the field.👉 Join Spatial Lab: https://forrest.nyc/spatial-lab/🎓 Want structured, career-changing learning?🚀 Modern GIS Accelerator: https://forrest.nyc/accelerator/ — master Python, Spatial SQL & cloud workflows in 2 weeks🧭 Career Compass: https://forrest.nyc/career-compass/ — fast, practical steps to land the GIS role you want🪄 AI Copilot for GIS: https://forrest.nyc/ai-copilot-for-gis/ — learn to integrate AI into your geospatial workflows & boost your productivity📰 Weekly modern GIS insights: https://forrest.nyc⚡️ Spots for the next live cohort and mentorship cycle are closing soon, join now to lock in your place and momentum.0:00 Intro to ArcGIS Pro0:31 My background with Esri1:16 What is ArcGIS 4:02 Why does ArcGIS Pro matter?7:11 Do you need to use ArcGIS Pro?12:54 How do you use ArcGIS Pro?14:50 Pitfalls of ArcGIS Pro17:47 When to use ArcGIS Pro?20:15 Where to learn about ArcGIS Pro?CONNECT 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 really take to teach AI to understand our planet?In this episode, Matt sits down with Isaac Corley, Senior Machine Learning Engineer at Wherobots and maintainer of TorchGeo, and Christopher Ren, Data Scientist and writer behind some of the most thought-provoking essays on Earth observation and AI.They dive deep into the state of Geospatial AI from embeddings and foundation models to how these tools are reshaping Earth observation and remote sensing. You’ll hear real-world perspectives on what’s working, what’s not, and where the hype outpaces reality.Key topics covered:What "embeddings" actually mean for geospatial and remote sensingHow foundation models like AlphaEarth and Tessera are trainedThe challenges of applying ML at global scaleThe future of Earth observation data pipelinesWhy geospatial AI is still the "wild west"If you’ve ever wondered how AI models are built to map, monitor, and understand the Earth, this conversation breaks it down without the buzzwords.LINKS:ISAAC CORLEYWebsite: https://isaacc.dev/LinkedIn: linkedin.com/in/isaaccorleyX: @isaaccorley_GitHub: @isaaccorleyI’m active in TorchGeo slack: free to join https://join.slack.com/t/torchgeo/shared_invite/zt-22rse667m-eqtCeNW0yI000Tl4B~2PIwCHRISTOPHER RENBlog: https://christopherren.substack.com/Podcast: Spotify | Apple | YoutubeLinkedIn: https://www.linkedin.com/in/christopherren/Geovibes/Github: https://github.com/cr458/geovibes🚀 Ready to move beyond desktop GIS?Step into the Spatial Lab: a global community for ambitious geospatial professionals who want to break out of outdated workflows and join the top 5% of the field.👉 Join Spatial Lab: https://forrest.nyc/spatial-lab/🎓 Want structured, career-changing learning?🚀 Modern GIS Accelerator: https://forrest.nyc/accelerator/— master Python, Spatial SQL & cloud workflows in 2 weeks🧭 Career Compass: https://forrest.nyc/career-compass/— fast, practical steps to land the GIS role you want🪄 AI Copilot for GIS: https://forrest.nyc/ai-copilot-for-gis/— learn to integrate AI into your geospatial workflows & boost your productivity📰 Weekly modern GIS insights: https://forrest.nyc⚡️ Spots for the next live cohort and mentorship cycle are closing soon, join now to lock in your place and momentum.CONNECT WITH ME📸 Instagram: https://www.instagram.com/matt_forrest/💼 LinkedIn: https://www.linkedin.com/in/mbforr/📧 Newsletter: https://forrest.nyc🌐 Website: https://forrest.nyc

GeoAI isn’t just another buzzword, it’s a turning point for the entire geospatial industry. In this episode of The Spatial Stack, Matt sits down with Tee Barr, Director at Verisk and Councilor for the American Geographical Society, to unpack why GeoAI could reshape the field as profoundly as GPS once did.From climate risk and supply chain resilience to defense, finance, and human security, Tee explains how AI is already influencing high-stakes decision making and why the upcoming Geography 2050 event is dedicating its theme to this massive shift.You’ll hear how GeoAI is challenging long-held assumptions about spatial data, the new opportunities and risks it creates, and why ethical responsibility must keep pace with technical innovation. Whether you’re a geospatial professional, business leader, or educator, this conversation will help you understand the stakes and the opportunities in the next era of mapping and analytics.Register for Geography 2050 here: https://www.geography2050.org/---🚀 Ready to move beyond desktop GIS?Step into the Spatial Lab: a global community for ambitious geospatial professionals who want to break out of outdated workflows and join the top 5% of the field.👉 Join Spatial Lab: https://forrest.nyc/spatial-lab/🎓 Want structured, career-changing learning?🚀 Modern GIS Accelerator: https://forrest.nyc/accelerator/ — master Python, Spatial SQL & cloud workflows in 2 weeks🧭 Career Compass: https://forrest.nyc/career-compass/ — fast, practical steps to land the GIS role you want🪄 AI Copilot for GIS: https://forrest.nyc/ai-copilot-for-gis/ — learn to integrate AI into your geospatial workflows & boost your productivity📰 Weekly modern GIS insights: https://forrest.nyc⚡️ Spots for the next live cohort and mentorship cycle are closing soon, join now to lock in your place and momentum.CONNECT 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 if satellites became as smart and as accessible as your smartphone?In this episode, I sit down with Michael Bartholomeusz, CEO of NOVI to unpack how Earth observation is being transformed by edge computing in space. We explore the shift from sending terabytes of raw imagery to delivering actionable insights, and why this change could take the cost of analysis from $150,000 down to under $1,000.Michael shares stories from his 25-year career, from working on the space shuttle that launched John Glenn, to leading NOVI’s dual-use strategy for defense and commercial markets. Along the way, we dive into:Why the current Earth observation model is brokenHow edge computing flips the economics of space dataThe “iPhone moment” for satellites and what it means for new applicationsReal-world examples of cost savings and new use casesThe industries poised to benefit most — from defense to agriculture to disaster responseThis is a conversation about more than satellites. It’s about making Earth observation affordable, democratized, and insight-driven.NOVI’s Website: www.novispace.aiNOVI’s LinkedIn: https://www.linkedin.com/company/novispace-incNOVI’s GENIE™ Constellation Press Release: https://www.newswire.com/news/novi-unveils-genie-tm-a-platform-and-satellite-constellation-that-22622479

Open data is supposed to unlock innovation, but what happens when “open” isn’t really open?In this episode of The Spatial Stack, I sit down with return guest Mina Nada to explore the world of open data licenses — from Creative Commons to Open Database Licenses and beyond. We break down what these licenses actually allow you to do, where the pitfalls are, and how they impact anyone building geospatial products, tools, or services.Along the way, Mina shares real-world experiences navigating licensing challenges, from NASA’s permissive CC0 approach to the more restrictive “share-alike” models. Whether you’re a developer, analyst, or entrepreneur, this conversation will help you understand how to work with open data without running into legal or business roadblocks.If you’ve ever wondered what “open data” really means for your projects, this is the episode to listen to.The future is spatial — so let’s get into it.