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# Matt Forrest

Modern GIS and Geospatial

## Sitemaps

- [XML Sitemap](https://forrest.nyc/sitemap.xml): Contains all public & indexable URLs for this website.

## Posts

- [Posts](https://forrest.nyc/posts/)
- [The Plumbing Layer: Why Most GIS Teams Stall on Modernization](https://forrest.nyc/the-plumbing-layer-why-most-gis-teams-stall-on-modernization/) - Most GIS teams I work with have already tried to modernize. They have people on Python. Someone is running PostGIS. A few have touched DuckDB or Sedona. And the modernization still stalls. The pattern: tools brought in, then abandoned The pattern is consistent. A new tool gets brought in. Three months later it is abandoned.
- [How to Use Source Cooperative for Cloud-Native Geospatial Data: A Complete Tutorial for QGIS, GeoPandas, DuckDB, PostGIS, and Apache Sedona](https://forrest.nyc/how-to-use-source-cooperative-for-cloud-native-geospatial-data-a-complete-tutorial-for-qgis-geopandas-duckdb-postgis-and-apache-sedona/) - Cloud-native geospatial workflows are finally becoming accessible to everyday GIS analysts. Instead of downloading giant zip files or managing your own S3 buckets, you can now stream geospatial data directly into your tools using modern formats like GeoParquet, COG, and PMTiles. One of the platforms leading this shift is Source Cooperative, a data sharing project
- [AI-Powered Crop Classification with NASA, IBM, and Hugging Face: A Complete Beginner Tutorial](https://forrest.nyc/ai-powered-crop-classification-with-nasa-ibm-and-hugging-face-a-complete-beginner-tutorial/) - Foundation models are changing what’s possible in geospatial analysis. Tasks that once required thousands of labeled samples and expensive GPU training can now be performed instantly using pre-trained models built on massive Earth observation datasets. One of the best examples is the new NASA–IBM Prithvi model, hosted on Hugging Face. It can classify cropland types,
- [The One Skill That Will 10x Your GIS Career (And Why Most Professionals Ignore It)](https://forrest.nyc/the-skill-that-will-10x-your-gis-career-sql/) - If you want to advance your GIS career, earn higher salaries, and work on modern geospatial projects, there is one essential skill you must learn: SQL. Here is why SQL is transforming GIS and how to start mastering it today.
- [Why GIS Jobs Are So Underpaid (And How To Break Out of the Technician Trap)](https://forrest.nyc/why-gis-jobs-are-so-underpaid-and-how-to-break-out-of-the-technician-trap/) - One of the most talked-about issues in geospatial right now is the wide pay gap across GIS roles. You can find entry level jobs paying barely above the U.S. median income right next to roles at the same company paying well into the six figures. This is not just an isolated problem. It is a
- [Is There Still a Future in GIS? A Realistic Look at the Career Path and How to Grow](https://forrest.nyc/gis-career-path-growth/) - Many GIS professionals eventually ask the same question. Is there a long term path for me in this field, and what should I expect from my career going forward? It is a fair question and one I hear constantly from beginners, mid career professionals, and people who have been in GIS for decades. The field
- [Understanding Spatial Data: Vector, Raster, LiDAR, Arrays, and the Modern Geospatial Stack](https://forrest.nyc/spatial-data-vector-raster-lidar-arrays-modern-gis/) - Learn the fundamentals of spatial data, including vector, raster, LiDAR, multidimensional arrays, cloud-optimized formats, and the modern geospatial tools powering today’s analytics. This guide explains how spatial data works and why it matters across industries.
- [How Data Warehouses Power Modern GIS Workflows (And When Not to Use Them)](https://forrest.nyc/data-warehouses-modern-gis-guide/) - Learn how data warehouses like BigQuery, Snowflake, Redshift, and Databricks fit into modern GIS workflows. This guide explains what they do well, where they fall short, and how they compare to tools like PostGIS, DuckDB, and Apache Sedona.
- [GeoParquet Explained: The Cloud-Native Spatial Format Transforming Modern GIS](https://forrest.nyc/geoparquet-guide-modern-gis/) - GeoParquet is quickly becoming the standard for large-scale spatial data. This guide explains how it works, why it matters, when you should and should not use it, and how it fits into the modern GIS and data engineering stack.
- [The Geospatial Index: Why Understanding the Business of GIS Changes Your Career, Your Income, and the Future of Our Industry](https://forrest.nyc/geospatial-index-business-of-gis/) - Understanding the business of geospatial technology is no longer optional. This article breaks down the Geospatial Index, why it matters, and how GIS professionals can use financial insight to shape their careers, income, and long-term impact.
- [GeoAI, Ethics, and the Future of Spatial Intelligence: Inside Geography 2050 with Tee Barr](https://forrest.nyc/geography-2050-geoai-future-of-spatial-intelligence/) - Geography 2050 is putting GeoAI, ethics, climate risk, supply chains, and spatial finance at center stage. In this interview, Tee Barr explains how AI is transforming geospatial analysis and why spatial thinking will be fully integrated into every dataset by 2050.
- [The Future of Mapping Is AI Native: Inside Mapbox’s Vision for Agents, Real-Time Location Intelligence, and Next-Gen Geospatial Apps](https://forrest.nyc/ai-native-mapping-mapbox-kieran-mccann-future-of-location-intelligence/) - Mapbox’s Kieran McCann explains why AI is reshaping mapping, the gap between LLMs and spatial understanding, and how AI native geospatial apps will transform development, navigation, and real-time decision making.
- [The Real State of Geospatial AI: What Foundation Models, Embeddings, and Earth Observation Can (and Can’t) Do Today](https://forrest.nyc/geospatial-ai-foundation-models-embeddings-earth-observation-future/) - A grounded look at the rise of geospatial AI, foundation models, and Earth observation. Learn what’s real, what’s hype, and where innovation in geospatial machine learning is actually happening.
- [Global POI Is Table Stakes: Foot Traffic, Mobility Gaps, and the Trust Layer with Dataplor's Emily Lisle](https://forrest.nyc/global-poi-is-table-stakes-foot-traffic-mobility-gaps-and-the-trust-layer-with-dataplors-emily-lisle/) - A market analyst pulls a Starbucks foot traffic report. The numbers look fine. The store-by-store breakdown is clean. The chart is presentable. Then someone asks how the brand is performing in Mexico, and the report has nothing to say. You were looking at about half the company. In episode 45 of The Spatial Stack, I
- [A5 and the Future of Global Grids: Why Pentagons May Redefine Spatial Indexing](https://forrest.nyc/a5-global-grid-system-equal-area-pentagons/) - Every decade or so, a new idea emerges that quietly shifts the entire trajectory of geospatial technology. H3 did that for the 2010s. S2 did it before that. But today, we’re looking at something entirely new. In a conversation with Felix Palmer, creator of A5, I realized just how much latent innovation still exists in
- [The Future of Geospatial Is Bigger Than Geospatial](https://forrest.nyc/future-of-geospatial-beyond-geo/) - Every so often, an insight lands that shakes the foundation of how an entire field sees itself. During my conversation with Nadine Alameh, one line did exactly that: “Stop introducing yourself as a geospatial person.” Not because geospatial isn’t important. But because we’ve unintentionally built walls around a discipline that powers almost everything people do
- [Edge Computing in Space: How Novi Is Rewriting the Economics of Earth Observation](https://forrest.nyc/edge-computing-in-space-novi-earth-observation/) - Edge computing in space is transforming Earth observation. Learn how Novi’s smart satellites cut costs by orders of magnitude, deliver real-time insights, and open new markets across agriculture, defense, maritime, and more.
- [How Open Source BI Is Transforming Geospatial Analytics: Lessons from Superset and Preset](https://forrest.nyc/how-open-source-bi-is-transforming-geospatial-analytics-lessons-from-superset-and-preset/) - If you work in GIS long enough, you eventually discover a major tension in the field. Most geospatial tools evolved in their own universe, built around desktop workflows and specialized formats. At the same time, the modern data stack has exploded, bringing enormous advances in cloud computing, real-time processing, SQL analytics, and open source engineering.
- [The Spatial SQL Landscape in 2026: A Guide to 50+ Databases](https://forrest.nyc/best-spatial-sql-tools/) - Navigate the 2026 Spatial SQL landscape. This guide categorizes 50+ databases (PostGIS, DuckDB, Sedona) into 6 architectures to help you choose the right tool.
- [From Static Maps to Living Systems: How TomTom & Overture are Redefining Geospatial Intelligence](https://forrest.nyc/ai-mapping-tomtom-overture-geospatial-future/) - Explore the shift from static navigation to AI-powered "living maps." Learn how the Overture Maps Foundation, TomTom, and predictive AI are creating a real-time global operating system for defense, tech, and humanitarian response.
- [Apache Sedona vs. Big Data: Solving the Geospatial Scale Problem](https://forrest.nyc/apache-sedona-geospatial-big-data/) - Discover how Apache Sedona optimizes geospatial data processing at scale. Learn about distributed spatial partitioning, Spatial SQL, and the future of the Spatial Lakehouse.
- [Learn Geospatial Python with GeoPandas: A Complete Beginner’s Guide](https://forrest.nyc/learn-geospatial-python-geopandas/) - Working with geospatial data used to require specialized desktop software. Today you can do almost everything directly in Python with open-source libraries. At the center of that ecosystem is GeoPandas, the foundational tool for handling vector data in Python. If you’re just getting started with geospatial Python, or you want a practical walkthrough you can
- [Beyond Latitude & Longitude: A Guide to H3, S2, and Discrete Global Grid Systems](https://forrest.nyc/discrete-global-grid-systems-h3-s2-vs-lat-long/) - Stop relying on raw coordinates. Learn how Discrete Global Grid Systems (DGGS) like H3, S2, and A5 speed up spatial analysis, improve visualization, and scale your geospatial data.
- [Imposter Syndrome in GIS: Why You Feel It (and How to Move Through It)](https://forrest.nyc/imposter-syndrome-in-gis/) - Imposter syndrome is common in GIS and tech. Learn why it happens, how to move through it, and why you don’t need a specific degree, certification, or permission to build a successful career in modern geospatial.
- [Should You Get a GISP? A Practical, Honest Guide for GIS Professionals](https://forrest.nyc/should-you-get-a-gisp/) - Thinking about getting your GISP certification? This guide breaks down what the GISP is, how the exam works, the benefits, the drawbacks, and whether it will actually help your GIS career.
- [Why We Have Billions in Flood Data (But You Still Can’t Find It)](https://forrest.nyc/why-we-have-billions-in-flood-data-but-you-still-cant-find-it/) - At a minimum, you should be able to look at a map and know if you are standing in a flood zone. It sounds simple. We have spent billions of tax dollars scanning the entire surface of the United States down to centimeter accuracy. We have thousands of stream gauges monitoring water levels every 15
- [Choosing the Right Query Engine for Cloud-Native Geospatial Analytics](https://forrest.nyc/choosing-the-right-query-engine-for-cloud-native-geospatial-analytics/) - Learn how to choose the right query engine for cloud-native geospatial analytics. Compare DuckDB, BigQuery, Snowflake, Databricks, and more to power the analytics layer of your spatial data lakehouse.
- [Stuck in Legacy GIS? A Practical Roadmap to Modern GIS and Cloud Native Geospatial](https://forrest.nyc/stuck-in-legacy-gis-a-practical-roadmap-to-modern-gis-and-cloud-native-geospatial/) - I get this question almost every day. “I feel stuck in legacy GIS, and I want to update my skills, but I don’t know where to start.” It does not matter if your goal is to keep up with the field, hit the next career milestone, or ship a project that feels out of reach.
- [Why Your GIS Career Feels Stuck (And How to Break Through)](https://forrest.nyc/why-your-gis-career-feels-stuck/) - Feeling stuck in your GIS career? Learn the three reasons geospatial professionals stop advancing and how to shift from technical tasks to high-value impact using positioning, specialization, and modern GIS skills.
- [What Is QGIS? The Open-Source Platform Powering Modern GIS](https://forrest.nyc/what-is-qgis-open-source-modern-gis/) - Learn what QGIS is, how it works, and why it’s the open-source platform powering modern GIS. Explore its strengths, weaknesses, plugins, and how it connects to tools like PostGIS, DuckDB, and the cloud.
- [What Is PostGIS? The Open-Source Spatial Database Powering Modern GIS and AI](https://forrest.nyc/what-is-postgis-the-open-source-spatial-database-powering-modern-gis-and-ai/) - Learn what PostGIS is, how it works, and why it’s powering the next generation of modern GIS and AI. Discover how this open-source spatial database extends PostgreSQL to handle geospatial data at scale.
- [From Leafmap to GeoAI: How Dr. Qiusheng Wu Is Transforming Open Source GIS and Geospatial Education](https://forrest.nyc/from-leafmap-to-geoai-how-dr-qiusheng-wu-is-transforming-open-source-gis-and-geospatial-education/) - When most people think of relaxing, they picture a walk, a movie, or a quiet evening. For Dr. Qiusheng Wu, relaxation means writing code. As he puts it, “When I have free time, when I’m relaxing, I’m coding. If you’ve ever used Leafmap, explored GeoAI, or watched one of his tutorials on YouTube, you already
- [SedonaDB vs DuckDB vs PostGIS: Which spatial SQL engine is fastest?](https://forrest.nyc/sedonadb-vs-duckdb-vs-postgis-which-spatial-sql-engine-is-fastest/) - Last week the team from Apache Sedona released SedonaDB, a new tool that makes spatial processing fast and also treats spatial data like a first class citizen. Or read a different way it is really fast for doing spatial analytics. It uses Python and SQL to analyze data and can also output data in GeoParquet
- [Spatial Data Lakehouse Architecture: Beyond H3 and Vector-Only Data](https://forrest.nyc/spatial-data-lakehouse-architecture/) - Storage and formats are the foundation. Pipelines make them practical. But storage and processing architectures determine what's actually possible at scale. We've talked about cloud storage enabling modern geospatial workflows and the formats that make data queryable. We've covered the pipelines that get your data into those formats. But there's a bigger architectural question that
- [The Modern Geospatial Data Stack: Trends, Tools, and What They Mean for You](https://forrest.nyc/the-modern-geospatial-data-stack-trends-tools-and-what-they-mean-for-you/) - The geospatial technology landscape is changing fast. What used to be a world of shapefiles, desktop software, and siloed workflows is now becoming cloud-native, AI-driven, and analytics-focused. This shift isn’t just technical—it’s reshaping how geospatial professionals build, analyze, and share data. In this post, I’ll break down the key trends shaping the modern geospatial data
- [Why your spatial pipelines are probably broken (And how Airflow can help)](https://forrest.nyc/airflow/) - In the world of spatial data, building pipelines often feels like duct-taping together cron jobs, brittle scripts, and whatever cloud service happens to be in reach. Whether you’re transforming geospatial imagery, generating features for machine learning, or managing time-sensitive datasets like weather and river gauges chances are, your pipelines could use an upgrade. In the
- [Geospatial Data Pipeline Management: Modern approaches vs traditional methods](https://forrest.nyc/geospatial-data-pipeline-management-modern-approaches-vs-traditional-methods/) - Having the right formats is one thing. Getting your data into those formats reliably, at scale, and on schedule is another thing entirely. You can read all you want about GeoParquet and Zarr and COG, but if you can't create a repeatable process to convert your legacy shapefiles to GeoParquet or your NetCDF files to
- [Esri vs Open Source GIS: The Real Debate Behind the Tools](https://forrest.nyc/esri-vs-open-source-gis-the-real-debate-behind-the-tools/) - It started the way most online debates do: with a LinkedIn post and a strong opinion. I’d shared a graphic about modern GIS tools, highlighting open-source workflows and cloud-based options I believe help push the industry forward. Kyle Satterfield, GISP, had a different take. He took my graphic, dropped it into ChatGPT, and asked it
- [Cloud Native Geospatial Formats: GeoParquet, Zarr, COG, and PMTiles Explained](https://forrest.nyc/cloud-native-geospatial-formats-geoparquet-zarr-cog-and-pmtiles-explained/) - Storage is the foundation, but formats are what make cloud-native geospatial actually work. You can put any file in cloud storage. A shapefile, a GeoTIFF, a KML file, whatever. But just because it’s in the cloud doesn’t mean it’s cloud-native. And there’s a big difference between the two. Cloud-native formats are designed from the ground
- [Airflow + AI + Iceberg V3: The New Stack for Scalable Geospatial Data](https://forrest.nyc/airflow-ai-iceberg-v3-the-new-stack-for-scalable-geospatial-data/) - TOP OF THE STACK Recently I have talked about Airflow, and I have talked about Agentic AI, but not the two together. Well with the release of the Airflow AI SDK from Astronomer you can now do both, together. Check out this video from The Data Guy (aka George Yates) about this functionality. Take a look and let me know
- [Breaking the GIS Silo: Why GeoParquet and Iceberg are the key to Spatial Analytics at Scale](https://forrest.nyc/breaking-the-gis-silo-why-geoparquet-and-iceberg-are-the-key-to-spatial-analytics-at-scale/) - For decades, GIS has lived in a world of its own. Specialized software. Obscure formats. A profession that, despite being critical to everything from climate modeling to logistics, has remained siloed from the rest of the data world. But that’s finally starting to change. In the latest episode of the Spatial Stack podcast, I sat
- [How to Build a Cloud-Native Spatial Data Lakehouse](https://forrest.nyc/how-to-build-a-cloud-native-spatial-data-lakehouse/) - Most spatial workflows today are still running on a foundation of folders, flat files, and fragile scripts. You’ve probably worked with shapefiles stored in six different places, Python notebooks that quietly break when a column changes, and a dozen versions of the same dataset ending in _final_v2_edit.shp. I’ve been there. But spatial data has changed.
- [How Cloud Storage Powers Cloud-Native Geospatial, AI, and Analytics](https://forrest.nyc/how-cloud-storage-powers-cloud-native-geospatial-ai-and-analytics/) - Look we can throw around a lot of terms about cloud-native and how geospatial is moving to the cloud, but none of this happens if it isn’t for cloud storage. Yes, this post is going to talk about storage. It’s one of the fundamentally more vanilla topics when discussion the cloud. When you boil it
- [Apache Sedona Tutorial: Scalable Spatial Joins and Geospatial Processing with Spark](https://forrest.nyc/apache-sedona-tutorial-scalable-spatial-joins-and-geospatial-processing-with-spark/) - If you’ve ever tried to run a spatial join on millions of features and watched your machine cry for help, it’s time to level up with Apache Sedona. In this new video, I walk through a complete hands-on tutorial for using Sedona in Python via JupyterLab. We’ll load spatial data, perform scalable spatial operations, and
- [Get Featured in the 2025 Geospatial Landscape Report (Submit Your Company Today)](https://forrest.nyc/geo-2025/) - The geospatial industry is evolving faster than ever: from AI-powered analytics to cloud-native infrastructures reshaping how we work with spatial data. That’s why I am excited to announce that the 2025 Geospatial Landscape is on the horizon. The response to this piece last year was amazing and I am excited to start work on the
- [BigQuery vs. Wherobots: What a 23-Second Difference in Spatial SQL Really Reveals](https://forrest.nyc/bigquery-vs-wherobots-what-a-23-second-difference-in-spatial-sql-really-reveals/) - The Real Story Behind Faster Spatial Queries I've been in geospatial long enough to know that performance metrics can be deceptive. When I recently ran a query to enrich drive-time isochrones with population data—something that's geometry-heavy and computation-intensive—I got results from two powerful engines: Wherobots and BigQuery. Wherobots returned results in 57 seconds.BigQuery took 1
- [Why Cloud-Native Geospatial Data Is Making "Spatial" Just Data Again](https://forrest.nyc/why-cloud-native-geospatial-data-is-making-spatial-just-data-again/) - Every once in a while, a conversation topic starts surfacing repeatedly, unprompted, from completely different directions. This week, for me, that topic was cloud-native geospatial data. Seven conversations in 24 hours. All roads leading to the same challenge: geospatial data is abundant but remains frustratingly difficult to use. What struck me wasn’t just the volume
- [Why Cloud-Native Geospatial Is the Future of GIS (And What Comes Next)](https://forrest.nyc/why-cloud-native-geospatial-is-the-future-of-gis-and-what-comes-next/) - For decades, working in GIS meant downloading massive datasets, struggling with storage limits, and figuring out how to make sense of it all locally. I remember those early days clearly—each download felt like a commitment, and each analysis came with its own compromise. We got used to it. But looking back, that entire process feels
- [How Placekey Is Revolutionizing Spatial Joins and Entity Resolution](https://forrest.nyc/how-placekey-is-revolutionizing-spatial-joins-and-entity-resolution/) - If you've ever tried to merge location data from different sources, you've probably run into the same nightmare I have: mismatched formats, duplicate addresses, missing POIs, and enough edge cases to make your head spin. This is why I was excited to sit down with Hayden Mortimer, president of Placekey, on the latest episode of
- [The Future of Spatial Stack: Why I’m doubling down on the conversations that matters most in geospatial](https://forrest.nyc/the-future-of-spatial-stack-why-im-doubling-down-on-the-conversations-that-matters-most-in-geospatial/) - Over the last few months, I’ve had a chance to step back and ask a simple but vital question: what do I actually want the Spatial Stack to be? Not just the podcast. Not just a channel. But the broader movement it’s becoming. I’ve been fortunate to spend the last year at the intersection of
- [What the Modern Data Stack can teach us about the future of geospatial](https://forrest.nyc/what-the-modern-data-stack-can-teach-us-about-the-future-of-geospatial/) - There are a few truths you can always count on in geospatial. Something is always changing. There’s always a new way to do something. Spatial is special. Spatial data needs to be democratized. Spatial data is in a silo. Spatial data is a second class citizen. I have heard so many of these over the
- [The Role of Geospatial Data in AI, LLMs, and the Next Wave of Tech Innovation](https://forrest.nyc/the-role-of-geospatial-data-in-ai-llms-and-the-next-wave-of-tech-innovation/) - Get the Audio Podcast on every platform here When people talk about AI, the focus is usually on large language models, GPU power, or the next wave of multimodal capabilities. But there's a quietly growing field that could be just as important: geospatial technology. In the latest episode of the podcast, I sat down with
- [Upload, Visualize, and Share Map Tiles in Seconds](https://forrest.nyc/upload-visualize-and-share-map-tiles-in-seconds/) - This issue is presented by MapHub TOP OF THE STACK Two quick datasets for mobile phone and data coverage. This data has always been hard to get your hands on but (at least for the US) I came across these shapefiles (they appear to be vectorized rasters) for LTE coverage for data and voice for the big providers: T-Mobile, AT&T,
- [How to Run Scalable Geospatial Analysis with Apache Sedona - Right From Your Laptop](https://forrest.nyc/how-to-run-scalable-geospatial-analysis-with-apache-sedona-right-from-your-laptop/) - I spend a lot of time talking about scaling geospatial analysis—massive datasets, remote sensing archives, distributed computation—but sometimes the best way to start is right from your laptop. In this tutorial, we’ll set up a local Apache Spark environment using Apache Sedona, a powerful extension for scalable geospatial processing. We’ll connect to remote cloud-hosted data,
- [Geospatial Tools Compared: When to Use GeoPandas, PostGIS, DuckDB, Apache Sedona, and Wherobots](https://forrest.nyc/geospatial-tools-compared-when-to-use-geopandas-postgis-duckdb-apache-sedona-and-wherobots/) - Geospatial data can be stored and analyzed using a variety of tools, databases, query engines, and frameworks. Choosing the right tool depends on the scale of your use case, from individual exploration on a laptop to enterprise-level deployments, and each technology has a point where its benefits taper off. The good news for you is
- [Scaling GIS Workflows with COGs, Airflow, and Apache Iceberg](https://forrest.nyc/scaling-gis-workflows-with-cogs-airflow-and-apache-iceberg/) - TOP OF THE STACK What we need to do with COGs COGs (Cloud-Optimized GeoTIFFs) are one of the most promising tools we have for making raster data truly cloud-native. They let you stream just the pieces you need, work remotely, and plug into modern geospatial systems without downloading giant files. But after working closely with
- [Spatial Joins: A comprehensive guide](https://forrest.nyc/spatial-joins-a-comprehensive-guide/) - Spatial joins combine data based on location instead of a common key. In a spatial join, attributes from one dataset are attached to another by evaluating how their geometries relate in space. For example, you could join a list of customer coordinates to sales territories by finding which territory polygon contains each customer point. This
- [The Top Geospatial Python Packages: What’s Driving Their Growth?](https://forrest.nyc/the-top-geospatial-python-packages-whats-driving-their-growth/) - Geospatial Python has seen an explosion in adoption, with several key libraries surpassing 10 million downloads this year. As geospatial analysis becomes increasingly critical in data science, urban planning, environmental monitoring, and AI applications, understanding why these libraries are growing can provide insight into where the industry is heading. Here’s a breakdown of the most
- [What is Modern GIS?](https://forrest.nyc/what-is-modern-gis/) - The GIS we use and practice today is fundamentally different from the GIS we used previously. In the past, I have written about the need to define geospatial as a practice, and yet again I think it is time to define another term in our space. Modern GIS is something that is starting to take
- [75+ Geospatial Python and Spatial Data Science Resources and Guides](https://forrest.nyc/75-geospatial-python-and-spatial-data-science-resources-and-guides/) - The growth of Python for geospatial has been nothing short of explosive over the past few years. More and more you find that geospatial processes are being developed and run on Python, and new users of geospatial are riding their way into geospatial because of it. How can I get started? The next step is
- [The 37 Geospatial Python Packages You Definitely Need](https://forrest.nyc/the-37-geospatial-python-packages-you-definitely-need/) - When performing geospatial analysis, the right set of tools can be the difference between surface-level insights and deep, actionable intelligence. Fortunately, amazing geospatial Python packages help to bridge this gap. Python, renowned for its versatility and robustness, offers a wide range of packages that can not only help you scale your spatial analysis, but reach
- [PostGIS and QGIS in 4 minutes](https://forrest.nyc/postgis-and-qgis-in-4-minutes/) - QGIS provides an excellent interface to get started with PostGIS, and (if you are a Mac user) you can start with PostGIS using Postgres.app very fast! Check out the video and follow along using this guide. Download and install Postgres.app First, head over to this site to download and install Postgres.app. This is a complete
- [40+ Spatial SQL Resources and Guides](https://forrest.nyc/40-spatial-sql-resources-and-guides/) - One of the top questions I get asked is what my favorite resources are for learning any given topic, and spatial SQL is always near the top of that list It’s no secret that I am a big fan of spatial SQL (see my past posts on the topic). It’s speed, scale, and ability to
- [Learn Geospatial Python with these top courses](https://forrest.nyc/geospatial-python-courses/) - Python is fast becoming one of the top languages for data analysis and data science, and for good reason. It is quick to learn, can be used for many use cases, and is fast becoming a key skill for job seekers. Python for GIS and geospatial analysis is no different. It can help you scale
- [From Desktop GIS to Cloud: A Beginner's Roadmap to Modern GIS Tool](https://forrest.nyc/from-desktop-gis-to-cloud-a-beginners-roadmap-to-modern-gis-tool/) - Modern GIS is changing fast. If you’ve been working with QGIS, ArcGIS, or any other desktop GIS tool, you’ve probably hit some limitations—datasets getting too big, processing times slowing down, and collaboration becoming a challenge. The good news? The cloud offers a way forward. But how do you make that transition? How do you go
- [Why the geospatial industry is stuck (and how we can fix it together)](https://forrest.nyc/why-the-geospatial-industry-is-stuck-and-how-we-can-fix-it-together/) - I want to set the scene that may seem odd at first, but it will help explain this post as we go along. Transport yourself back to a bustling school cafeteria at lunchtime. The room hums with chatter as students gather around their tables, each unpacking their lunch. Some have crisp apple slices and hearty
- [Why spatial thinking still matters (or why I got it wrong 😟)](https://forrest.nyc/why-spatial-thinking-still-matters-or-why-i-got-it-wrong-😟/) - In a recent post (see below), I emphasized Python, SQL, and Cloud as core skills for GIS professionals today. Yes I still think these are critical skills but there is one thing I would fix about how I positioned that. ​However, some pointed out that I seemed to overlook the fundamentals: spatial thinking, methodologies, and
- [🛰️ Introducing "Signals from the Surface" & Valencia Flooding](https://forrest.nyc/🛰️-introducing-signals-from-the-surface-valencia-flooding/) - A few months ago I got a message from the person I will shortly introduce on LinkedIn. The idea was simple (and one that I had been interested in working on) - partner up to share more resources to the geospatial community on the overlap between geospatial and earth observation. Now for me EO is
- [🚫 Hype vs. reality: The big data debate in geospatial](https://forrest.nyc/🚫-hype-vs-reality-the-big-data-debate-in-geospatial/) - Was big data in GIS ever a thing? When we talk about big data in geospatial and GIS, it tends to open up quite the debate. On one hand, you have the promise of detailed insights and the ability to understand our world in ways we’ve never imagined. On the other, there’s the stark reality
- [🤨 Is Esri finally catching up?](https://forrest.nyc/🤨-is-esri-finally-catching-up/) - Esri’s integration of DuckDB hints at modern GIS progress, but is it enough to shed its legacy systems?
- [😢 The hard truth about learning GIS and programming (and how I did it)](https://forrest.nyc/😢-the-hard-truth-about-learning-gis-and-programming-and-how-i-did-it/) - Here are the two questions I get asked most often by people online or at events: How do you have the time to create so much content?(Short answer: organization in Notion; long answer: 🤷🏼) How did you learn all these different tools? Here’s the unfiltered and direct answer to the second question: it took almost
- [80% of all data is spatial? (is this really true)](https://forrest.nyc/80-of-all-data-is-spatial-is-this-really-true/) - By the numbers 80% of all data has a spatial component (I am sure you have heard it) 78% of articles have a georeferenced component (“How much information is geospatially referenced? Networks and cognition.” 2012) Modern GIS with Matt Forrest is a reader-supported publication. To receive new posts and support my work, consider becoming a
- [Why the open source vs. traditional GIS debate needs to stop](https://forrest.nyc/why-the-open-source-vs-traditional-gis-debate-needs-to-stop/) - This is a video that I have been thinking about making for some time and the topic itself is one that has resonated with me for years. I sort of steered away from it since the topic itself can be a bit contentious, for both the open-source and traditional GIS community. But it is the
- [Modern GIS is way more than Web GIS](https://forrest.nyc/modern-gis-is-way-more-than-web-gis/) - Look I have been talking about modern GIS for about three years now (a full three if you count this post). And the adoption of the term has grown significantly since my first full article on the topic in January 2022: But in the past year or so something caught my eye from a specific company that says
- ["Atomic Habits" for learning modern GIS](https://forrest.nyc/atomic-habits-for-learning-modern-gis/) - In the last few weeks I have been reading (or rather listening) to Atomic Habits by James Clear. While I am certainly not productivity obsessed or focused on rigid habits, I do always look to optimize the way I work. For me there are a lot of things I want to do, and I want
- [🐍 The 7 things I wish I knew about Python before learning Python](https://forrest.nyc/🐍-the-7-things-i-wish-i-knew-about-python-before-learning-python/) - It’s more than likely that Python is going to become a fundamental skill in all areas in the coming years, just as Excel did in previous decades. Its applications across many domains and ability to automate processes make it one of the most popular languages today. But in GIS, we already know that. For years,
- [Why I joined Wherobots](https://forrest.nyc/why-i-joined-wherobots/) - This past week, I started a new path in my career for the first time in 9 years over with the amazing team at Wherobots. There are a number of reasons why I am excited to join (the technology reasons will be explained below) but the first is the amazing team members I met this
- [The 3 critical skills you need for modern GIS (that aren’t Python or SQL)](https://forrest.nyc/the-3-critical-skills-you-need-for-modern-gis-that-arent-python-or-sql/) - In GIS we love to collect skills like sports collectors chasing the 2009-10 Panini National Treasures Stephen Curry Logoman Autograph Rookie Card. I admit to this as well, both falling victim to this as well as focusing a lot of content on this as well. (By the way, the Spatial Lab, my new membership community, is
- [No, 80% of data isn’t spatial (and why that is a good thing)](https://forrest.nyc/no-80-of-data-isnt-spatial-and-why-that-is-a-good-thing/) - Earlier this year I wrote a post which addressed the ubiquitous phrase in the geospatial industry that 80% of data contains a spatial component. The problem with this statement is that there is no single source where this stat line came from, even though it has been used widely for years. Some have tried to track this down, but I
- [2 reasons why GIS jobs pay $19,049 less](https://forrest.nyc/2-reasons-why-gis-jobs-pay-19049-less/) - Out of all the things I love about the geospatial and GIS industries, there are two that I have always taken issue with. The first is that more technical skills are not always taught in GIS, and if they are they require going back for a certificate or masters program (the only reason I am
- [I want to change the way we learn geospatial in the next 6 months](https://forrest.nyc/i-want-to-change-the-way-we-learn-geospatial-in-the-next-6-months/) - First off, thank you and welcome. This is my new consolidated newsletter that I’ll be sharing on a regular basis called Spatial Stack. After a semi-productive first half of the year, I took a look at what my goals are and decided to refocus around one simple idea: maximizing how I can help others learn
- [The Top 11 Open GeoParquet Datasets: Making big geospatial data easy](https://forrest.nyc/the-top-11-open-geoparquet-datasets-making-big-geospatial-data-easy/) - In the dynamic field of geospatial technology, the evolution of data formats plays a pivotal role in shaping how we interact with and interpret spatial information. The advent of GeoParquet has marked a significant milestone, offering a more efficient and accessible way to handle large spatial datasets. This blog post delves into a comprehensive exploration
- [Mastering Spatial SQL: The Ultimate Guide to Tools & Databases in 2024](https://forrest.nyc/mastering-spatial-sql-the-ultimate-guide-to-tools-databases-in-2024/) - The Evolving Landscape of Spatial SQL In today's technologically driven world, the use of spatial SQL in databases and data warehouses has become increasingly significant. This growth not only enriches the database management landscape but also simplifies the learning curve for professionals, allowing them to apply their expertise across various tools. This blog post delves
- [The case for using spatial SQL](https://forrest.nyc/the-case-for-using-spatial-sql/) - Why spatial SQL matters and how it can help you accelerate your GIS and geospatial workflows Originally published on Towards Data Science in June 2021 It was the spring of 2012 and I just had my first encounter with a SQL query. I had just moved to New York at the end of 2011 and
- [What is spatial SQL?](https://forrest.nyc/what-is-spatial-sql/) - Spatial SQL is not just a query language. It is becoming far more than that and its uses are expanding beyond just a database for spatial data. It allows for faster spatial analysis, supports spatial applications, enables spatial data science and machine learning, and far more. Because of these reasons I wanted to share a
- [PostGIS and GeoPandas in Jupyter in 4 minutes](https://forrest.nyc/postgis-and-geopandas-in-jupyter-in-4-minutes/) - Take advantage of the speed of PostGIS along with the flexibility of Geopandas and Python in 4 minutes! Take a look at the video and follow along with these steps! First, install your libaries You will need to install Geopandas and psycopg2 (you can also use SQLAlchemy) in your Jupyter notebook environment. If you are
- [Spatial SQL Cookbook: Common GIS Analyses in Spatial SQL](https://forrest.nyc/spatial-sql-cookbook/) - One of the biggest challenges, at least for me, when getting started with spatial SQL is having a quick and easy reference to transfer your current GIS workflows into SQL. There are many amazing resources out there to expand this knowledge, but this guide is meant to be a really simple cookbook to start to
- [SQL Basics for Spatial SQL: Importing Data to PostGIS](https://forrest.nyc/sql-basics-for-spatial-sql-importing-data-to-postgis/) - If you are looking for help loading a variety of geospatial data into PostGIS, then you have landed in the right place. This is a guide for my video below with further tutorials and guides. Special shout out to the team at Crunchy Data for their fantastic post on the topic. shp2pgsql This is a
- [Top Modern GIS Skills for Spatial Data Science in 2022](https://forrest.nyc/top-modern-gis-skills-for-spatial-data-science-in-2022/) - Spatial data science has been one of the fastest-growing career paths in modern GIS in the past few years. The combination of the boom in the data science path, proliferation and popularity of Python, and demand for more flexible/technical roles in data science and analytics have spilled over into modern GIS. Yet spatial data science
- [GeoParquet will be the most important tool in modern GIS in 2022](https://forrest.nyc/geoparquet-will-be-the-most-important-tool-in-modern-gis-in-2022/) - Yes, (another) file format is the most important new development tool for the modern GIS stack in 2022. There is a ton of hype around tools, processes, and methods for making geospatial analysis faster and at scale, but what if the data (in this case vector data) was better formatted for different query performance both
- [Spatial SQL for GIS and Geospatial: Basic SQL](https://forrest.nyc/spatial-sql-for-gis-and-geospatial-basic-sql/) - Welcome to the first in a series of videos and posts on learning spatial SQL. This will focus on learning the core elements of SQL, and in the name of not reinventing the wheel, there are already such great resources to learn SQL. What you need to know Here are some of the top things
- [Building your spatial SQL toolkit](https://forrest.nyc/building-your-spatial-sql-toolkit/) - There are a ton of different ways to work with spatial SQL, but there are three different elements of every spatial SQL setup: The database or data warehouse The access method The visualization layer The database or data warehouse Below are some of the options that I covered in the video to create your spatial
- [A Brief History of Web Maps](https://forrest.nyc/a-brief-history-of-web-maps/) - Or how a Flemish cartographer and PNGs made web maps a part of our everyday lives Originally published on Towards Data Science in May 2020 When was the last time you were lost? Really think about it. Unless you didn’t have a phone or yours ran out of power, you likely had directions telling you where
- [How to get started with spatial SQL](https://forrest.nyc/getting-started-with-spatial-sql-part-1-the-basics/) - Mastering SQL fundamentals to get started with spatial SQL So you are interested in getting started with spatial SQL — that’s great! Getting started can seem overwhelming but in this post and others, I hope to take you through the different use cases for spatial SQL bit by bit. One of the biggest challenges if you are working
- [Join all the things in spatial SQL](https://forrest.nyc/join-all-the-things-in-spatial-sql/) - In this post, we will take a look at joining data in SQL. We will take a quick look at joining data in SQL generally, and then how to perform spatial joins using spatial relationships. Let’s take a look at the answers to the challenges from the previous post If you are following along, in
- [Geospatial needs to be defined](https://forrest.nyc/geospatial-needs-to-be-defined/) - If you know, you know. That is a very short way of saying that “geospatial” lacks definition. In the past few years, and more so recently, I have seen more and more people who state that they work “in geospatial” or are “doing geospatial”, alongside a rise in many different job titles that have the
- [Geospatial can’t solve the current supply chain crunch - but it can help make it more resilient going forward](https://forrest.nyc/geospatial-cant-solve-the-current-supply-chain-crunch/) - Around the world, the current supply chain disruptions and backlog are being felt by companies and consumers alike across a wide range of products and categories. This article from the Washington Post shows the view of the Port of Los Angeles and the developing backlog of ships from satellite imagery. As a result, people working
- [Get started with Python and GeoPandas in 3 minutes](https://forrest.nyc/get-started-with-python-and-geopandas-in-3-minutes/) - Looking to get started with geospatial Python and GeoPandas! Below you can find the step-by-step instructions to go along with the following video to get you up and running with GeoPandas in no time at all. First, open Google Colab First, head over to Google Colab and get started by creating a new notebook. Google
- [Top Modern GIS Skils for GIS Analysts in 2022](https://forrest.nyc/top-modern-gis-for-gis-analysts-in-2022/) - GIS Analysts serve the incredibly important purpose of providing detailed analysis and flexible results working with a wide range of data and tools. Not only do GIS Analysts work with many different stakeholder groups, but they also have to maintain a flexible workflow and use a wide range of data, delivering easy to use and
- [SQL Basics for Spatial SQL: Basic Query Structure](https://forrest.nyc/spatial-sql-basic-query-structure/) - This post serves as the guide for the first video in the Learn Spatial SQL series, focusing on SQL Basics for Spatial SQL, specifically Basic Query Structure: SELECT SELECT provides the basic query structure to return data from a table. This is the most foundational query structure in SQL when returning data from a table.
- [Cloud-native GIS - what is the actual definition?](https://forrest.nyc/cloud-native-gis/) - Lately, I have been discussing the concept of modern GIS, and while it doesn’t require the cloud to run (in fact a core principle is that it can be run locally or in the cloud) it does allow you to easily move to the cloud when ready. With that said not all things in the
- [Load geospatial data to Redshift, BigQuery, Snowflake, and PostGIS: The complete guide](https://forrest.nyc/load-geospatial-data-to-redshift-bigquery-snowflake-and-postgis-the-complete-guide/) - Getting started with spatial SQL will always require one key step where many hit a roadblock - importing data into your spatial database. In a traditional GIS setting, this is as simple as dragging or dropping a file or simply clicking to load it. For databases and data warehouses, this requires a few more steps
- [Tapping into the power of spatial SQL aggregations](https://forrest.nyc/tapping-into-the-power-of-spatial-sql-aggregations/) - Use aggregations in SQL to group your data and perform large scale spatial joins Picking up where we left off from our last tutorial, we will jump right into the next set of topics: Using the WHERE clause to do more advanced filtering of your dataAggregations by grouping your data, filtering aggregated data using HAVING,
- [Stop Using Zip Codes for Geospatial Analysis](https://forrest.nyc/stop-using-zip-codes-for-geospatial-analysis/) - Originally published on CARTO and Towards Data Science in August 2019 The last time you used your zip code, you were most likely entering your address into a website to make a purchase, finding a store near your home or office, or filling out some other online form. You likely found the answer you were
- [What do you get from sharing your location data?](https://forrest.nyc/what-do-you-get-from-sharing-your-location-data/) - You are sharing your location all the time. What do you get in return for the data you share? Knowingly or not, you are sharing your location. Your mobile device sends out your current location, multiple times a day, to companies that collect that information from apps on your phone. You may not have thought twice

## Pages

- [Modern GIS Training & Career Resources | Matt Forrest](https://forrest.nyc/) - Build a geospatial career that can't be automated. Twice a week I send essays, tools, and teardowns that bridge traditional GIS and the modern data stack. Python. Spatial SQL. Cloud-native pipelines. The work that actually pays. Trusted by 184,339 geospatial pros. Free. No fluff. Featured in / partnered with Wherobots LinkedIn Learning Mapbox Apache Sedona
- [Sponsor — Reach 195K+ Modern GIS Pros | Matt Forrest](https://forrest.nyc/sponsor/) - Sponsor & Partner Reach the people building modern GIS. Practitioners, architects, and leaders working at the intersection of GIS, data engineering, and AI. Companies use my channels to introduce tools, win mindshare, and shape how the industry thinks about modern geospatial. Start a conversation See the audience Currently booking Q3 & Q4 2026 partnerships Combined
- [Sponsor and Partner with Matt](https://forrest.nyc/sponsor-old/) - Partner with the modern geospatial community Reach practitioners, architects, and leaders working at the intersection of GIS, data engineering, and AI. 121,000+ geospatial experts across all platforms Why Partner? Reach the leaders shaping the future of geospatial I work with companies and leadership building the tools, platforms, and infrastructure powering modern GIS, spatial analytics, earth
- [The Spatial Lab | The Career Accelerator for Modern Geospatial Professionals](https://forrest.nyc/spatial-lab-feb-2026/) - Stop just making maps. Start building systems. The Spatial Lab is the only accelerator designed to take you from Desktop GIS to Cloud-Native Spatial Architect. Master Python, SQL, and Strategy.
- [Geospatial Career Accelerator: Become a Spatial Architect](https://forrest.nyc/coaching/) - ✦ Escape The Technician Trap You are one step away from your dream role. The only program that combines a 12-week modern technical accelerator with 12 months of direct, personal mentorship from Matt. 2 spots available Change Your Career The Skills Trap Why more tutorials aren't getting you promoted. You’ve done the work. You
- [Matt Forrest - Modern GIS and Geospatial](https://forrest.nyc/home-ai-software/) - Build a career that can't be automated. I help geospatial professionals bridge the gap between traditional GIS and the modern data stack to build high-impact, future-proof careers. Join 115,484+ geospatial experts growing in modern GIS and geospatial every day. Most Popular Welcome to modern GIS My most popular tools and courses. Not sure what is
- [The MGx Program](https://forrest.nyc/mgx/) - Go From GIS Analyst to Spatial Architect in 12 Weeks Build a portfolio of modern spatial system blueprints and pipelines, then get 12 months of coaching and support to turn that portfolio into your next role. MGx is a career accelerator for GIS professionals who want to design how spatial data is stored, processed, and
- [Modern GIS Accelerator](https://forrest.nyc/accelerator/) - Become a job-ready Modern GIS Analyst in 30 days Learn the modern GIS stack the way employers actually use it. Python, spatial SQL, and AI workflows, taught through real GIS tasks, with portfolio projects you can show in interviews. Start Your Journey "This course by Matt Forrest proved invaluable for my progression and learning and
- [Modern GIS Accelerator | Learn Python, SQL & Cloud GIS to Advance Your Career](https://forrest.nyc/accelerator-2025/) - Level up your GIS career and your earning potential Professionals who apply modern GIS skills like Python, SQL, and Cloud GIS consistently report higher salaries and faster career growth than peers in traditional roles. The Modern GIS Accelerator gives you the roadmap, hands-on projects, and AI-powered guidance to build those skills and move into
- [GIS Team Training & Development Programs: Build a Top 5% Geospatial Workforce](https://forrest.nyc/modern-gis-training-for-teams/) - The fastest way to turn your GIS team into a top 5% powerhouse starts here Equip your workforce with the skills they need to thrive in modern GIS. From AI copilots to advanced data engineering, our programs accelerate learning, deliver measurable ROI, and connect you to a pipeline of certified geospatial talent. Why “Top 5%
- [Modern GIS Accelerator | Learn Python, SQL & Cloud GIS to Advance Your Career](https://forrest.nyc/mgx-old/) - Go From GIS Analyst to Spatial Architect in 12 Weeks And receive 12 full months of personal coaching and support to step into high-impact, $100K+ roles in spatial engineering, architecture, and strategy. MGx is the only modern GIS career accelerator that teaches the technical skills, the system architecture, and the strategic thinking required to become
- [Matt Forrest - Modern GIS and Geospatial](https://forrest.nyc/2026-goals/) - Shape your growth in 2026. Tell me what you want to achieve next year so I can build the courses, tools, and support that actually help you get there. This will take less than 36 seconds and will have a real impact on what I create for you.
- [Modern GIS Accelerator - Learn GIS skills that pay off](https://forrest.nyc/accelerator-old/) - • MODERN GIS ACCELERATOR Learn GIS skills that pay off Get straight to the skills you need to learn and get the tactical steps for your next career move… in just 2 weeks Accelerate your career ⚡️ ENABLED BY AI • Join 100+ students already enrolled The Trap Are You Stuck in the Technician Trap?
- [AI Copilot for GIS: Prompts & Workflows for SQL & Python](https://forrest.nyc/ai-copilot-offer/) - LIMITED TIME OFFER - ONLY AVAILABLE HERE Reclaim hours & supercharge your GIS workflow with AI You’ve got your free guide. Now go beyond tips — build a repeatable AI system for SQL, Python, analysis, and documentation so you work faster and stand out. 👉 Upgrade Now — Lifetime Access $27 (limited) 🔒 SECURE CHECKOUT 
- [Career Compass for GIS Professionals: The step-by-step system to land your next GIS job fast](https://forrest.nyc/career-compass-newsletter/) - • CAREER COMPASS Land your next GIS job, fast. A tactical career system for job seekers ready to level up and get hired... without the headache. Unlock for ̶ $̶9̶9̶ ̶ $49 ⚡️ POWERED BY AI • Trusted by 100+ GIS professionals The Burnout ❌ Tired of applying and hearing nothing back? You’re not alone.
- [Career Compass for GIS Professionals: The step-by-step system to land your next GIS job fast](https://forrest.nyc/career-compass/) - • CAREER COMPASS Land your next GIS job, fast. A tactical career system for job seekers ready to level up and get hired... without the headache. Unlock for $99 ⚡️ POWERED BY AI • Trusted by 100+ GIS professionals The Burnout ❌ Tired of applying and hearing nothing back? You’re not alone. You’ve got
- [Career Compass for GIS Professionals: The step-by-step system to land your next GIS job fast](https://forrest.nyc/career-compass-for-gis-professionals-the-step-by-step-system-to-land-your-next-gis-job-fast/) - • CAREER COMPASS Land your next GIS job, fast. A tactical career system for job seekers ready to level up and get hired... without the headache. Unlock for ̶ $̶9̶9̶ ̶ $77 ⚡️ POWERED BY AI • Trusted by 100+ GIS professionals The Burnout ❌ Tired of applying and hearing nothing back? You’re not alone.
- [AI Copilot for GIS: Prompts & Workflows for SQL & Python](https://forrest.nyc/ai-copilot-for-gis-prompts-workflows-for-sql-python/) - Put AI to work in your GIS and reclaim hours every week Build a repeatable system for using AI tools like ChatGPT, Claude, and Cursor in your GIS and geospatial work, every day. Turn routine into leverage, become the person who ships high-impact work, and future-proof your career. Why AI is a real career accelerator—not
- [AI Copilot for GIS: Prompts & Workflows for SQL & Python](https://forrest.nyc/ai-copilot-for-gis/) - Put AI to work in your GIS and reclaim hours every week Build a repeatable system for using AI tools like ChatGPT, Claude, and Cursor in your GIS and geospatial work, every day. Turn routine into leverage, become the person who ships high-impact work, and future-proof your career. Why AI is a real career accelerator—not
- [Learn Geospatial Data Science: Spatial Statistics with PySAL, Cloud-Native Geospatial](https://forrest.nyc/learn-geospatial-data-science/) - MODERN GIS CERTIFICATION G Track: Geospatial Data Science The G Track teaches you how to perform advanced spatial analysis and modeling—combining classic statistical methods with modern, scalable tools for real-world geospatial insights. Register and get certified Micro-courses This track consists of four micro-courses (bricks), each designed to take 4–6 hours. Learn by doing You’ll learn
- [G1: Spatial Autocorrelation - Learn Spatial Data Science](https://forrest.nyc/bricks-g1/) - MODERN GIS CERTIFICATION G1: Spatial Autocorrelation This brick introduces the essential methods for detecting spatial patterns and identifying hotspots in your data. You’ll get hands-on experience with techniques like: Moran’s I for measuring spatial autocorrelation Getis-Ord Gi* for pinpointing statistically significant clusters Register & Get Started for $49 Brick G1 – Core Competencies 
- [Learn Geospatial Data Engineering: Cloud-Native Pipelines, Airflow, and Apache Iceberg](https://forrest.nyc/geospatial-data-engineering/) - MODERN GIS CERTIFICATION E Track: Geospatial Data Engineering & Pipelines The E Track teaches you how to build scalable, automated, cloud-native pipelines for geospatial data—using the same tools trusted by data engineers, scientists, and modern GIS teams. Register and get certified Micro-courses This track consists of four micro-courses (bricks), each designed to take 4–6 hours.
- [E3: Apache Airflow for Geospatial Automation - Learn Cloud-Native Geospatial](https://forrest.nyc/bricks-e3/) - This brick introduces automated geospatial pipelines using Apache Airflow—a powerful workflow engine for scheduling, monitoring, and scaling spatial data tasks. You’ll get hands-on experience with real-world pipelines like: Daily raster inference and tiling to PMTiles Vector-to-GeoParquet transformation and catalog updates Register & Get Started for $49 SPATIAL LAB CERTIFICATION E3: Apache Airflow for
- [E2: Apache Iceberg for Geospatial Data - Learn Cloud-Native Geospatial](https://forrest.nyc/bricks-e2/) - SPATIAL LAB CERTIFICATION E2: Apache Iceberg for Geospatial Data This brick introduces Apache Iceberg—an open table format that brings versioning, schema evolution, and SQL access to large-scale spatial data. You’ll get hands-on experience building and querying Iceberg tables with: GeoParquet for scalable vector storage Cloud object storage as the data lake foundation PyIceberg
- [E1: Cloud-Native Geospatial Files - Learn Cloud-Native Geospatial](https://forrest.nyc/bricks-e1/) - MODERN GIS CERTIFICATION E1: Cloud-Native Geospatial Files This brick introduces the essential file formats powering modern, scalable spatial data workflows. You’ll get hands-on experience with formats like: Cloud-Optimized GeoTIFF (COG) for raster data GeoParquet for columnar vector data Register & Get Started for $49 Brick E1 – Core Competencies (High-Level)Cloud Storage & Streaming
- [Terms and Conditions](https://forrest.nyc/terms-and-conditions/) - 📄 Terms and Conditions Effective Date: June 23, 2025Last Updated: June 23, 2025 Welcome to the Modern GIS Accelerator ("Program"). By enrolling, you agree to these Terms and Conditions ("Terms") which govern your participation. 1. Enrollment & Access You must be at least 16 years old to participate. Upon payment, you receive a personal, non-transferable
- [Privacy Policy](https://forrest.nyc/privacy-policy/) - 🔒 Privacy Policy Effective Date: June 23, 2025Last Updated: June 23, 2025 Modern GIS Accelerator and Spatial Lab ("we," "us," or "our") is committed to protecting your privacy. This Privacy Policy outlines how we collect, use, and safeguard your personal information when you enroll in the Modern GIS Accelerator program or visit our website. 1.
- [Matt Forrest - Modern GIS and Geospatial](https://forrest.nyc/thank-you/) - Thank you. Really. Welcome! I am excited to have you on board and am excited to help you grow. You will receive an email shortly with all the information you need to get started with your program! In the meantime I would love to learn how I can help you most. Mind sparing 18.3 seconds
- [Matt Forrest - Modern GIS and Geospatial](https://forrest.nyc/media-kit/) - Reach target customers geospatial experts decision makers new audiences Reach 93,000+ geospatial experts and industry leaders focused on geospatial across multiple channels with partnered content with a long shelf life. My Audience Growing modern geospatial Learn a bit about my audience and who you can reach. LinkedIn Reach an engaged global audience I use
- [Career Compass for GIS Professionals: The step-by-step system to land your next GIS job fast](https://forrest.nyc/career-compass-offer/) - • CAREER COMPASS Land your next GIS job, fast. A tactical career system for job seekers ready to level up and get hired... without the headache. Unlock for ̶ $̶9̶9̶ ̶ $27 ⚡️ POWERED BY AI • Trusted by 100+ GIS professionals The Burnout ❌ Tired of applying and hearing nothing back? You’re not alone.
- [Matt Forrest - Modern GIS and Geospatial](https://forrest.nyc/thanks/) - Thank you. Really. I want to make sure that I send you exactly the type of content and newsletters you want to read. Mind sparing 18.3 seconds (I took it myself and timed it) to tell me about what you're hoping to learn?
- [Modern GIS Accelerator - Learn GIS skills that pay off](https://forrest.nyc/modern-gis-accelerator-students/) - • MODERN GIS ACCELERATOR Learn GIS skills that pay off Get straight to the skills you need to learn and get the tactical steps for your next career move… in just 2 weeks Unlock for ̶ ̶$̶3̶9̶9̶ ̶ $197 ⚡️ ENABLED BY AI • Join 100+ students already enrolled The Trap Are You Stuck in
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- [Articles](https://forrest.nyc/articles/)
- [Tech Stack and Gear](https://forrest.nyc/tech-stack-and-gear/) - ResourcesSpatial SQLPythonModern GISThe CloudToolsTech Stack & GearMy Notion Productivity TemplateBooks & CoursesAbout meGet in touchPodcastsTalksModern GIS & Spatial SQL GearGrab some modern GIS and spatial SQL gear!Modern GIS & Spatial SQL StoreModern GIS Tech StackOn any given day I use a random mix of tools for different GIS tasks. Most of my time is spent
- [About](https://forrest.nyc/about/) - Get started hereGEOSPATIAL ARTICLES AND GUIDESThe best place to get started is with my articles and guidesTake a look at some of my past guides and resources on topics like spatial SQL, geospatial Python, modern GIS, and more.TAKE ME TO THE ARTICLESA MONTHLY LINKEDIN NEWSLETTERI publish a once a month newsletter only on LinkedInMy newsletter,

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## Templates

- [Footer](https://forrest.nyc/?elementskit_template=footer) - Spatial Lab Join the Spatial Lab community Policies Privacy Policy Terms & Conditions Spatial SQL Get the Spatial SQL book today Join Us © Matt Forrest 2024. All Rights Reserved.
- [Header](https://forrest.nyc/?elementskit_template=header) - Posts Join the Spatial Lab Learn Modern GIS Sponsor Coaching Podcast X Sign Up Get the newsletter Join 71,000+ geospatial experts growing their skills and careers. Get updates on the most cutting edge updates in modern GIS and geospatial every week. Edit Content LinkedIn YouTube

## Portfolio

- [Running up that hill](https://forrest.nyc/portfolio/running-up-that-hill/) - Convey the determination and effort required to overcome obstacles and reach one’s goals.
- [Visualizing concepts](https://forrest.nyc/portfolio/visualizing-concepts/) - Discuss the power of graphical representations in clarifying complex ideas and information.
- [Full-scale expression](https://forrest.nyc/portfolio/full-scale-expression/) - Investigate the significance of complete and unreserved self-expression in various creative endeavors.
- [Smooth handoff](https://forrest.nyc/portfolio/smooth-handoff/) - Explore the seamless transfer of responsibilities between team members in a project or task.
- [Behind the feature](https://forrest.nyc/portfolio/behind-the-feature/) - Provide insights into the development and decision-making process behind a specific product or service feature.
- [Lingua franca](https://forrest.nyc/portfolio/lingua-franca/) - Delves into the role of a common language in facilitating communication and understanding among cultures.
- [Just your type](https://forrest.nyc/portfolio/just-your-type/) - Examine the importance of selecting the right font style and size for effective communication and design.
- [Throwing curveballs](https://forrest.nyc/portfolio/throwing-curveballs/) - Delve into the strategy of introducing unexpected challenges or changes to test adaptability and problem-solving skills.
- [Illuminating dark mode](https://forrest.nyc/portfolio/illuminating-dark-mode/) - Explore the benefits and design considerations of dark user interfaces in digital applications.

## Categories

- [Article](https://forrest.nyc/category/article/)
- [Tutorial](https://forrest.nyc/category/tutorial/)
- [Podcast](https://forrest.nyc/category/podcast/)
- [Essay](https://forrest.nyc/category/essay/)

## Tags

- [zip codes](https://forrest.nyc/tag/zip-codes/)
- [geospatial](https://forrest.nyc/tag/geospatial/)
- [gis](https://forrest.nyc/tag/gis/)
- [Spatial SQL](https://forrest.nyc/tag/spatial-sql/)
- [sql](https://forrest.nyc/tag/sql/)
- [bigquery](https://forrest.nyc/tag/bigquery/)
- [aggregations](https://forrest.nyc/tag/aggregations/)
- [postgis](https://forrest.nyc/tag/postgis/)
- [Modern GIS](https://forrest.nyc/tag/modern-gis/)
- [Cloud GIS](https://forrest.nyc/tag/cloud-gis/)
- [Python](https://forrest.nyc/tag/python-for-gis/)
- [snowflake](https://forrest.nyc/tag/snowflake/)
- [duckdb](https://forrest.nyc/tag/duckdb/)
- [geoparquet](https://forrest.nyc/tag/geoparquet/)
- [Apache Sedona](https://forrest.nyc/tag/apache-sedona/)
- [Apache Iceberg](https://forrest.nyc/tag/apache-iceberg/)
- [Apache Airflow](https://forrest.nyc/tag/apache-airflow/)
- [Cloud Optimized GeoTIFF](https://forrest.nyc/tag/cloud-optimized-geotiff/)
- [Wherobots](https://forrest.nyc/tag/wherobots/)
- [Cloud-Native Geospatial](https://forrest.nyc/tag/cloud-native-geospatial/)
- [Esri](https://forrest.nyc/tag/esri/)
- [ArcGIS](https://forrest.nyc/tag/arcgis/)
- [GISP](https://forrest.nyc/tag/gisp/)

## Categories

- [Business](https://forrest.nyc/portfolio-category/business/)
- [Corporate](https://forrest.nyc/portfolio-category/corporate/)
- [Creative](https://forrest.nyc/portfolio-category/creative/)