Exploring the Evolution and Impact of Mapillary with Ed from Meta. 

Topics include Ed's journey with Mapillary, the process of uploading and utilizing street-level imagery, and the integration with OpenStreetMap.

Ed talks about the challenges of mapping with various devices, the role of community contributions, and future potentials in mapping technology, such as using neural radiance fields (NeRFs) for creating immersive 3D scenes.

The episode provides insights into how Mapillary is advancing geospatial data collection and usage.

00:00 Introduction to the Map Scaping Podcast 00:57

Meet Ed: Product Manager at Meta 02:09

Ed's Journey with Mapillary 03:59

What is Mapillary? 07:00

The Evolution of 360 Cameras 09:20

Uploading Imagery to Mapillary 14:10

Building a 3D Model of the World 19:10

Meta's Use of Map Data 21:24

The Importance of Community in Mapping 24:15

The Importance of Authoritative Data 24:49

Meta's Contributions to Open Source Geo World 25:27

Real-World Applications: Vietnam's B Group 28:16

Innovative Mapping in Detroit 31:38

Future of Mapping: Lidar and Beyond 32:20

Exploring Neural Radiance Fields (NeRFs) 35:40

Challenges and Innovations in Mapping Technology 45:25

Community Contributions and Future Directions 46:37

Closing Remarks and Contact Information

https://mapscaping.com/podcast/scaling-map-data-generation-using-computer-vision/

https://mapscaping.com/podcast/the-rapid-editor/

https://mapscaping.com/podcast/overture-maps-and-the-daylight-distribution/

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

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!

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:

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/ 

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

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

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 [email protected]

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

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.

• What is Satclip?: Learn about Satclip's location encoding, a neural network that converts geographic coordinates into numerical representations based on satellite images.

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/

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.

Quotes:

• "Natural language geocoding is about turning a user's textual description of a place on Earth into a precise polygon."

Additional Resources:

• Element 84 Website

Connect with Jason:

• Visit Element 84's website for more information and contact details.

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:

1. 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.

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/