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

Most companies analyze data.  But very few analyze where the data is happening. That’s why this new update from Microsoft Fabric is interesting 𝗠𝗮𝗽𝘀 𝗶𝗻 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 𝗮𝗿𝗲 𝗻𝗼𝘄 𝗚𝗲𝗻𝗲𝗿𝗮𝗹𝗹𝘆 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲. And it adds a completely new dimension to analytics: Location intelligence. Instead of just dashboards and tables, teams can now visualize data directly on maps inside Fabric. Why this matters: → You can monitor real-time events geographically  → Overlay multiple datasets on spatial layers  → Analyze regional trends instantly  → Track devices, logistics, and operations visually And because it's integrated with Fabric Lakehouse, Eventhouse, and Real-Time Intelligence, geospatial analytics becomes part of your core data platform. In simple terms: Before → You saw numbers in dashboards  Now → You see patterns on a map This unlocks powerful use cases:  • Logistics route optimization   • IoT device monitoring   • Regional sales analysis   • Supply chain tracking   • Operational intelligence Microsoft is quietly turning Fabric into a full intelligence platform, not just data analytics, but real-time + spatial insights together. And that’s a big step toward next-gen analytics platforms. Curious? What would you map first in Microsoft Fabric? Full announcement:  https://lnkd.in/gYvZHDJX #MicrosoftFabric #DataAnalytics #Azure #DataEngineering #BusinessIntelligence #LocationIntelligence #GeospatialAnalytics #AzureMaps #IoTAnalytics #ModernDataStack #TechInnovation #DataPlatform #AnalyticsCommunity 

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!

I tested 50 AEO / GEO tools in the last 7 days. These 6 are the only ones worth their weight in gold… Promptwatch uncovers massive visibility gaps you didn’t know existed and shows you exactly how to fix them. It lets you see (live) how AI snapshots, crawlers, and GEO changes affect traffic. SEOmonitor is a game-changer for showing clients exactly where their visibility lives, whether in organic search or AI responses, and increases buy-in from C-suite by tying directly to organic revenue projections using their forecasting tools. Cognizo goes beyond analytics with the most actionable recommendations in AI search – giving marketers a clear path to turn visibility into growth. They help brands adapt to the new customer journey and be part of the answer. Evertune AI is the only AI search optimization platform that runs 1M+ prompts per customer every month across major AI platforms, showing you how these engines actually recommend brands. The platform also provides data-driven content strategy playbooks to help brands improve their AI visibility and recommendations. Morningscore uses AI-driven suggestions for link building to figure out which sites might bring you the most benefit and alerts you to potential link gaps. Ahrefs web analytics offers a better way to track website traffic with focused insights that's privacy friendly, cookie-free, and lightning fast. Users can track SEO wins, monitor AI traffic, analyze user journey, and capture outbound links.

🧵 #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

🚨 What’s New in ArcGIS Location Platform – Summer 2025 🚨 Esri just rolled out some major updates to the ArcGIS Location Platform, making it even easier to embed high-quality location intelligence into your apps, services, and analytics pipelines. Here are some highlights developers, analysts, and architects should take note of: 🛣️ Snap to Roads (June 2025) GPS traces now automatically align to road geometry—with attributes like road type, direction, and restrictions. Perfect for route correction, logistics, and mobile apps. 🗺️ New Basemap Services (August 2025) • Basemap Sessions – one flat fee for unlimited tile views per session. Predictable, budget-friendly for interactive apps. • Open Basemaps – fresh, community-sourced maps from Overture, OpenStreetMap & Microsoft. Open data, ready to go. 📊 Service Health Dashboard Real-time status and historical reliability, now visible at the ArcGIS Trust Center. Because uptime matters. 📈 GeoEnrichment Updates Now powered by Esri’s 2025 demographic data! Legacy data has been retired. Plan your updates accordingly. Heads-up: Legacy API Keys will be deprecated by June 2026. Now's the time to migrate to new keys and token workflows. The Best Part? All these services are callable from anywhere. Use them in Python notebooks, JavaScript apps, or even trigger them from UDFs inside Snowflake or Databricks. Whether you’re building mobile apps, dashboards, or running advanced spatial analytics—this platform is ready to plug in. Full blog: https://lnkd.in/g3vpZCpx #Esri #ArcGIS #LocationIntelligence #SpatialAnalytics #Snowflake #Databricks #Developers #OpenData #GIS #GeoEnrichment #Basemaps #SnapToRoads #PlatformEngineering #GeospatialAI #DataEngineering #APIs

What if you could identify, at a ZIP code level, exactly where your best customers live and where your next "best markets" are emerging? That’s what we set out to do this quarter with a geospatial analysis 🌎 for one of our clients. Part 1: Geo-Spatial Analysis (partner KnoWhere Analytics) Part 2: Incrementality Testing (partner Stella | Growth Intelligence) 𝗧𝗵𝗲 𝗴𝗼𝗮𝗹 𝘄𝗮𝘀 𝘀𝗶𝗺𝗽𝗹𝗲: 👉 Identify ZIP codes across the US with 𝙪𝙣𝙧𝙚𝙖𝙡𝙞𝙯𝙚𝙙 𝙨𝙖𝙡𝙚𝙨 𝙤𝙥𝙥𝙤𝙧𝙩𝙪𝙣𝙞𝙩𝙮 👉 Build a smarter pool of high-potential customers to make Q4 as impactful as possible Here is how it works ⬇️ 𝗜𝗻𝗽𝘂𝘁𝘀: ▪️ 2-3 years of customer data (Shopify, BigCommerce, etc) ▪️ 2020 & 2023 Census data (population, income, demographic data) ▪️ Custom Development Index derived from federal imagery and national atlas datasets 𝗢𝘂𝘁𝗽𝘂𝘁𝘀: 🔵 National coverage, ZIP code-level scoring system broken into 3 groups & 3 tiers (e.g. Strong Tier 1, As Expected, Opportunity Tier 2) 🔵 General Targeting Score (GTS) - a full ranking of all zip codes within the nation and propensity for sales 🔵 Full range of high resolution maps and clickable KML files for Google Earth to aid visualization 🌎 (see image attached) 🔵 Key Audience (sales drivers) variable importance list 𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗼 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀: Once the model runs, it tells you which variables are most correlated to your customers - because this is independent of surveys, ad platform data, and other information, the result is an independent validation of current understanding of the audience, and provides unique insight into consumer qualities. Maybe it’s ZIPs with more renters, and maybe it’s zips with a certain range of renters to buyers. Maybe it’s higher education levels or higher income clusters. The result is the ability to see your customer DNA, geographically mapped across the U.S. 𝗛𝗼𝘄 𝗪𝗲 𝗨𝘀𝗲𝗱 𝗜𝘁: That’s where things get fun. For this client, we identified 1.6K ZIP codes classified as “Opportunity” areas. Those zip codes were match markets to our top-performing ZIPs, but they were underindexing with sales. Next, we took those 1600 zip codes and ran an incrementality test across Meta and YouTube. Then we used Stella to measure lift. There are many tests for this model and data which can be tested and applied: ▪️Use the Opportunity ZIPs for out-of-home or direct mail testing ▪️ Double down on your strongest ZIPs for customer acquisition and retention during promo 𝗔 𝗻𝗼𝘁𝗲 𝗼𝗻 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗶𝘁𝘀𝗲𝗹𝗳: Our end goal was to find 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 to better direct ad spend. And while we’re always trailing real data, we think because demographic structures shift slowly; relative differences between ZIPs remain meaningful. If you’re interested in Google Ads, or about running one of these analyses, feel free to connect with me. Banfana, Stella | Growth Intelligence

ISRO - Indian Space Research Organization Chief S Somnath recently said that India's Bhuvan geoportal is almost 10 x better than Google since it provides details even at Panchayat level. We took a deep dive to find out why and how is the platform better than the global giant in terms of Indian needs and applications. Emphasising the importance of Bhuvan, Radha Krishna Kavuluru, principal engineer at Dhruva Space also said, “Almost everything that can be done with satellite imagery like land use, land cover, flood information system… everything is already integrated on Bhuvan.” He advised, “If you just open Bhuvan 2D and see the applications, scroll down, you will see a lot of them.” The Bhuvan platform hosts an extensive collection of vector datasets including the locations of post offices, Aadhaar centres, and disaster response agencies. It also powers sector-specific applications such as School GIS, Tourism GIS, Water Body Information System, and real-time forest fire alerts. What sets Bhuvan apart is its unique integration of government departments on a single GIS platform that is openly accessible to citizens. “There is no such GIS system which is open for the public available in the real world,” noted Krishna. The platform democratises access to valuable geospatial data and satellite imagery that can be utilised for a variety of purposes including navigation. This integration of local government bodies on a GIS platform is unparalleled globally. “Panchayat is one of the sectors integrated in GIS. This is a GIS system that integrates all the government departments, which really does not exist in any other country,” said Radha Krishna. According to a recent study, Bhuvan-Panchayat provides high-resolution data to over 250,000 village panchayats across India, enabling precise governance interventions. Read more at: In contrast, other platforms like Google Earth, ArcGIS, and Bing Maps have their own unique strengths, such as global coverage, advanced GIS capabilities, and location intelligence. Read the article for more details: