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

MapScaping
  • 5.0（2）
  • 地球科学
  • アップデート：毎週

A podcast for geospatial people. Weekly episodes that focus on the tech, trends, tools, and stories from the geospatial world. Interviews with the people that are shaping the future of GIS, geospatial as well as practitioners working in the geo industry. This is a podcast for the GIS and geospatial community subscribe or visit https://mapscaping.com to learn more

  1. 1月9日

    Telematics Data is Reshaping Our Understanding of Road Networks

    Telematics Data is Reshaping Our Understanding of Road Networks In this episode MIT Professor Hari Balakrishnan explains how Cambridge Mobile Telematics (CMT) is transforming traditional road network analysis by layering dynamic behavioural data onto static map geometries.  Telematics data creates "living maps" that go beyond traditional road geometry and attributes. By collecting movement data from 45 million users through phones and IoT devices, CMT has developed sophisticated models that can: - Generate dynamic risk maps showing crash probability for every road segment globally - Detect infrastructure issues that aren't visible in traditional mapping (like poorly placed bus stops) - Validate and correct map attributes like speed limits and lane connectivity - Differentiate between overpasses and intersections using movement patterns - Create contextual understanding of road segments based on actual usage patterns Particularly interesting for GIS professionals is CMT's approach to data fusion, combining traditional map geometry with temporal movement data to create predictive models. This has practical applications from infrastructure planning to autonomous vehicle navigation, where understanding the cultural context of road usage proves as important as precise geometry. The episode challenges traditional static approaches to road network mapping, suggesting that the future lies in dynamic, behavior-informed spatial data models that can adapt to changing conditions and usage patterns. For anyone working with transportation networks or smart city initiatives, this episode provides valuable insights into how movement data is changing our understanding of road infrastructure and spatial behaviour.   Connect with Hari on LinkedIn! https://www.linkedin.com/in/hari-balakrishnan-0702263/ Cambridge Mobile Telematics https://www.cmtelematics.com/   BTW,  I keep busy creating free mapping tools and publishing them there https://mapscaping.com/map-tools/ swing by and take a look!

    59分

  2. 2024/12/05

    Hivemapper

    In this week’s episode, I’m thrilled to welcome back Ariel Seidman, founder of HiveMapper. Ariel was my very first podcast guest back in 2019, and HiveMapper has come a long way since then! We explore how HiveMapper has evolved from a drone-based mapping system to a cutting-edge platform collecting street-level data at a global scale. Ariel shares the challenges of scaling large-scale mapping efforts, the pivot to building their own hardware, and the role of blockchain-based incentives in driving adoption. Here are just a few topics we cover: Why HiveMapper shifted focus from drones to street-level mapping. The power of combining hardware and software to solve mapping challenges. How HiveMapper has already mapped 28% of the global road network. The revolutionary edge computing and data filtering techniques driving efficiency. What it takes to compete with industry giants like Google Maps. Whether you're fascinated by the intersection of geospatial technology and innovation or looking for insights into scaling impactful startups, this episode is packed with value. Let me know your thoughts or hit reply if you’d like to discuss the episode!   https://beemaps.com/ Connect with Ariel here https://www.linkedin.com/in/aseidman/   PS I have just finished creating a web-based tool that lets you explore and download OpenStreetMap data, It is a bit different from other tools and I would appreciate some feedback.  https://mapscaping.com/openstreetmap-category-viewer/

    51分

  3. 2024/11/06

    Tracking Elephants

    Tracking elephants in Southern Africa’s Kavango-Zambezi (KAZA) region, the largest transfrontier conservation area in the world. Lead scientist Robin Naidoo from the World Wildlife Fund-US explains the complex, cross-border collaboration required to understand elephant movements across vast landscapes and the role of GNSS.   Connected with Robin  https://www.worldwildlife.org/experts/robin-naidoo   Read more information about this study here https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2664.14746   https://news.mongabay.com/2024/09/jumbo-collaring-effort-reveals-key-elephant-movement-corridors/   Check out https://www.movebank.org/

    46分

  4. 2024/09/25

    Female Voices in Geospatial

    Today's episode touches on some pretty big topics like Imposter Syndrome, Mentorship, Career Progression, Adaptability and Diversity Today you are going to hear two stories from two very different voices. Two brilliant people who happen to be women in geospatial.    Ta Taneka https://www.linkedin.com/in/ta-taneka/ Mary Murphy https://www.linkedin.com/in/mary-murphy-12319433/   You can check out the GIS Directions Podcast here: https://esriaustralia.com.au/gis-directions-podcast or search for GIS Directions where every you listen to podcasts   Recommended Podcast Episodes Getting where you want to go in your geospatial career Mentorship leadership and career advice Mentorship leadership and career advice

    43分

  5. 2024/09/18

    QField

    In this episode, Marco Bernasconi, co-founder and CEO of OPENGIS.ch, introduces us to QField, an open-source mobile application designed for field data collection in conjunction with QGIS. Marco shares his journey in developing QField and discusses its seamless integration with QGIS, allowing users to capture, survey, and manage geospatial data on various mobile devices. We also discuss the technical aspects of QField, including its user-friendly interface, the ability to connect with external sensors, and the recent introduction of QField Cloud for enhanced data synchronization and management. Marco highlights the application’s diverse use cases, from citizen science initiatives to archaeological documentation and utility inspections, demonstrating its potential to transform data collection processes across various industries. More information on Qfield:  https://qfield.org/ https://qfield.cloud/ Or https://www.opengis.ch/#contact      On a personal note, I have been working as a freelance Geospatial consultant for some time now and one of my projects is slowly winding down, which is why I am looking for new projects to get involved in! If you need expertise in Geospatial consultancy, GIS management or the marketing of geospatial products and services Please reach out! https://www.linkedin.com/in/danielodonohue/ or contact me here info@mapscpaing.com

    49分

  6. 2024/08/28

    Analyst To Engineer

    This is the story of Priscilla Cole, and what she did when she discovered that her ambitions were bigger than the tools she was using! Connect with Priscilla here! https://www.linkedin.com/in/priscilla-cole-5892549/   Recommended Listening The Way You Talk About Your Skills Is Costing You Money   Geospatial Consulting As A Business And Career   Mid-Life Career Change   Getting Where You Want To Go In Your Career   Applying For A Job, Getting Picked and Negotiating   Mentorship Leadership And Career Advice

    41分

  7. 2024/08/16

    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/

    44分

  8. 2024/08/01

    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.

    45分
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番組について

A podcast for geospatial people. Weekly episodes that focus on the tech, trends, tools, and stories from the geospatial world. Interviews with the people that are shaping the future of GIS, geospatial as well as practitioners working in the geo industry. This is a podcast for the GIS and geospatial community subscribe or visit https://mapscaping.com to learn more

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