The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

MapScaping
The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography

A podcast for the mapping community. Interviews with the people that are shaping the future of GIS, geospatial and the mapping world. This is a podcast for the GIS and geospatial community https://mapscaping.com/

  1. ١٢ صفر

    Satclip - Encoding Location

    In this episode, I'm joined by Konstantine Klemmer, a researcher at Microsoft, to dive deep into the fascinating world of GeoAI. Konstantine introduces us to Satclip, a cutting-edge model that encodes geographic locations based on satellite images. We discuss how Satclip works, the data it uses, and its potential applications, particularly in low-resource settings and predictive modeling. Whether you're into AI, geography, or just curious about the intersection of these fields, this episode is packed with insights. Key Takeaways: What is Satclip?: Learn about Satclip's location encoding, a neural network that converts geographic coordinates into numerical representations based on satellite images. Data and Training: Understand how Satclip is trained using Sentinel-2 satellite images and how it captures unique geographic features. Applications: Discover how Satclip can be used in low-resource environments, such as on edge devices, and how it enhances other models by providing geographic context. The Future of GeoAI: Explore the potential future directions for Satclip, including more detailed regional models and the integration of multiple data modalities. Connect with Konstantine https://www.linkedin.com/in/konstantinklemmer/ Try Satclip https://github.com/microsoft/satclip   Recommended Listening https://mapscaping.com/podcast/computer-vision-and-geoai/ https://mapscaping.com/podcast/planet-imaging-everything-every-day-almost/

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  2. ٢٦ محرم

    Natural Language Geocoding

    In this episode, I welcome Jason Gilman, a Principal Software Engineer at Element 84, to explore the exciting world of natural language geocoding. Key Topics Discussed: Introduction to Natural Language Geocoding: Jason explains the concept of natural language geocoding and its significance in converting textual descriptions of locations into precise geographical data. This involves using large language models to interpret a user's natural language input, such as "the coast of Florida south of Miami," and transform it into an accurate polygon that represents that specific area on a map. This process automates and simplifies how users interact with geospatial data, making it more accessible and user-friendly. The Evolution of AI and ML in Geospatial Work: Over the last six months, Jason has shifted focus to AI and machine learning, leveraging large language models to enhance geospatial data processing. Challenges and Solutions: Jason discusses the challenges of interpreting natural language descriptions and the solutions they've implemented, such as using JSON schemas and OpenStreetMap data. Applications and Use Cases: From finding specific datasets to processing geographical queries, the applications of natural language geocoding are vast. Jason shares some real-world examples and potential future uses. Future of Geospatial AIML: Jason touches on the broader implications of geospatial AI and ML, including the potential for natural language geoprocessing and its impact on scientific research and everyday applications. Interesting Insights: The use of large language models can simplify complex geospatial queries, making advanced geospatial analysis accessible to non-experts. Integration of AI and machine learning with traditional geospatial tools opens new avenues for research and application, from environmental monitoring to urban planning. Quotes: "Natural language geocoding is about turning a user's textual description of a place on Earth into a precise polygon." "The combination of vision models and large language models allows us to automate complex tasks that previously required manual effort." Additional Resources: Element 84 Website State of the Map US Conference Talk on YouTube Blog Posts on Natural Language Geocoding Connect with Jason: Visit Element 84's website for more information and contact details. Google "Element 84 Natural Language Geocoding" for additional resources and talks.

    ٤٥ من الدقائق
  3. ٤ محرم

    Semantic Search For Geospatial

    This podcast episode is all about semantic search and using embeddings to analyse text and social media data. Dominik Weckmüller, a researcher at the Technical University of Dresden, talks about his PhD research, where he looks at how to analyze text with geographic references.  He explains hyperloglog and embeddings, showing how these methods capture the meaning of text and can be used to search big databases without knowing the topics beforehand. Here are the main points discussed: Intro to Semantic Search and Hyperloglog: Looking at social media data by counting different users talking about specific topics in parks, while keeping privacy in mind. Embeddings and Deep Learning Models: Turning text into numerical vectors (embeddings) to understand its meaning, allowing for advanced searches. Application Examples: Using embeddings to search for things like emotions or activities in parks without needing predefined keywords. Creating and Using Embeddings: Tools like transformers.js let you make embeddings on your computer, making it easy to analyze text. Challenges and Innovations: Talking about how to explain the models, deal with long texts, and keep data private when using embeddings. Future Directions: The potential for using embeddings with different media (like images and videos) and languages, plus the ongoing research in this fast-moving field. Connect with Dominik Weckmüller here https://geo.rocks/ Stay up to date with AI here https://huggingface.co/ Try searching for “map”  here https://huggingface.co/spaces   Check out this project I am working on  https://quickmaptools.com/

    ٥١ من الدقائق
  4. ٢٨ ذو القعدة

    Why You Should Care About L Band

    In this episode, we welcome back Lauren Guy, CEO and founder of ASTERRA, a groundbreaking company using L band and synthetic aperture radar (SAR) for commercial purposes. Lauren shares his journey as a geophysicist and discusses the innovative applications of L band in detecting water leakages, soil moisture, and even minerals from space. Dive deep into the technical, commercial, and environmental aspects of SAR technology and learn about the future potential of this exciting field. **Key Topics Covered:** **Introduction to Astera**:    - Overview of Asterra's mission and Lauren Guy's background as a geophysicist.    - The unique use of L band and SAR for commercial applications.   **Understanding L Band and Synthetic Aperture Radar (SAR)**:    - Explanation of the electromagnetic spectrum and how L band fits in.    - Advantages of L band, including its ability to penetrate the ground.   **Technical Insights into SAR**:    - Detailed discussion on polarizations, signal processing, and the electrical properties of materials detected by SAR.    - Comparison between L band and other bands like X and C band.   **Applications and Benefits of L Band**:    - Real-world examples of how Astera uses L band for water leak detection and soil moisture mapping.    - Discussion on the environmental and commercial impact of these applications.   **Challenges and Limitations**:    - Addressing issues such as noise interference from cell phones and radars.    - Limitations in resolution and the complexities of SAR technology.   **Case Studies and Success Stories**:    - Success stories including the detection of 118,000 water leakages worldwide and the discovery of significant lithium deposits.   **Business Strategies and Market Penetration**:    - Insights into ASTERRA's business model, customer education, and market challenges.    - Strategies for overcoming barriers and building trust with clients.   **Future Aspirations and Technological Developments**:    - Plans for launching their own satellites to ensure reliable data sources.    - The role of AI in enhancing SAR capabilities and improving detection accuracy.   **Entrepreneurial Advice for Remote Sensing Practitioners**:    - Lauren’s advice for remote sensing scientists and entrepreneurs in the industry.    - The importance of data feedback loops and the journey from a 20% to an 86% success rate in detections.   **Guest Information:** - **Lauren Guy**: CTO and founder of ASTERRA. Connect with Lauren on https://www.linkedin.com/in/lauren-guy-asterra/   **Company Information:** - **ASTERRA**: Learn more about ASTERRA’s innovative solutions at https://asterra.io/   **Additional Resources:** - Check out Lauren’s previous appearance on the podcast for more insights into SAR technology. - Explore ASTERRA’s groundbreaking work in remote sensing and their various applications across different industries.   **Episode Highlights:** - "We can find water leakages from space and distinguish treated water from other types of water based on their dielectric properties." - "ASTERRA has verified, dug, and fixed 118,000 leakages across 65 countries using L band SAR technology." - "Our success rate has increased from 20% to around 86% thanks to the integration of AI and continuous data feedback."   **Support the Show:** - If you enjoyed this episode, please leave a review on your favourite podcast platform and share it with your network.   Thank you for tuning in to the MapScaping Podcast!   Recommended Listening  Finding Water Leaks From Space Introduction To Synthetic Aperture Radar-SAR Flood Monitoring From Space ( using SAR)

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A podcast for the mapping community. Interviews with the people that are shaping the future of GIS, geospatial and the mapping world. This is a podcast for the GIS and geospatial community https://mapscaping.com/

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