Geo-analytics Platforms

💥 You don’t need $40,000 worth of GIS software to build powerful geospatial systems I’ve seen full smart city platforms, dashboards, routing, spatial analysis, real-time sensors, built entirely on open source. And when done right, they’re faster, more flexible, and vendor-free. Here’s the kind of stack that makes it possible: 🖥️ Desktop & Analysis QGIS, GRASS GIS, SAGA GIS, WhiteboxTools 🗄️ Databases & Data Management PostGIS, pgRouting, Spatialite, GeoPackage ☁️ Publishing & Servers GeoServer, MapServer, TileServer GL, MapProxy 🧭 Web Mapping & Visualization Leaflet.js, OpenLayers, MapLibre GL, Kepler.gl 🤖 Python Automation & Processing GeoPandas, Rasterio, PyQGIS, Shapely, Fiona, Snakemake 🛰️ Remote Sensing & EO ESA SNAP, Orfeo Toolbox, Sentinel Hub, OpenDroneMap, eo-learn 🚦 Routing, Mobility, and Indoor GIS OpenRouteService, Valhalla, OpenStreetMap, JOSM, OpenIndoor This isn’t just about cost. It’s about control. Scalability. Transparency. Innovation. Open source GIS is not a compromise. It’s a competitive advantage But only if you know how to connect the pieces. What’s in your open source GIS stack? Let’s build a real ecosystem — no licenses required #GIS #OpenSource #SmartCities #QGIS #PostGIS #GeoServer #PythonGIS #DigitalTwin #Wayfinding #UrbanTech

Ever felt like your datasets were just sitting there, lonely and a little bored? You're not alone. The world is awash in data, but without the right tools, it's just a bunch of numbers. A mind-boggling 80% of all data is estimated to have a geospatial component. 🤯 But for many organizations, that rich, locational information is often overlooked, trapped in silos, or too complex to analyze alongside other business data. It's like having a map without knowing how to read it. 🗺️ The Problem: The Geospatial Data Gap 👉 Think about it. You have sales figures, customer demographics, and supply chain logistics. But what if you could overlay that with satellite imagery to see how weather patterns are impacting your delivery routes? Or analyze how a new construction project is affecting foot traffic? 👉 Previously, this was a massive undertaking, requiring specialized GIS (Geographic Information System) software, complex data pipelines, and a team of experts. It was a huge barrier to entry for most data professionals. The Solution: Earth Engine + BigQuery Geospatial 👉 This is where the game-changer comes in. The general availability of Earth Engine in BigQuery and the new geospatial visualization capabilities in BigQuery Studio have made a huge leap forward. It’s like bringing the world's largest public satellite imagery and geospatial data catalog right into your data warehouse. 👉 Now, data analysts can seamlessly combine their own structured data with petabytes of pre-analyzed geospatial data. No more moving massive datasets around! 🚀 Benefits for Your Organization: This isn't just a technical upgrade; it's a strategic one. Here's what this can mean for your business: 👉 Risk Assessment: An insurance provider can quickly analyze changes in extreme weather events to better assess risk and price policies. ☔ 👉 Supply Chain Optimization: Retailers can integrate traffic data and weather forecasts to find the most efficient delivery routes and avoid delays. 🚚 👉 Sustainable Practices: Companies can monitor deforestation or agricultural land changes to ensure their supply chain is sustainable. 🌳 👉 Unified Platform: Analysts can go from data discovery to complex analysis and interactive visualization, all in one place. No more switching between multiple tools. 💻 This unified approach democratizes geospatial analysis, making it accessible to a much broader audience and unlocking powerful new insights that were once out of reach. We're moving beyond static dashboards. The ability to ask "what if" questions and visualize the answers directly on a map is a game-changer. It’s no longer about just analyzing what happened, but understanding where it happened and why. So, let your data explore the world, and see the amazing new stories it has to tell. 💖 Follow Omkar Sawant for more. More details in the comments. #EarthEngine #BigQuery #Geospatial #DataAnalytics #DataScience #CloudComputing #GIS #GoogleCloud #TechTrends #Innovation

The hardest part of modern GIS isn’t the data, it’s choosing the right stack. What works beautifully on your laptop might crumble under enterprise demands. I’ve heard this again and again: "I know how to use GeoPandas, but I don’t know when to move to PostGIS, Apache Sedona, or the cloud." "I’m stuck deciding what’s overkill and what’s underpowered." So I wrote the guide I wish existed: 🔍 A practical breakdown of today’s top geospatial processing tools: from GeoPandas to DuckDB, PostGIS, Apache Sedona, Wherobots, and BigQuery/Snowflake. For each tool, I cover: ✅ Where it shines ⚠️ Where it breaks down 🎯 What use cases it’s best suited for 📉 When returns start diminishing Whether you're an individual analyst or scaling planetary datasets across the cloud, this will help you pick the right tool for your stage, your team, and your data. 🌎 I'm Matt and I talk about modern GIS, geospatial data engineering, and how spatial thinking is changing. 📬 This post is live on my site, but you would have already had it if you signed up for my newsletter. Join 5k+ others learning from my newsletter → forrest.nyc

The GIS SaaS market is growing, and the GIS jobs are not. How is it possible? 2 weeks ago, I wrote my most popular post ever: “Will GIS be replaced by BI?” reaching 42,000 impressions and 50 comments. Many smart folks commented under the post, sharing their thoughts. Here is one interesting takeaway: GIS software/SaaS/cloud is growing 8-18%/year (IMR-14305) But on the job market, some decline -0.3%/y, some grow 0.5%/year (BLM) Here is what I think is happening: new GIS tools are not for GIS experts anymore. Instead, they target data and business analysts as their main users. Here is how they do it: → Move GIS analysis to the web (CARTO, KeplerGL) → Enable GIS support in SQL (BigQuery, Snowflake, Wherobots) → Enable access to data in the cloud (Overture Maps, CARTO Data Observatory) → AI prompts to SQL to map (Aino, Overture Maps GPT) Below are 7 tools I know implementing these strategies: 1️⃣ Aino, follow Alex Kamenev They put together a database with open data and map visualization and let an AI Agent do the queries. → Who is it for? Business users, planners, analysts. 2️⃣ Wherobots, follow Matt Forrest and Sean Knight Build managed Apache Sedona (GIS extension of Spark) so you can run GIS functions against large datasets in the cloud, by just typing SQL. → Who is it for? Data and ML engineers. 3️⃣ CARTO, follow Javier de la Torre Put datasets into the cloud (BigQuery/Snowflake) and created a low-code pipeline builder with prebaked analytical functions, so you can build GIS dashboards with drag-and-drop. → Who it’s for: Data Analysts 4️⃣ KeplerGL with DuckDB, follow Ilya Boyandin and Vikram Gundeti Build UI for deckGL (webGL map visualisations) and combine it with DuckDB, so you can open big Geoparquet files and crunch them in the browser. → Who is it for? Data Scientists, Data Analysts 5️⃣ Dekart, follow me 🤠 Build a backend for KeplerGL with connectors to BigQuery/Snowflake/Wherobots so you can create maps with SQL. → Who is it for? Data Scientists, Data Analysts 6️⃣ Overture Maps Foundation, follow Marc Prioleau Combined many open datasets like OSM and Open Buildings into a well-curated schema in the cloud so you get map data with a simple SQL query. → Who is it for? Data Scientists, Data Analysts 7️⃣ Monda AI, follow Martin Aschenbrenner Build tools for data providers to ship datasets to the cloud (BigQuery/Snowflake) with a few clicks so data analysts on the buyer side can easily access it. → Who is it for? Sales, Data Analysts —— Reading this, it’s easy to see the patterns: → desktop to web → Shapefiles to cloud datasets → GIS experts to data and business analysts 👋 Hey, I’m on the challenge of posting daily for Managers in Data. Can I do it, and will it help my project? Curios, FOLLOW me on my journey!

🧵 #OSINT 📍Geoanalysis: 7 powerful tools in 2024: 1. #QGIS QGIS is a comprehensive open-source Geographic Information System that allows for detailed spatial analysis, visualization, and mapping. Use Case: Analysts can import satellite imagery, GPS data, and create layered visualizations for crime scene mapping or conflict monitoring. https://qgis.org/ 2. #OpenStreetMap (OSM) OSM is a collaborative mapping project that offers freely editable map data of the world. Use Case: Journalists can cross-reference and geolocate areas during investigations or verify infrastructure damage using OSM overlays with other imagery. https://lnkd.in/dGqnzwpY 3. Google Earth Engine A cloud-based platform for planetary-scale environmental data analysis. It hosts satellite data and provides analysis tools. Use Case: Used to track deforestation, environmental disasters, or changes in conflict zones over time using time-series imagery. https://lnkd.in/dg3B74kU 4. #Sentinel Hub Sentinel Hub provides access to ESA’s Copernicus program’s satellite data (Sentinel series) with processing and analysis capabilities. Use Case: Useful for detecting military movements, refugee camps, or natural disasters using high-resolution satellite imagery. https://lnkd.in/dQx9cjrk 5. Mapillary Description: Mapillary is an open platform for street-level imagery contributed by a global community. Use Case: Journalists can validate on-ground conditions in remote areas using Mapillary images or cross-check social media claims. https://www.mapillary.com/ 6. SAS Planet Description: A standalone software to view and download satellite imagery from multiple sources (Bing, Google, Yandex, etc.) for offline analysis. Use Case: Great for side-by-side imagery comparisons in rapidly evolving conflict zones or natural disasters. https://sasgis.org/ 7. CesiumJS Description: CesiumJS is a JavaScript library for creating 3D geospatial applications and visualizations. Use Case: Used in investigative journalism to create interactive 3D reconstructions of conflict events, incidents, or large-scale developments. https://lnkd.in/d9i6gD3F