Spatial Stack with Matt Forrest – Détails, épisodes et analyse

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.nyc

00:00 - 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 Everything

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Have you ever stopped to think about how GPS completely changed the world simply by becoming an invisible infrastructure running in the background of our everyday apps?

According to Pierrick Poulenas, the CEO and co-founder of Picterra, the exact same pattern is playing out right now with Earth Observation and GeoAI.In this episode, we sit down with Pierrick to explore how GeoAI is bridging the gap between raw satellite imagery and accessible business intelligence. We dive into how Picterra is removing the friction of complex remote sensing data, allowing non-technical users to train machine learning models and turn planetary pixels into actionable insights.

We also discuss the massive real-world impact this has on global supply chains and monitoring regenerative agriculture at scale. Plus, Pierrick shares his vision for a collaborative future in the space industry and teases an exciting new free tool for sustainability innovation.

Connect with Pierrick and Picterra:

https://picterra.ai/
https://www.linkedin.com/company/picterra/

Key Takeaways:

- Why Earth Observation is following the "GPS Playbook" to reach mass adoption.
- The shift from just collecting raw satellite data to creating usable applications at scale.
- How human-in-the-loop design builds trust and accuracy in AI models.
- Real-world use cases in spatial finance, fast-moving consumer goods (FMCG), and regenerative agriculture.

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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 started

This 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 workflows

Resources 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

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🚀 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

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0:00 Intro to GeoPandas
0:35 What is GeoPandas
2:54 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 GeoPandas
13:06 When NOT to use GeoPandas?
14:50 Where to learn about GeoPandas?

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Meta has more than 3 billion users across Instagram, WhatsApp, and even its new AR glasses. Behind the scenes, all of them are powered by one thing: maps. But instead of relying on closed systems, Meta is betting big on open data—and building its own global map.

In this episode, I talk with Said Turksever from Meta, who leads their open mapping strategy. We dive into:

🌍 Why Meta cares so much about maps
🛠 The tools they’re building with AI and open source
🏙 How cities from Phoenix to Naples are being transformed by open data
🚶 The future of pedestrian mapping and accessibility
🤝 The role of communities in shaping the next generation of maps

From disaster response to daily navigation, the impact of open mapping stretches far beyond social media. This is a conversation about technology, community, and the future of how we navigate the world.

🚀 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 6 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
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💼 LinkedIn: https://www.linkedin.com/in/mbforr/
📧 Newsletter: https://forrest.nyc
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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

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🚀 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 Pro
0:31 My background with Esri
1:16 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 Pro
17:47 When to use ArcGIS Pro?
20:15 Where to learn about ArcGIS Pro?

CONNECT WITH ME
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In this episode, I sit down with Felix Palmer, creator of A5, a new global grid system that’s redefining how we represent and analyze the Earth.
Felix shares how a 1980s math paper led him to build a pentagon-based global grid, one that fixes the distortions found in systems like H3 and S2, achieving true equal-area cells across the entire planet.

We discuss the geometry behind A5, the trade-offs of global gridding, and why visual design and spatial computation are deeply connected.
If you’ve ever worked with spatial indexes or wondered how we might rebuild the geometry of the globe itself, this episode will change the way you see maps.

We cover:

The origins of A5 and how it compares to H3
Why equal-area grids matter for accurate analysis
The visual and geometric challenges of mapping a sphere

A5 Website: https://a5geo.org/
A5 on GitHub: https://github.com/felixpalmer/a5

🚀 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 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 sensing
How foundation models like AlphaEarth and Tessera are trained
The challenges of applying ML at global scale
The future of Earth observation data pipelines
Why 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 CORLEY

Website: https://isaacc.dev/
LinkedIn: linkedin.com/in/isaaccorley
X: @isaaccorley_
GitHub: @isaaccorley
I’m active in TorchGeo slack: free to join https://join.slack.com/t/torchgeo/shared_invite/zt-22rse667m-eqtCeNW0yI000Tl4B~2PIw

CHRISTOPHER REN

Blog: https://christopherren.substack.com/
Podcast: Spotify | Apple | Youtube
LinkedIn: 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

AI can answer almost anything, except “where.” That gap is huge, and  Kieran McCann from Mapbox is working to close it.

In this episode of The Spatial Stack, Matt sits down with Kieran, who’s spent six years helping Mapbox quietly power some of the most widely used maps and location services in the world. From his early days doing grunt map edits at Apple Maps to shaping Mapbox’s next big bet: AI-native mapping. Kieran shares what it takes to bring true spatial understanding into artificial intelligence.

You’ll hear how Mapbox is experimenting with ways for AI to finally reason about place and direction, what’s still missing for models to “get” geography, and how anyone, even those just starting out, can build powerful AI + geospatial tools today. Kieran also breaks down how showing prototypes can change your career trajectory and why now is the perfect time to jump into this space.

If you’re curious about where mapping and AI collide and what that means for your work, your career, and the apps we all use every day, this conversation is a must-listen.

🚀 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/

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🚀 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 happens when a geospatial professional decides to map the entire business of our industry?

In this episode of Spatial Stack, Matt talks with Wilfred Waters, the creator of the first-ever Geospatial Index, a hand-built list tracking hundreds of public companies shaping maps, data, satellites, sensors, and spatial software. Will shares how he spent countless late nights pulling together every geospatial stock he could find, from Vietnam to Finland to the U.S., and what the process revealed about where the industry is heading.

Along the way, we unpack how indexes work, why understanding the business side of geospatial matters (even if you’re not an investor), and how seeing the market clearly can help you think differently about your own career and the technologies you rely on.

Geospatial FM on Spotify: https://open.spotify.com/show/5gpQUsaWxEBpYCnypEdHFC
On Apple Podcasts: https://podcasts.apple.com/us/podcast/geospatial-fm/id1674368928
Substack: www.geospatial.fm
Index introduction and construction rules: https://www.geospatial.fm/p/compounding
2024 Year In Review: https://www.geospatial.fm/p/2024-geospatial-stocks-performance

⚠️ Nothing in this episode is investment advice. It’s for educational and informational purposes only.