# Wherobots

> Wherobots is the context engine for physical world data: spatial compute and earth intelligence that ground AI agents and physical AI in the real world\.

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## Pages
- [Products](https://wherobots.com/products/)
- [Automate](https://wherobots.com/products/automate/)
- [AI for Earth](https://wherobots.com/products/ai-for-earth/)
- [Build](https://wherobots.com/products/build/)
- [Discover](https://wherobots.com/products/discover/)
- [Compute](https://wherobots.com/products/compute/)
- [Apache Sedona](https://wherobots.com/apache-sedona/)

## Posts
- [Most Dangerous Roads for Pedestrians and Cyclists in the US \(Part 2\)](https://wherobots.com/blog/most-dangerous-roads-for-pedestrians.md): We ran the Wall Street Journal's Union Avenue test on every U\.S\. arterial road\. The worst 1\.5 miles for people on foot is Westheimer Road in Houston\.
- [Most Dangerous Highway in the US: 25 Deadliest Stretches](https://wherobots.com/blog/most-dangerous-highway-in-the-us.md): We compared five years of fatal crashes with the crashes expected on similar roads\. The worst stretch is 10 miles of U\.S\. 19 in Pasco County, Florida\.
- [Utility Vegetation Management at Scale with Earth Intelligence](https://wherobots.com/blog/utility-vegetation-management-earth-intelligence.md): Utility vegetation management with open data: we mapped trees that could reach power lines in King County, WA and Shasta County, CA in under an hour each\.
- [Putting the HERE Technologies and Wherobots partnership to work](https://wherobots.com/blog/here-wherobots-wildfire-evacuation-routes.md): Every road out of Mount Hermon, California, runs beside high\-risk power lines\. Wherobots and HERE measured the evacuation trade\-off in miles and minutes\.
- [Yulin Naval Base in Satellite Imagery: AI\-Assisted Vessel Counts](https://wherobots.com/blog/yulin-naval-base-satellite-imagery.md): Six Vantor images of Yulin Naval Base run through SAM3 and spatial SQL: 902 detections, 72 checked by eye, 37 confirmed vessels and 20 piers\.
- [Wherobots for QGIS: Cloud\-Scale Spatial Data, from Wherobots Labs](https://wherobots.com/blog/spatial-sql-qgis.md): Run spatial SQL in QGIS against cloud\-scale data\. The Wherobots plugin queries billions of geometries, loads results as layers, and pulls raster into view\.
- [How Wherobots builds with NVIDIA to let AI see the physical world](https://wherobots.com/blog/wherobots-nvidia-geospatial-ai-physical-world.md): How does Wherobots do geospatial AI on NVIDIA GPUs? RasterFlow for satellite imagery inference, SedonaDB spatial joins on ray tracing cores, up to 5\.9× faster\.
- [El Niño 2026, atmospheric rivers, and California’s burn scars: one SQL engine, two data models](https://wherobots.com/blog/raster-vector-join-high-hazard-basins.md): A raster vector join in WherobotsDB counts 7,718 buildings and 411 km of road below 42 high\-hazard Eaton basins as California prepares for El Niño 2026\.
- [Orchestrating Wherobots Jobs from AWS Step Functions: A Reference Architecture](https://wherobots.com/blog/orchestrate-jobs-from-aws-step-functions-a-reference-architecture.md): Orchestrate jobs with AWS Step Functions using the callback pattern\. Submit a Wherobots job, pause for the task token, resume when it finishes\. See the code\.
- [Measuring the Strait of Hormuz shutdown with Sentinel\-2, WherobotsDB and Overture Maps](https://wherobots.com/blog/hormuz-vessel-detection.md): WherobotsDB read 719 Sentinel\-2 scenes in place, fetched about 1\.5 GB of the 151 GB, and joined the detections against Overture Maps land polygons to measure a 95% fall in traffic through the Strait of Hormuz corridor\. Loading at Kharg and waiting at Fujairah held at 2025 levels, and the analysis cost about $63\.
- [RasterFlow is now available in Public Preview](https://wherobots.com/blog/rasterflow-public-preview-planetary-scale-earth-intelligence.md): RasterFlow is now in public preview\. Run planetary\-scale Earth observation with SAM3, cloud\-free Sentinel\-2 mosaics, and predictable per\-task pricing\. See how it compares to Google Earth Engine\.
- [How to score every building in a state for catastrophe risk: an exploration project](https://wherobots.com/blog/how-to-score-every-building-in-a-state-for-catastrophe-risk.md): Building\-level catastrophe risk scoring with WherobotsDB\. 2\.77M Colorado buildings across wildfire, hail, flood, wind, and access in one spatial SQL pipeline\.
- [Learning Wherobots by Building a National AI Data Center Suitability Report](https://wherobots.com/blog/ai-data-center-site-suitability-wherobots.md): AI data center site suitability analysis across 17 Australian candidates, scored on 15\.9M geometries with Wherobots and published as an interactive report\.
- [The Wherobots Spatial AI Assistant is now in the Anthropic Connectors Directory](https://wherobots.com/blog/spatial-ai-assistant-anthropic-connectors.md): Spatial AI in Claude: the Wherobots spatial data connector is live in the Anthropic Connectors Directory\. Ask about the physical world, get grounded answers\.
- [From the Spokane firestorm to all of Washington: real\-time wildfire monitoring for under $50 a pass](https://wherobots.com/blog/spokane-fire-dnbr.md): The moment a satellite pass lands, this pipeline turns it into a burn\-severity map in 14 minutes: real\-time wildfire monitoring with Python and Spatial SQL that protects lives and assets, shown on the Spokane firestorm and scaled to the entire state of Washington\.
- [Wherobots Now Federates with the AWS Glue Data Catalog](https://wherobots.com/blog/aws-glue-data-catalog-spatial-workloads.md): Wherobots now reads and writes spatial data in the AWS Glue Data Catalog\. Keep governance in Glue, run spatial joins and RasterFlow on a purpose\-built engine\.
- [How Bad Telemetry Data Sabotages Modern Fleets](https://wherobots.com/blog/bad-telemetry-data-fleet-observability.md): Fleet observability begins where fleet monitoring ends\. See how Aspen Fleet, on Wherobots, uses spatial context to catch bad telemetry before incidents\.
- [Introducing the Wherobots Innovation Edition, designed to accelerate your physical world objectives ](https://wherobots.com/blog/introducing-the-innovation-edition.md): Make your spatial data AI\-ready\. The Wherobots Innovation Edition pairs our cloud platform with expert spatial engineers to ship production outcomes faster\.
- [Spatial Data in Apache Iceberg: Optimizations and Management That Matter](https://wherobots.com/blog/apache-iceberg-spatial-data.md): Spatial data in Apache Iceberg needs different optimization than tabular tables\. How to sort, size, partition, and retain geometry columns so filters prune\.
- [Spatial Graph RAG for the Physical World](https://wherobots.com/blog/spatial-graph-rag.md): Graph RAG grounds LLMs in a knowledge graph of entities and relationships\. Learn how Spatial Graph RAG builds that graph from physical\-world data with spatial SQL\.
- [Building the Wherobots Mobility Solution Accelerator: A Technical Deep Dive](https://wherobots.com/blog/mobility-solution-accelerator-gps-trajectory-processing.md): Build a GPS trajectory processing pipeline with Apache Sedona and Wherobots: 4D XYZM geometry, map matching, DBSCAN clustering, and GeoParquet output\.
- [How well does SAM3 detect building footprints? We asked the Wherobots Spatial AI Coding Assistant](https://wherobots.com/blog/sam3-aerial-imagery-building-footprints.md): Evaluate SAM3 on aerial imagery with the Wherobots Spatial AI Coding Assistant\. See how SAM3 building detections compare to Overture footprints in Oregon\.
- [Wherobots MCP Server: Building GEOINT Spatial Pipelines with AI Agents](https://wherobots.com/blog/wherobots-mcp-server-geoint-spatial-pipelines-ai-agents.md): The Wherobots geospatial MCP server gives AI agents direct access to your spatial catalog to build multi\-table GEOINT pipelines on Overture data in days\.
- [Change Detection Using AlphaEarth Foundations \(Part 2\)](https://wherobots.com/blog/alphaearth-foundations-change-detection-part-2.md): Score AlphaEarth Foundations embeddings for temporal change with leave\-one\-out medoid distance and robust z\-scoring on RasterFlow\. Workflow \+ Colorado demo\.
- [AlphaEarth Embeddings, Zonal Statistics, and PCA](https://wherobots.com/blog/alphaearth-embeddings-zonal-statistics.md): Aggregate AlphaEarth Foundations embeddings into field\-level vectors with zonal statistics\. We process 3\.5M Iowa fields and visualize them with PCA in GeoParquet\.
- [Introducing the Wherobots Python SDK](https://wherobots.com/blog/wherobots-python-sdk.md): The Wherobots Python SDK submits, monitors, and manages spatial jobs from any Python environment\. One install, one API key, no AWS credentials\.
- [Detecting Objects From Text Prompts with RasterFlow and Segment Anything 3](https://wherobots.com/blog/sam3-earth-observation-rasterflow.md): Wherobots ran Segment Anything 3 on NAIP aerial imagery at county scale with RasterFlow, detecting roofs, containers, and tractors\. See where SAM3 holds up\.
- [Spatial Data Processing Platforms: A Comparison of Enterprise and Cloud\-Native Options](https://wherobots.com/blog/spatial-data-processing-platforms.md): Compare PostGIS, Snowflake, Databricks, BigQuery GIS, Sedona, and Wherobots for spatial data processing at scale\. Find the right platform for your workload\.
- [How We Delivered “Fields of The World” with RasterFlow: A Planetary\-Scale GeoAI Pipeline](https://wherobots.com/blog/fields-of-the-world-rasterflow-geoai-pipeline.md): Learn how RasterFlow powered the Fields of the World global release, running satellite compositing, model inference, and vectorization as one GeoAI pipeline across 348 TB of data\.
- [Spatial Data Pipeline Architecture: PostGIS and Wherobots Together](https://wherobots.com/blog/spatial-data-pipeline-architecture-postgis-wherobots.md): A spatial data pipeline architecture needs more than one tool\. This guide covers the Bronze, Silver, and Gold layer approach using Wherobots and PostGIS\.
- [Iceberg v3 Gets Native Geo Types\. It’s More Than a Format Upgrade](https://wherobots.com/blog/iceberg-geospatial-types-v3.md): Iceberg v3 geospatial types bring native geometry and geography to the open lakehouse\. What changed, how Wherobots designed and contributed the spec, and what it means for spatial data across engines\.
- [Take\-aways from the 2026 Geospatial Embeddings Workshop at Clark University](https://wherobots.com/blog/clark-embeddings-workshop.md): Take\-aways from a workshop at Clark University to set standards for storing and sharing geospatial embeddings\.
- [Introducing developer tools that let AI build with physical world data](https://wherobots.com/blog/spatial-ai-coding-tools.md): New spatial AI coding tools from Wherobots: an MCP server, VS Code extension, and CLI for geospatial development\. Get started free with a 30\-day trial\.
- [How Agricultural Fields Change in AlphaEarth Foundations](https://wherobots.com/blog/alphaearth-foundations-agriculture-change-detection.md): Detect crop rotation and field\-level change in AlphaEarth Foundations satellite embeddings using PCA, cosine distance, and Zarr mosaics with RasterFlow\.
- [Mobility Data Processing at Scale: Why Traditional Spatial Systems Break Down](https://wherobots.com/blog/mobility-data-processing-traditional-systems.md): Spatial databases and distributed frameworks were not built for mobility data\. Here is why they fail and what a modern spatial data architecture does differently\.
- [PostGIS vs Wherobots: What It Actually Costs You to Choose Wrong](https://wherobots.com/blog/spatial-database-cost-comparison-postgis-vs-wherobots.md): PostGIS works for apps\. Wherobots is built for scale\. See which spatial architecture fits your workload, and what each one actually costs to run at the enterprise level\.
- [Streaming Spatial Data into Wherobots with Spark Structured Streaming](https://wherobots.com/blog/streaming-spatial-data-into-wherobots-with-spark-structured-streaming.md): I've been doing geospatial work for over twenty years now\.
- [WherobotsDB is 3x faster with up to 45% better price performance](https://wherobots.com/blog/wherobotsdb-is-3x-faster-with-up-to-45-better-price-performance.md): Explore how WherobotsDB spatial engine enhances spatial data intelligence, accelerating queries and improving decision making for various industries\.
- [Raster Processing at Scale: The Out\-of\-Database Architecture Behind WherobotsDB](https://wherobots.com/blog/raster-processing-at-scale-out-of-database-architecture-wherobotsdb.md): Learn how WherobotsDB's out\-of\-database architecture processes terabyte\-scale satellite imagery, elevation models, and sensor data at scale, enabling zonal statistics, raster algebra, and planetary\-scale AI inference without custom infrastructure\.
- [PostGIS, Wherobots, and the Spatial Data Lakehouse: A Strategic Guide for Leaders](https://wherobots.com/blog/postgis-wherobots-spatial-data-lakehouse-guide.md): Not sure whether PostGIS or Wherobots fits your stack? This guide breaks down each spatial architecture so you can build smarter and spend less\.
- [It takes 15 minutes for the Caltrain to get from Sunnyvale to SAP Center](https://wherobots.com/blog/ai-agents-spatial-analytics-15-minute-train-ride.md): On a 15 minute Caltrain ride from Sunnyvale to San Jose, I asked our MCP server a simple question: how many bus stops are in Maryland? What happened next shows how AI agents are transforming spatial analytics from days of work into minutes of autonomous reasoning\.
- [Wherobots and Felt Partner to Modernize Spatial Intelligence](https://wherobots.com/blog/modern-spatial-intelligence-stack-wherobots-felt.md): Learn how Wherobots and Felt power a modern spatial intelligence stack—replacing legacy GIS with AI\-enabled, collaborative, cloud\-native spatial analytics at scale\.
- [Scaling Spatial Analysis: How KNN Solves the Spatial Density Problem for Large\-Scale Proximity Analysis](https://wherobots.com/blog/scaling-spatial-analysis-how-knn-solves-the-spatial-density-problem-for-large-scale-proximity-analysis.md): Learn how KNN solves the spatial density problem that breaks traditional ST\_DWithin queries at scale\. Includes SQL patterns, benchmarks, and cost analysis\.
- [Wherobots brought modern infrastructure to spatial data in 2025](https://wherobots.com/blog/wherobots-brought-modern-infrastructure-to-spatial-data-in-2025.md): Wherobots’ 2025 recap: advancing spatial data infrastructure, open standards, and cloud integrations to enable scalable AI on physical world data in 2026\.
- [The Medallion Architecture for Geospatial Data: Why Spatial Intelligence Demands a Different Approach](https://wherobots.com/blog/geospatial-medallion-architecture.md): Medallion architecture organizes a lakehouse into Bronze, Silver, and Gold layers\. Learn how to adapt each layer for geospatial data with Iceberg and GeoParquet\.
- [Introducing RasterFlow: a planetary scale inference engine for Earth Intelligence](https://wherobots.com/blog/rasterflow-earth-observation-inference-engine.md): RasterFlow is a planetary\-scale inference engine for Earth Observation data\. Perform raster mosaicking, run geospatial AI models, and export insights to Apache Iceberg tables\.
- [Wherobots and Taylor Geospatial Engine Bring Fields\-of\-the\-World Models to Production Scale](https://wherobots.com/blog/fields-of-the-world-taylor-geospatial-engine-agricultural-ai.md): Wherobots and the Taylor Geospatial Engine scale Fields of the World models using earth observation data for agricultural AI\.
- [How Aarden\.ai Scaled Spatial Intelligence 300× Faster for Land Investments with Wherobots](https://wherobots.com/blog/aarden-ai-geospatial-intelligence-wherobots-case-study.md): Discover how Aarden\.ai scaled geospatial intelligence for land investments 300× faster with Wherobots — transforming spatial data into business insights\.
- [Your Perfect Week for Geospatial at AWS re:Invent 2025](https://wherobots.com/blog/your-perfect-week-geospatial-awsreinvent-2025.md): Here's the guide to your perfect week for geospatial at AWS re:Invent\. Don't miss the spatial data sessions and the Geo Party\!
- [Introducing wkls: A Python Library for Instantly Accessing Global Administrative Boundaries](https://wherobots.com/blog/wkls-python-global-administrative-boundaries.md): Instantly access 625K\+ global administrative boundaries with wkls, a Python library for seamless geospatial data and analysis\.
- [How to Use PMTiles with the Esri JavaScript API \(ArcGIS Maps SDK\)](https://wherobots.com/blog/use-pmtiles-esri-javascript-api-arcgis.md): Learn how to use PMTiles with the Esri JavaScript API\. Follow this step\-by\-step guide to serve PMTiles in ArcGIS Maps SDK using a lightweight tile server
- [Introducing Scalability for GeoPandas in Apache Sedona](https://wherobots.com/blog/scaling-geopandas-apache-sedona.md): Discover the GeoPandas API for Apache Sedona\. Scale geospatial analysis in Python with distributed computing, lazy loading, and parallel performance\.
- [Introducing SedonaDB and SpatialBench for Apache Sedona](https://wherobots.com/blog/sedonadb-spatialbench-spatial-query-engine-apache-sedona.md): SedonaDB is the query engine that gets spatial data support right\. Written in Rust, it's open\-source, blazing fast, and lightweight\.
- [Wherobots Spatial Intelligence Engine Integrates with Databricks Unity Catalog for Spatial Data](https://wherobots.com/blog/spatial-intelligence-engine-databricks.md): Wherobots integrates with Databricks Unity Catalog for advanced geospatial analytics\. Get 20x faster performance, 60% cost savings, and 300\+ spatial functions for raster and vector data\.
- [Tutorial: How to Use GERS IDs in Wherobots for Geospatial Data Integration](https://wherobots.com/blog/wherobots-gers-ids-tutorial-geospatial-integration.md): Follow this tutorial to match non\-GERS datasets to Overture Maps GERS IDs in Wherobots\. Learn GERS matching functions, scalable Apache Sedona processing, and methods for seamless cross\-dataset geospatial integration\.
- [Raster Spatial Joins at Scale: Google Earth Engine and BigQuery vs Apache Sedona and Wherobots](https://wherobots.com/blog/raster-spatial-joins-at-scale-google-earth-engine-bigquery-vs-apache-sedona-wherobots.md): Apache Sedona completed a state\-scale zonal statistics analysis that BigQuery could not finish, and ran 13x faster on a metro\-scale test\. See the full benchmark, architectural comparison, and decision guide for large\-scale raster\-vector spatial joins\.
- [Dekart Supports Wherobots as a Spatial SQL Engine](https://wherobots.com/blog/dekart-supports-wherobots-as-a-spatial-sql-engine.md): Leverage WherobotsDB as a powerful Spatial SQL Engine to run fast spatial queries and visualize results instantly with the Dekart platform\.
- [Exploring the Foursquare Open Places Data with Wherobots](https://wherobots.com/blog/exploring-the-foursquare-open-places-data-with-wherobots.md): Learn how to access, query, and visualize Foursquare’s Open Places dataset using Wherobots\. In this tutorial, we analyze coffee shop distribution with a choropleth map—perfect for exploring POI data and spatial insights\.
- [Advancing the Integration of Map Data via Overture’s Global Entity Reference System and Wherobots](https://wherobots.com/blog/overtures-global-entity-reference-system-generally-available.md): The general availability of Overture’s Global Entity Reference System \(GERS\) makes it a lot easier to build intelligence about features of our physical world\. What is GERS?You can think of a GERS as a system for applying a unique key to physical features in the world\. Overture assigns GERS IDs to millions of features in their data products, such as office buildings, highways, countries, rivers, schools, and more\.
- [Wherobots received its SOC 2 Type 2 attestation](https://wherobots.com/blog/wherobots-received-its-soc-2-type-2-attestation.md): Wherobots received its SOC 2 Type 2 attestation report, reinforcing our commitment to data security and privacy for our customers\.
- [The Spatial Intelligence Newsletter: GeoPandas, Isochrones, Iceberg GEO, SAM2 and More](https://wherobots.com/blog/spatial-intelligence-newsletter-geopandas-isochrones-iceberg-geo-sam2.md): In the latest edition of the Spatial Intelligence Newsletter, we're covering GeoPandas, Isochrones, Iceberg GEO, SAM2 and more\.
- [Enabling Meta’s SAM 2 model for Geospatial AI on satellite imagery](https://wherobots.com/blog/sam-2-model-geospatial-ai-satellite-imagery.md): Explore Meta's SAM 2 model for Geospatial AI with Wherobots Raster Inference to enhance object detection in satellite imagery\.
- [Wherobots, Sedona, and GeoPandas are better together](https://wherobots.com/blog/wherobots-sedona-and-geopandas-are-better-together.md): Learn how Sedona and GeoPandas integrates with Wherobots for powerful geospatial data computation\. Find out how they work better together\.
- [Wherobots, the Spatial Intelligence Cloud, is Now Available in AWS Europe](https://wherobots.com/blog/wherobots-now-available-in-aws-europe.md): Now available in AWS Europe \(Ireland\), Wherobots is a cloud\-native platform for fast, cost\-effective geospatial data processing\. Built for spatial intelligence, it supports open\-source tools like Apache Sedona and meets EU data residency requirements\. Start your free trial on AWS Marketplace today\.
- [Spatial Intelligence Newsletter: Location Intelligence w/ Isochrones, Overture Places, Cloud\-Native Geospatial, Iceberg and More](https://wherobots.com/blog/spatial-intelligence-newsletter-isochrones-overture-places-apache-iceberg-geospatial.md): In this month's newsletter, explore the benefits of Apache Iceberg, spatial joins, cloud\-native geospatial, isochrones and more\.
- [Location Intelligence with Isochrones: A Complete Guide](https://wherobots.com/blog/scale-location-intelligence-new-functions-overture-dataset-isochrones.md): Complete guide to isochrone analysis: Generate millions of travel\-time polygons for data\-driven site selection, emergency planning, and risk assessment\.
- [Benefits of Apache Iceberg for geospatial data analysis](https://wherobots.com/blog/benefits-of-apache-iceberg-for-geospatial-data-analysis.md): Boost geospatial analytics with Apache Iceberg: unlock fast file listing, automatic small\-file compaction \& efficient merge\-on\-read operations for spatial data\.
- [The Spatial Intelligence Newsletter: Map Matching, Spatial Joins, ML for EO, Cloud\-Native Geospatial and More](https://wherobots.com/blog/march-spatial-intelligence-newsletter-cloud-native-geospatial-and-more.md): The latest updates on Wherobots, Apache Sedona and Geospatial Data\. Topics for this month include map matching, spatial joins, cloud\-native geospatial and more\.
- [Iceberg GEO: Technical Insights and Implementation Strategies](https://wherobots.com/blog/iceberg-geo-technical-insights-and-implementation-strategies.md): GEO data types in Iceberg, explained: design, key features, and how to implement spatial types in Apache Iceberg\.
- [Apache Iceberg and Parquet now support GEO](https://wherobots.com/blog/apache-iceberg-and-parquet-now-support-geo.md): Apache Iceberg and Parquet now support native geospatial types, connecting Wherobots, PostGIS, Sedona, Databricks, and Snowflake to one table format\.
- [Wherobots 2024 accomplishments, and what’s on\-deck in 2025](https://wherobots.com/blog/reflecting-on-wherobots-accomplishments-2024.md): 2024 was a transformative year for Wherobots\. Our mission to revolutionize how geospatial data is used took significant strides forward, positively impacting our customers and industry\. Over the past year, we more than tripled the size of our team and successfully closed a $21\.5M Series A funding round\. We expanded accessibility to Wherobots’ industry\-leading geospatial query performance, integrated Wherobots into the native AWS buying experience, and unveiled groundbreaking features like Raster Inference, Map Matching, and GeoStats—empowering users to create scalable geospatial solutions like never before\.
- [Wherobots Raster Inference is GA with Support for Bring Your Own Model](https://wherobots.com/blog/wherobotsai-raster-inference-is-ga.md): We are excited to announce that Wherobots Raster Inference is now generally available\! Raster Inference is a serverless, planetary\-scale computer vision solution that extracts meaningful insights from aerial imagery \(raster data\) sources, such as satellites or drones, and puts these insights at the fingertips of data scientists and developers\.
- [Building a Spatial Data Lakehouse](https://wherobots.com/blog/building-a-spatial-data-lakehouse.md): How does Apache Iceberg based Havasu redefine data management for spatial data lakehouse architectures? Efficiently store, query, and analyze massive geospatial datasets with performance, scalability, and cost\-effectiveness in mind\.
- [Wherobots is ready for AWS workloads](https://wherobots.com/blog/wherobots-is-ready-for-aws-workloads.md): Wherobots is now live on the AWS Marketplace with pay\-as\-you\-go pricing\. AWS customers can start a 30\-day free trial, covering up to $400 in usage of the Wherobots Professional Edition\. Easily build advanced geospatial solutions on AWS, with seamless integration into private or public Amazon S3 buckets\. Ideal for customers with AWS spend commitments, Wherobots simplifies spatial data analytics and accelerates innovation in the cloud\.
- [Announcing Our 21\.5M Series A :: Unlocking Answers to Planetary\-scale Questions\.](https://wherobots.com/blog/unlocking-answers-to-planetary-scale-questions.md): To enable our mission, we’re partnering with leading investors in the technology space and have raised $21\.5M in Series A funding—led by Felicis, with continued support from Wing Venture Capital and Clear Ventures and participation from JetBlue Ventures and P7 Ventures\. Aydin Senkut, Founder and Managing Partner at Felicis will also be joining Wherobots’ Board of Directors together with Peter Wagner from Wing Venture Capital\. We are committed to constantly improving our technology to process and analyze geospatial data faster and more efficiently and this funding will accelerate our product development and go\-to\-market operations\.
- [Accelerating Vector and Raster Analysis at GeoPostcodes](https://wherobots.com/blog/accelerating-geospatial-analysis-wherobots-geopostcodes.md): How long is too long to wait for a data set to process? In the fast\-paced world of data as a service, efficiency isn't just a nice\-to\-have; it's essential\. But for GeoPostcodes, previous updates to the global population movement datasets took about 39 days\. This was running on a headless QGIS instance in combination with PostGIS, combining population rasters with postal code boundaries\.
- [Overture Data In Wherobots Spatial Data Catalog](https://wherobots.com/blog/overture-data-in-wherobots-spatial-data-catalog.md): Wherobots makes Overture data easy to access \& analyze\. Get optimized performance with Havasu Iceberg for powerful geospatial visualizations\.
- [This Month in Apache Sedona: November Edition](https://wherobots.com/blog/this-month-in-apache-sedona-november-edition.md): Welcome to the November edition of This Month in Apache Sedona\! In this issue, you'll find the latest news about Apache Sedona and Wherobots\. Learn about our newest release, which includes KNN Join, GeoStats, and DataFrame\-based readers\.
- [How to shift Apache Sedona on Spark workloads to WherobotsDB](https://wherobots.com/blog/shifting-apache-sedona-to-wherobotsdb.md): Seamlessly transition your Apache Sedona workflows to WherobotsDB\. 100% code\-compatible, simplified cluster setup, and enhanced geospatial capabilities\. Learn how to migrate today\!
- [Introducing kNN Join for Wherobots and Apache Sedona](https://wherobots.com/blog/introducing-knn-join-for-wherobots-and-apache-sedona.md): WherobotsDB and Apache Sedona 1\.7\.0 now support Exact and Approximate kNN Joins\. Learn how ST\_KNN and ST\_AKNN work, when to use each, and how they outperform PostGIS at scale\.
- [Introducing GeoStats for Wherobots and Apache Sedona](https://wherobots.com/blog/introducing-geostats.md): Discover GeoStats, a machine learning and statistical toolbox for Wherobots and Apache Sedona users\! With GeoStats, you can easily identify critical patterns in geospatial datasets such as hotspots and anomalies, and quickly get critical insights from large scale data\.
- [What is Apache Sedona?](https://wherobots.com/blog/what-is-apache-sedona.md): Apache Sedona is an open\-source cluster computing system for processing large\-scale spatial data on Apache Spark, Flink, and Snowflake\. Learn how it works, key use cases, and how to get started\.
- [Announcing SAML Single Sign\-On \(SSO\) Support](https://wherobots.com/blog/announcing-saml-single-sign-on-sso-support.md): Wherobots Cloud now supports SAML Single Sign\-On \(SSO\) for Professional Edition customers, providing simplified login processes and stronger security features tailored for businesses handling sensitive data\. Learn how SAML SSO can benefit your organization\.
- [Wherobots and PostgreSQL \+ PostGIS: A Synergy in Spatial Analysis](https://wherobots.com/blog/wherobots-postgresql-postgis-better-together.md): Wherobots and PostgreSQL \+ PostGIS serve different purposes in spatial data workflows\. Learn when to use each, how they integrate, and see benchmark data comparing WherobotsDB vs PostGIS at scale\.
- [Wherobots Joins Overture, Winning The Taco Wars, Spatial SQL API, Geospatial Index Podcast – This Month In Wherobots](https://wherobots.com/blog/wherobots-joins-overture-taco-wars-spatial-sql-api-geospatial-index-podcast.md): Welcome to This Month In Wherobots the monthly developer newsletter for the Wherobots \& Apache Sedona community\! This month we have news about Wherobots and the Overture Maps Foundation, a deep dive on new Wherobots Cloud features like raster inference, generating vector tiles, and the Spatial SQL API, plus a look at retail cannibalization analysis for the commercial real estate industry\.
- [Wherobots Joins Overture Maps Foundation As Contributing Member To Enable Open Cloud\-Native Geospatial Intelligence](https://wherobots.com/blog/overture-maps-foundation-wherobots-new-member-cloud-native-geospatial-intelligence.md): Wherobots is excited to share that we have officially joined Overture Maps Foundation as a Contributing Member to support the next generation of planetary\-scale open map data\. Wherobots believes wholeheartedly in Overture’s mission to bring open global\-scale map data to the world while leveraging cloud\-native technologies to enable efficient and accessible usage of these datasets\.
- [Generate Global PMTiles in 26 Minutes: Processing 2\.3B Overture Maps Data](https://wherobots.com/blog/generate-pmtiles-overture-maps-wherobotsdb-vtiles.md): Generate global PMTiles from 2\.3B Overture Maps features in 26 minutes using WherobotsDB VTiles, distributed computation, and feature filtering\.
- [WherobotsAI Map Matching: Turn GPS Tracks into Road\-Aligned Trip Insights at Scale](https://wherobots.com/blog/wherobotsai-map-matching-telematics-gps-road-segments.md): Discover how Wherobots Map Matching snaps noisy GPS data into precise, road‑aligned trip insights—at planetary‑scale, 99 % cheaper than Mapbox, HERE, or Google Maps\.
- [Unlock Satellite Imagery Insights with Wherobots Raster Inference](https://wherobots.com/blog/wherobotsai-for-raster-inference.md): Run satellite and aerial imagery inference with SQL or Python using Wherobots Raster Inference and open source ML models\.
- [Quickly and Easily Create Vector Tiles with Wherobots and Overture Maps Foundation Data](https://wherobots.com/blog/vector-tile-generation-pmtiles-wherobots.md): Learn how to quickly and easily generate vector tiles in PMTiles format using Wherobots and Overture Maps Foundation data\. See how Wherobots simplifies vector tile creation for large datasets, demonstrated through NYC and NY state transportation data\.
- [🌶 Comparing taco chains :: a consumer retail cannibalization study with isochrones](https://wherobots.com/blog/real-estate-retail-cannibalization-with-isochrones.md): Using Wherobots for a Retial Cannibalization Study Comparing Two Leading Taco ChainsIn this post, we explore how to implement a workflow from the commercial real estate \(CRE\) space using Wherobots Cloud\. This workflow is commonly known as a cannibalization study, and we will be using WherobotsDB, POI data from OvertureMaps, the open source Valhalla API, and visualization capabilities offered by SedonaKepler\. What is a retail cannibalization study?In CRE \(consumer real estate\), stakeholders are often interested in questions like “If we build a new fast food restaurant here, how will its performance be affected by other similar fast food locations that already exist nearby?”\. The idea of the new fast food restaurant “eating into” the sales of other fast food restaurants that already exist nearby is what is known as ‘cannibalization’\. The main objective of studying this phenomenon is to determine the extent to which a new store might divert sales from existing stores owned by the same company or brand and evaluate the overall impact on the company's market share and profitability in the area\. Cannibalization Study in WherobotsFor this case study, we will look at two taco chains which are located primarily in Texas: Torchy’s Tacos and Velvet Taco\. In general, information about the performance of individual locations and customer demographics are often proprietary information\. We can, however, still learn a great deal about the potential for cannibalization both between these two chains as competitors, and between individual locations of each chain\. We also know, based on our own experience, these chains compete with each other\. Which taco shop to go to when we are visiting Texas is always a spicy debate\.
- [New Wherobots Cloud Features, How Overture Maps Uses Apache Sedona, Aircraft Data, \& Spatial Lakehouses](https://wherobots.com/blog/wherobots-ai-features-overture-maps-apache-sedona-flight-analytics-spatial-data-lakehouse.md): Welcome to This Month In Wherobots the monthly developer newsletter for the Wherobots \& Apache Sedona community\! In this edition we have a look at the latest Wherobots Cloud release, how the Overture Maps Foundation uses Apache Sedona to generate their data releases, processing a billion aircraft observations, building spatial data lakehouses with Iceberg Havasu, the new Apache Sedona 1\.6\.0 release, and more\!
- [Introducing WherobotsAI for planetary inference, and capabilities that modernize spatial intelligence at scale](https://wherobots.com/blog/wherobots-ai-spatial-sql-vector-tile-gen.md): We are excited to announce a preview of WherobotsAI, our new suite of AI and ML powered capabilities that unlock spatial intelligence in satellite imagery and GPS location data\. Additionally, we are bringing the high\-performance of WherobotsDB to your favorite data applications with a Spatial SQL API that integrates WherobotsDB with more interfaces including Apache Airflow\. Finally, we’re introducing the most scalable vector tile generator on earth to make it easier for teams to produce engaging and interactive map applications\. All of these new features are capable of operating on planetary\-scale data\.
- [The Spatial SQL API brings the performance of WherobotsDB to your favorite data applications](https://wherobots.com/blog/wherobots-spatial-sql-api.md): Since its launch last fall, Wherobots has raised the bar for cloud\-native geospatial data analytics, offering the first and only platform for working with vector and raster geospatial data together at a planetary scale\. Wherobots delivers a significant breadth of geospatial analytics capabilities, built around a cloud\-native data lakehouse architecture and query engine that delivers up to 60x better performance than incumbent solutions\. Accessible through the powerful notebook experience data scientists and data engineers know and love, Wherobots Cloud is the most comprehensive, approachable, and fully\-managed serverless offering for enabling spatial intelligence at scale\. Today, we’re announcing the Wherobots Spatial SQL API, powered by Apache Sedona, to bring the performance of WherobotsDB to your favorite data applications: opening the doors to a world of direct\-SQL integrations with Wherobots Cloud, bringing a serverless cloud engine that’s optimized for spatial workloads at any scale into your spatial ETL pipelines and applications, and taking your users and engineers closer to your data and spatial insights\.
- [Processing A Billion Aircraft Observations And Combining With Weather Data Using Apache Sedona On Wherobots Cloud](https://wherobots.com/blog/billions-aircraft-observations-apache-sedona-wherobots-cloud.md): In this post we take a look at combining aircraft flight data with weather data to identify potentially impacted flights using public ADS\-B data and weather data from NOAA\. Along the way we introduce the types of spatial queries available with WherobotsDB including spatial range queries, spatial kNN, and spatial joins using Spatial SQL, geospatial visualization options, working with various file formats including GeoParquet, GeoTiff, Shapefiles, and more\.
- [Making Overture Maps Data More Efficient With GeoParquet And Apache Sedona](https://wherobots.com/blog/overture-maps-data-cloud-native-geoparquet-apache-sedona.md): The latest release of Overture Maps data is now published in GeoParquet format, allowing for more efficient spatial operations when selecting subsets of the dataset and enabling interoperability with a growing ecosystem of data tooling that supports the cloud\-native GeoParquet format\. In this post we explore some of the motivations and advantages of publishing the Overture Maps data as GeoParquet as well as the process used by Overture to generate and publish a large scale geospatial dataset as GeoParquet using Apache Sedona\.
- [Raster Data Analysis, Processing Petabytes of Agronomic Data, Overview of Sedona 1\.5, and Unlocking The Spatial Frontier – This Month In Wherobots](https://wherobots.com/blog/raster-data-analysis-petabytes-agronomic-data-sedona-1-5-unlocking-spatial-frontier.md): Welcome to This Month In Wherobots, the monthly newsletter for data practitioners in the Apache Sedona and Wherobots community\. This month we’re exploring raster data analysis with Spatial SQL, processing petabytes of agronomic data with Apache Sedona, a deep dive on new features added in the 1\.5 release series, and an overview of working with files in Wherobots Cloud\.
- [Raster Data Analysis With Spatial SQL And Apache Sedona](https://wherobots.com/blog/raster-data-analysis-spatial-sql-wherobots-apache-sedona.md): Learn how to work with raster data in Sedona using Spatial SQL and some of the use cases for raster data analysis including vector / raster join operations, zonal statistics, and raster map algebra\.
- [Working With Files – Getting Started With Wherobots Cloud Part 3](https://wherobots.com/blog/working-with-files-getting-started-with-wherobots-cloud-sedonadb-part-3.md): In this post we’re going to take a look at loading and working with our own data in Wherobots Cloud as well as creating and saving data as the result of our analysis, such as the end result of a data pipeline\. We will cover importing files in various formats including CSV, GeoJSON, Shapefile, and GeoTIFF in SedonaDB, working with AWS S3 cloud object storage, and creating GeoParquet files
- [Introducing Sedona 1\.5: Making Sedona the most comprehensive \& scalable spatial data processing and ETL engine for both Raster and Vector data](https://wherobots.com/blog/introducing-sedona-1-5-making-sedona-the-most-comprehensive-scalable-spatial-data-processing-and-etl-engine-for-both-raster-and-vector-data.md): We're excited to introduce Apache Sedona's 1\.5 series, a leap forward in geospatial processing that brings essential features and enhancements\.
- [Unlocking the Spatial Frontier: The Evolution and Potential of spatial technology in Apple Vision Pro and Augmented Reality Apps](https://wherobots.com/blog/unlocking-the-spatial-frontier-the-evolution-and-potential-of-spatial-technology-in-apple-vision-pro-and-augmented-reality-apps.md): The evolution of Augmented Reality \(AR\) from the realm of science fiction to tangible, practical applications like Augmented Driving, Pokemon Go, and…
- [SedonaSnow: Apache Sedona On Snowflake, Accelerating Your GIS Pipeline, Exploring Global Fishing Watch Data With GeoParquet, and Apache Sedona 1\.5\.1 Release](https://wherobots.com/blog/sedonasnow-apache-sedona-snowflake-accelerating-gis-pipeline-geoparquet-sedona-latest-release.md): Explore SedonaSnow—Apache Sedona on Snowflake—for faster GIS pipelines, GeoParquet\-powered analytics, and highlights from the Sedona 1\.5\.1 release\.
- [Exploring Global Fishing Watch Public Data With Apache Sedona, Wherobots Cloud \& GeoParquet](https://wherobots.com/blog/exploring-global-fishing-watch-public-data-sedonadb-geoparquet.md): This post is a hands\-on look at offshore ocean infrastructure and industrial vessel activity with WherobotsDB using data from Global Fishing Watch\. We also see how GeoParquet can be used with this data to improve the efficiency of data retrieval and enable large\-scale geospatial visualization\.
- [The Wherobots Notebook Environment – Getting Started With Wherobots Cloud Part 2](https://wherobots.com/blog/wherobots-notebook-environment-getting-started-with-wherobots-cloud-sedonadb-part-2.md): Wherobots Cloud is a fully managed cloud platform that enables developers and data scientists to efficiently manage their spatial analytics and AI pipelines in the cloud\. The core of Wherobots Cloud is powered by Apache Sedona, a scalable geospatial analytics database engine\. Wherobots is built on a distributed compute architecture which enables scalable computation of massive datasets without sacrificing speed\. With an architecture that separates the compute layer from the storage layer Wherobots is truly cloud\-native\.
- [Introducing The Havasu Spatial Table Format, Wherobots 2023 In Review, Analyzing Overture Maps and Real Estate Data: This Month In Wherobots](https://wherobots.com/blog/havasu-wherobots-2023-review-analyzing-overture-real-estate-data.md): In the latest edition of This Month In Wherobots the latest highlights from the Wherobots \& Apache Sedona community include an overview of the Havasu…
- [Wherobots: 2023 Year in Review\!](https://wherobots.com/blog/wherobots-2023-year-in-review.md): 2023 has been an exceptional year for Wherobots, marked by a series of significant milestones\.
- [Havasu: A Table Format for Spatial Attributes in a Data Lake Architecture](https://wherobots.com/blog/havasu-a-table-format-for-spatial-attributes-in-a-data-lake-architecture.md): In the past decade, many organizations have been using BLOB storage \(e\.g\., AWS S3\) as a primary storage platform\.
- [Wherobots Cloud Overview – Getting Started With Wherobots Cloud Part 1](https://wherobots.com/blog/wherobots-cloud-overview.md): Learn how to get started with Wherobots Cloud, a fully scalable managed cloud platform and geospatial analytics database engine\.
- [Analyzing Real Estate Data With Apache Sedona](https://wherobots.com/blog/analyzing-real-estate-data-sedonadb.md): In a recent tutorial on the Wherobots YouTube channel we explored how to analyze real estate data using Apache Sedona and Wherobots Cloud using data from…
- [Analyzing The Overture Maps Places Dataset Using Apache Sedona, Wherobots Cloud, \& GeoParquet](https://wherobots.com/blog/analyzing-overture-maps-dataset-sedona-wherobots-cloud-geoparquet.md): Explore how to analyze the Overture Maps Places dataset using Apache Sedona, Wherobots Cloud, and GeoParquet\. Learn how GeoParquet enhances geospatial analytics and unlocks insights into urban dynamics with real\-world use cases\.
- [The Biggest Apache Sedona Release Ever, Wherobots Cloud Launch, Building Maps With Felt \& Self Service Geospatial Analytics – This Month In Wherobots](https://wherobots.com/blog/wherobots-cloud-launch-felt-maps-community-this-month-in-wherobots.md): Welcome to This Month In Wherobots where we highlight the latest goings on from the Wherobots \& Apache Sedona community\.
- [Creating Collaborative Web Maps With The Felt API And Wherobots Cloud](https://wherobots.com/blog/creating-maps-with-the-felt-api-and-wherobots-cloud.md): Explore how to create collaborative web maps with Felt, providing data using the Felt API and using Wherobots for geospatial data processing\.
- [Wherobots Cloud: The Cloud\-Native Spatial Analytics Data Platform](https://wherobots.com/blog/sedonadb-the-cloud-native-spatial-analytics-database-platform.md): Today we are excited to announce the release of WherobotsDB, a cloud\-native scalable spatial analytics database engine\.
- [Spatial Data, GeoParquet, and Apache Sedona](https://wherobots.com/blog/spatial-data-geoparquet-and-apache-sedona.md): Apache Sedona supports reading and writing GeoParquet files \- A variant of Parquet for exchanging spatial data\. Apache Sedona can perform spatial filter pushdown when running spatial range queries on GeoParquet files\. You can group your GeoParquet dataset by spatial proximity to achieve faster spatial query performance\.
- [Harnessing Overture Maps Data: Apache Sedona’s Journey from Parquet to GeoParquet](https://wherobots.com/blog/wherobots-provides-ready-to-use-spatially-indexed-overture-maps.md): We demonstrate the capabilities of Apache Sedona for working with massive Overture Maps data\. The article also shows that GeoParquet OMF data produced by Sedona can accelerate the spatial queries by 60X\. This exploration underscores Sedona's proficiency in handling scalable geospatial tasks using prevalent industry formats like Parquet and GeoParquet\.
- [Announcing Apache Sedona 1\.4 – A Giant Leap in Geospatial Processing](https://wherobots.com/blog/announcing-apache-sedona-1-4-a-giant-leap-in-geospatial-processing.md): We're exhilarated to share the launch of Apache Sedona 1\.4, signifying a transformative stage in geospatial analytics\. These successive versions introduce an array of striking new features, major enhancements, and indispensable bug fixes\.
- [Wherobots raises $5\.5 Million in seed round to build the data platform for spatial analytics \& AI](https://wherobots.com/blog/wherobots-raises-5-5-million-in-seed-round-to-build-the-data-platform-for-spatial-analytics-ai.md): We are happy to announce that we raised $5\.5 Million in seed round led by Clear Ventures and Wing VC\.

## Events
- [RasterFlow Panel](https://wherobots.com/event/rasterflow-in-production/)
- [From Pixels to Predictions at Planetary Scale: RasterFlow Public Preview](https://wherobots.com/event/pixels-to-predictions-planetary-scale-rasterflow/)
- [Getting Started with GeoAI \& Map Matching](https://wherobots.com/event/geoai-map-matching-mobility-data-aerial-imagery-webinar/)
- [Wherobots at the Data \+ AI Summit](https://wherobots.com/event/data-ai-summit-2026/)
- [Turn Satellite Data into Risk Intelligence](https://wherobots.com/event/turn-satellite-data-into-risk-intelligence/)

## Jobs
- [Senior Machine Learning Engineer \- GeoAI Platform](https://wherobots.com/careers/senior-machine-learning-engineer-geoai-platform/)
- [Senior/Staff Cloud Infrastructure Engineer \- Networking \+ Security](https://wherobots.com/careers/senior-staff-cloud-infrastructure-engineer-networking-security/)
- [Senior Account Executive \- Enterprise East](https://wherobots.com/careers/senior-account-executive-global/)

## Today's News
- [Amid Ukraine's Strikes, Fire Days at Russia's Oil Sites Rise as Its Advance Slows](https://wherobots.com/todays-news/ukraine-russia-war-2026/): Russia's oil sites had 221 fire days from Jan 1 to Oct 23, 2026, more than any year back to 2019\. Russia took 3\.1 km² of Ukraine a day, against 11\.2 in 2025\.
- [Tibet Earthquake Hit Homes That Open Map Data Doesn't Show](https://wherobots.com/todays-news/tibet-earthquake-exposure/): Tibet's Oct 22 earthquake killed at least 16\. Open maps show no building within 1 km of 40 of 42 settlements in its strong shaking\. Homes may stand unmapped\.
- [Ukraine Lost Starlink With Dozens of Satellites Overhead](https://wherobots.com/todays-news/starlink-satellites/): At least 47 Starlink satellites were over each of 7 Ukrainian cities as dishes dropped at speed\. Fires in towns far from the front show no clear rise\.
- [Super Typhoon Champi: Looking Beyond the Storm Track to Understand Its Potential Impact](https://wherobots.com/todays-news/typhoon-champi-path/): On Oct 23, 98% of Okinawa's households without power were in Ishigaki and Taketomi, where the forecast had put nearly every building in 120 km/h winds\.

## Solution Gallery
- [Part 4: Spatial Joins](https://wherobots.com/solution-gallery/part-4-spatial-joins/)
- [RasterFlow S2 Mosaic](https://wherobots.com/solution-gallery/rasterflow-s2-mosaic/)
- [RasterFlow ChangeDetection](https://wherobots.com/solution-gallery/rasterflow-changedetection/)
- [Isochrones](https://wherobots.com/solution-gallery/isochrones/)
- [Getis Ord Gi\*](https://wherobots.com/solution-gallery/getis-ord-gi/)

## Press Releases
- [Predicting Wildfire Containment with AI and Distributed Compute](https://wherobots.com/press/predicting-wildfire-containment-with-ai-and-distributed-compute/): Wildfire management is entering a new era\. As climate change drives larger and more unpredictable fire seasons, the tools used to model and predict wildfires are being reinvented from the ground up\.
- [HERE Technologies and Wherobots partner to give AI agents geospatial intelligence](https://wherobots.com/press/here-technologies-wherobots-partnership-ai-agents/): Wherobots and HERE Technologies have formed a strategic partnership to enable AI agents to understand and make precise, deterministic decisions about the physical world\.
- [Introducing Wherobots Raster Inference to Unleash Innovation with Planetary Imagery](https://wherobots.com/press/introducing-wherobots-raster-inference-to-unleash-innovation-with-earth-imagery/)
- [Wherobots' founders receive prestigious "ACM SIGSPATIAL 10\-Year Impact Award"](https://wherobots.com/press/wherobots-founders-receive-prestigious-acm-sigspatial-10-year-impact-award/)
- [Wherobots Raises $21\.5M in Series A Funding Led by Felicis to Modernize Geospatial and Climate Intelligence, Starting in the AWS Cloud](https://wherobots.com/press/wherobots-raises-21-5m-in-series-a-funding-led-by-felicis-to-modernize-geospatial-and-climate-intelligence-starting-in-the-aws-cloud/)

## Landing Pages
- [Wherobots for Spatial Data](https://wherobots.com/lp/spatial-data/)
- [Wherobots for Geospatial Data](https://wherobots.com/lp/geospatial-data/)

## Discover
- [What is a Geofence? How Geofencing Works, With Examples](https://wherobots.com/discover/geofence.md): A geofence is a virtual boundary on a map\. Learn how geofencing works, what it is used for, how legal it is, and what a test on ship positions found\.
- [What is Map Matching? GPS Traces, Methods and Examples](https://wherobots.com/discover/map-matching.md): Map matching places each GPS record on the road a vehicle drove\. Learn how it works, how hidden Markov models do it, and what a test on real drives found\.
- [Geospatial Big Data: Why Analytics Is Hard to Scale](https://wherobots.com/discover/geospatial-analytics-at-scale.md): Why geospatial analytics is hard to scale: data volume, mixed vector and raster formats, many coordinate systems, spatial joins, and pipeline upkeep\.
- [What is an Isochrone? Isochrone Maps and Travel Time](https://wherobots.com/discover/isochrone.md): An isochrone is the area you can reach from a place within a set travel time\. Learn how isochrone maps are made and how they differ from a simple radius\.
- [What is a Geospatial Database? Definition, Examples](https://wherobots.com/discover/geospatial-database.md): A geospatial database stores shapes, indexes them by location and runs spatial SQL queries\. Learn the definition, examples, and how to choose one by workload\.
- [What is a Map Projection? Types, Distortion, Examples](https://wherobots.com/discover/map-projection.md): A map projection turns the curved Earth into a flat map and distorts area, shape, distance or direction\. Learn the types, examples, and how to choose one\.
- [What is Geospatial Intelligence? GEOINT Defined, Examples](https://wherobots.com/discover/geospatial-intelligence.md): Geospatial intelligence \(GEOINT\) fuses imagery with map data to describe activity on earth\. Definition, history, examples, and a vessel detection test\.
- [What is Ground Truth Data? Meaning and How to Check AI](https://wherobots.com/discover/ground-truth.md): Ground truth is data collected by direct observation at a known place and time\. How it calibrates sensors, scores maps, trains AI, and where it falls short\.
- [What is a World Model? How AI Predicts the Physical World](https://wherobots.com/discover/world-model.md): A world model predicts the next state of an environment from a state and an action\. How it works, types, examples, and reinforcement learning on real drive logs\.
- [What is a Context Engine? Why Physical World Data Needs One](https://wherobots.com/discover/context-engine.md): A context engine computes, stores, and serves the context AI agents use\. How it works, examples, and why physical world data needs spatial relations\.
- [What Is the Partitioning Tax? Tiles, Seams, and Reruns](https://wherobots.com/discover/partitioning-tax.md): The partitioning tax is the cost of tiling spatial data that outgrows one machine: tile loops, edge errors at seams, and reruns\. See it on Colorado data\.
- [What is Context Engineering for Physical AI?](https://wherobots.com/discover/context-engineering.md): Context engineering sets what an AI model receives at each step\. How it works, how it compares to prompt engineering and RAG, and how it applies to places\.
- [What is an Ontology? Definition, Parts, Spatial Ontologies](https://wherobots.com/discover/ontology.md): An ontology is a formal model of the things in a domain and how they relate\. Learn its parts, ontology vs taxonomy vs knowledge graph, and spatial ontologies\.
- [What is H3? Uber’s Hexagonal Spatial Index](https://wherobots.com/discover/h3.md): H3 is Uber's open\-source hexagonal grid that gives every place on Earth a 64\-bit cell ID\. How the H3 index works, its 16 resolutions, and H3 vs S2 in SQL\.
- [What is Geospatial Data? Types, Formats, Examples](https://wherobots.com/discover/geospatial-data.md): Geospatial data ties information to a location on Earth\. Learn its types \(vector, raster, point clouds, trajectories\), formats, sources, and examples\.
- [What is Geospatial Analysis? Methods and Examples](https://wherobots.com/discover/geospatial-analysis.md): Spatial analysis, or geospatial analysis, studies locations and patterns in geospatial data\. Learn the core methods, hot spots, examples, and spatial SQL\.
- [What is a Coordinate Reference System? CRS, EPSG](https://wherobots.com/discover/coordinate-reference-system.md): A coordinate system in GIS, or coordinate reference system \(CRS\), ties coordinates to places on Earth\. Geographic vs projected, EPSG, WGS 84, and UTM\.
- [What is the Havasu Catalog? A Spatial Data Catalog](https://wherobots.com/discover/havasu-catalog.md): The Havasu Catalog is the Wherobots spatial data catalog: open data in Apache Iceberg tables with geometry types, time travel, and spatial pruning\.
- [What is Satellite Imagery Analysis? AI, Tasks, Uses](https://wherobots.com/discover/satellite-imagery-analysis.md): Satellite imagery analysis turns satellite and aerial pixels into maps, counts, and alerts: detecting, segmenting, and measuring objects in imagery\.
- [What is Land Cover Classification? Classes and Data](https://wherobots.com/discover/land-cover-classification.md): Land cover classification labels the Earth's surface as water, forest, crops, or pavement from imagery\. Classes, NLCD and WorldCover data, change mapping\.
- [What is a Building Footprint? Data, Sources, Uses](https://wherobots.com/discover/building-footprint.md): A building footprint is the outline a building covers on the ground\. How footprint data is made from imagery, open sources such as Overture, and its uses\.
- [What is Probable Maximum Loss \(PML\)? EP Curves, AAL](https://wherobots.com/discover/probable-maximum-loss.md): Probable maximum loss \(PML\) is the largest loss expected from a property or portfolio\. PML in insurance and real estate, OEP vs AEP, AAL, and TVaR\.
- [What is POI Data? Points of Interest Data, Sources](https://wherobots.com/discover/poi-data.md): POI data maps the places people visit: name, category, address, hours, and location\. Open and commercial sources, deduplication, quality, and uses\.
- [What Is a Spatial Join? Predicates, Types, and SQL](https://wherobots.com/discover/spatial-join.md): A spatial join matches rows by location\. Learn spatial join predicates, inner and outer joins, distance, KNN, and raster\-vector joins, with geospatial SQL\.
- [What is Sentinel\-2? Bands, Resolution, Data Access, Uses](https://wherobots.com/discover/sentinel-2.md): Sentinel\-2 is the free Copernicus optical satellite mission with 13 bands at 10, 20, and 60 m\. Bands, revisit time, L1C vs L2A, data download, and uses\.
- [What is Synthetic Aperture Radar \(SAR\)? Bands, Data, Uses](https://wherobots.com/discover/synthetic-aperture-radar.md): Synthetic aperture radar \(SAR\) images Earth with microwaves through cloud and darkness\. How SAR works, bands, polarization, Sentinel\-1, NISAR, and uses\.
- [What is Stochastic Modeling? Definition, Types, Examples](https://wherobots.com/discover/stochastic-modeling.md): Stochastic modeling forecasts outcomes from random variables\. Stochastic vs deterministic models, Monte Carlo simulation, examples, and catastrophe risk\.
- [Raster vs\. Vector Data: Differences, Formats, and Uses](https://wherobots.com/discover/raster-vs-vector-data.md): Raster data is a grid of pixels; vector data is points, lines, and polygons\. Compare the two GIS data models, their formats, uses, and how to combine them\.
- [What is NDVI? Formula, Values, and Uses](https://wherobots.com/discover/ndvi.md): NDVI measures vegetation health from red and near\-infrared light\. The formula, Sentinel\-2 and Landsat bands, what NDVI values mean, and how to calculate it\.
- [What is Parcel Data? Parcel Numbers, Boundaries, Sources](https://wherobots.com/discover/parcel-data.md): Parcel data maps every piece of land: boundary, parcel number \(APN\), owner, land use, and value\. What it contains, where it comes from, and how to use it\.
- [What is Physical AI? Definition, Examples, How It Works](https://wherobots.com/discover/physical-ai.md): Physical AI is AI that perceives, reasons, and acts in the physical world\. How it works, robots, world models, examples, and the spatial data it runs on\.
- [What is LiDAR Data? How It Works, Formats, and Sources](https://wherobots.com/discover/lidar-data.md): LiDAR data is a 3D point cloud from laser pulses that maps ground, trees, and buildings\. How it works, LAS and COPC formats, USGS 3DEP downloads, and uses\.
- [What is Landsat? Satellites, Bands, Data Access](https://wherobots.com/discover/landsat.md): Landsat is the USGS and NASA satellite program that has imaged Earth's land at 30 m since 1972\. Missions, bands, Collection 2, and how WherobotsDB reads it\.
- [What is Hyperspectral Imaging? vs Multispectral](https://wherobots.com/discover/hyperspectral-imagery.md): Hyperspectral imaging records hundreds of narrow spectral bands per pixel, enough to identify materials by their spectra\. Sensors, multispectral, WherobotsDB\.
- [What is the HRRR Model? NOAA Rapid Refresh Forecast](https://wherobots.com/discover/hrrr.md): The HRRR model is NOAA's hourly 3 km weather forecast for the US: run schedule, variables, GRIB2 and Zarr data on AWS, and HRRR vs RAP, GFS, and NAM\.
- [What is a GeoTIFF? Format, Tags, and COG](https://wherobots.com/discover/geotiff.md): A GeoTIFF is a TIFF image with embedded georeferencing tags that place each pixel on Earth\. Structure, Cloud Optimized GeoTIFF, WherobotsDB\.
- [What is Geospatial AI? GeoAI Models, Agents, Examples](https://wherobots.com/discover/geospatial-ai.md): Geospatial AI applies machine learning and AI agents to imagery, maps, and location data\. How GeoAI works, foundation models, examples, and research\.
- [What is a Flood Risk Map? Zones, Depth Grids, Data](https://wherobots.com/discover/flood-risk-data.md): A flood risk map shows where flooding is likely, how deep and how often\. FEMA zones, flood types, data sources, HAND, and a buildings query in SQL\.
- [What is Earth Observation Data? Types, Sources](https://wherobots.com/discover/earth-observation-data.md): Earth observation data is imagery and measurements of the planet's surface and atmosphere from satellites and aircraft\. Types, sources, formats, WherobotsDB\.
- [What is a Digital Elevation Model? DEM vs DSM vs DTM](https://wherobots.com/discover/digital-elevation-model.md): A digital elevation model is a raster of heights\. DEM vs DSM vs DTM, free DEM data from Copernicus GLO\-30, SRTM, and USGS 3DEP, datums, and slope\.
- [Data Center Site Selection: Criteria, Data Layers, Process](https://wherobots.com/discover/data-center-site-selection.md): Data center site selection criteria and process: power, transmission, fiber, water, hazards, land, latency, and incentives, with a GIS MCDA screen in SQL\.
- [What is Catastrophe Modeling? Cat Models Explained](https://wherobots.com/discover/catastrophe-modeling.md): Catastrophe modeling estimates insured losses from hurricanes, floods, earthquakes and wildfires\. The four modules, AAL, EP curves, vendors and an example\.
- [What is Change Detection in Satellite Imagery?](https://wherobots.com/discover/change-detection.md): Change detection compares satellite or aerial images of the same place over time to find what changed\. Methods, data needs, and how RasterFlow runs it\.

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