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We talk about geospatial data a lot and how transformative it can be when used and applied to solve problems - but what exactly do we mean when we say 'geospatial'? Geovation's Innovation Researcher, Bryn Medd-Sygrove explores the world of #geospatial data, its applications, and the practical applications we're already seeing in a world powered by data-driven decision-making: https://ow.ly/k2bi50Q3oqz

In the future, with the significant role played by AI-driven prompts in geospatial data analysis and visualization, I wonder if our demand for colleagues such as GIS Analysts, technicians, and junior developers will decrease. Also, you can reach out #GeoGPT 's showcase demo video on this link below: https://lnkd.in/d7-GTxKE #CustomGPT #GeoGPT #ArtificialIntelligence #GeospatialData

Using #GenAI to easily access complex #data and #geospatial analysis results. For our customer NEO BV Netherlands we enabled searching through databases with a TB of satellite images for #EarthObservation with the #SuperAPI and #GenAI front end. Curious to see the details? Find out more in our blog.

Using #GenAI to easily access complex #data and #geospatial analysis results. For our customer NEO BV Netherlands we enabled searching through databases with a TB of satellite images for #EarthObservation with the #SuperAPI and #GenAI front end. Curious to see the details? Find out more in our blog.

🌐 Our team is thrilled to participate in this year’s Esri Partner Conference at the Palm Springs Convention Center on March 10 and 11. Geospatial analysis is core to Striveworks. Our strength with unstructured data makes us a natural partner for enhancing GIS workflows with machine learning. Whether you need a complete no-code solution for object detection or a flexible MLOps workspace to remediate a degraded CV model, we have tools to help. Schedule time now to learn how we can transform your geospatial workflows. 👉 Link in Comment #AI #MachineLearning #GIS #ArcGIS #Esri #ComputerVision

🛰️ Transforming Geospatial Data Visualisation: Fused's Game-Changing Approach Unlock the full potential of geospatial data with Fused, a revolutionary serverless platform that streamlines satellite imagery visualisation and processing. 🌐 Read our latest blog, where we delve into some of its remarkable capabilities to make informed decisions in real time! ⚡ Disrupting the traditional methods of data visualisation, Fused significantly reduces the processing time of satellite imagery and geospatial data from hours to seconds! 🕒 This rapid visualisation empowers organisations to monitor and analyse data across various sectors like agriculture, environmental conservation, and urban planning. 🌱 Read more: https://buff.ly/3TAeIjh In what ways do you think Fused could revolutionise your industry? Share your thoughts, and let's start the conversation! 💡 #geospatialdata #fusedplatform #satelliteimagery #datavisualisation #realtimedecisionmaking

With growing skill gaps and other issues in the geospatial industry, the emergence of GeoAI could be part of the solution, writes Frank de Morsier. Picterra #GeoAI #artificialintelligence #geospatialdata

We're biased of course but we believe GeoAI to be crucial for the future of the geospatial industry. Check out Frank de Morsier's feature in Geo Week to learn more!

Geospatial annotations involve attaching metadata to digital maps, encompassing details such as geographic locations, physical boundaries, and attributes of specific places. With rising demand for precise geospatial data in urban planning, environmental monitoring, logistics, and other sectors, ensuring the precision of these annotations is paramount. In this discussion, we delve into optimal strategies for enhancing the accuracy of geospatial annotations, essential for informed decision-making grounded in geospatial data. #geospatialannotation #artificialintelligence #datalabeling #machinelearning #aiforgood #dataannotation #ml https://lnkd.in/dXzz7XUV

Powers and Limitations of H3 Have you heard about H3? It is a geospatial indexing system that uses a hexagonal grid structure to partition the surface of the Earth. Developed by Uber, this system organizes the Earth's surface into hexagons of varying sizes, creating a hierarchical structure where each smaller hexagon fits perfectly inside a larger one across multiple levels of granularity. This hierarchical, hexagonal tessellation is particularly useful because it offers several advantages over traditional square grid systems used in many other geospatial indexing systems. Powers of H3: ✔ Uniform Spatial Analysis: Hexagons reduce edge effects and provide consistent distances between points, improving spatial analysis uniformity, crucial for environmental modeling and resource distribution. ✔ Enhanced Data Visualization: Hexagons allow for smoother visual representations, minimizing visual distortions in mapping dense urban areas or detailed geographic features. ✔ Efficient Computation: Hexagons cover areas more efficiently than squares, reducing computational overhead and speeding up spatial operations like distance calculations and spatial joins. Limitations of H3: ❗ Non-Hexagonal Requirements: H3 may struggle with irregularly shaped boundaries like political borders or natural features, which do not conform neatly to a hexagonal grid. ❗ Granularity Constraints: With predefined granularity levels, H3 may not match the specific resolution needs of all projects, potentially leading to inefficiencies. ❗ Dynamic Data Handling: H3's static grids may not be ideal for applications requiring real-time tracking of highly dynamic objects. ❗ Complex Spatial Queries: Advanced spatial operations that require sophisticated querying capabilities might exceed H3's optimal use cases. Despite its limitations, H3's design for enhancing geospatial data management positions it as a promising tool in the future of spatial analytics. As the demand for precise and efficient geospatial data processing grows, especially in fields like urban planning, environmental management, and public safety, the integration of H3 with other technologies could address its current constraints. Future advancements may see H3 becoming part of a hybrid approach, combined with other geospatial tools to leverage the strengths of each, paving the way for more sophisticated spatial data applications. Here is an interesting article for you to explore H3: https://lnkd.in/gpHuSAse #gis #h3 #spatialindexing #gisframeworks #spatialcomputing #geospatial #skillbuilding