Hongwei Liu is the CEO & Co-Founder of MappedIn, a company focused on indoor mapping. I know a lot about what it takes to map the outdoor world, but little about what’s required to map indoors. That’s what this conversation is about.

Sean Gorman is currently on his 4th start-up, Zephr, working on improving smartphone location. Previously he worked on 3D mapping (acquired by Snap), mapping fibre optics infrastructure (and caught the NAS's attention as a grad student). I was recently in Colorado and got to spend a few days with Sean, at the end of which we recorded a conversation about building great teams, finding what to work on and building businesses around maps

Harold Goddijn is one of the co-founders & the CEO of TomTom. TomTom has pivoted many times, from its beginnings making PDA software in the early 90s, stumbling onto mapping, building its own hardware to millions of devices sold in a day, to its current form today. TomTom is a fascinating company in the mapping industry and I'm excited to share a conversation with the person leading it all, Harold Goddijn.

James Killick worked at Apple from 2013 to 2022 on the Maps team and has worked in mapping for the past 40 years. I've been wondering why Apple has gotten so much into Maps; Google makes sense to me, they're just the same ad business as search, but on a map. So, why -and how- did Apple get into Map?

Patreon Exclusive: I recently published the 50th episode of MBM, so thought I might record some thoughts on what the journey has been like, thinking about the podcast over the long term, and also making videos on Earth Observation and mapping for the broadest audience possible.

Aravind Ravichandran is the founder of TerraWatch Space, where he does consulting and strategy with the goal, in his words, to demystify Earth Observation. This is an introduction to the 5 layers Aravind identifies as making the Earth Observation industry. Aravind writes one of the most popular newsletter gathering the latest news and featuring deep dives analysing the industry. We also hosts a podcast -albeit on pause at the moment- so was the perfect person to discuss Earth Observation at a high level.

Steve Brumby is the founder & CTO of Impact Observatory, a company working on providing rapid land cover maps anywhere on Earth. He puts it as wanting to provide "the maps the US takes for granted, all around the globe".

Steve was also a co-founder & the CTO at Descartes Labs and worked at National Geographic

Robert Cheetham is the founder of Azavea, founded all the way back in 2000 and Dan Pilone one of the founders of Element84, started in 2010. Recently Element84 acquired Azavea to expand from large scale computing to also analysis. I wanted to talk to Robert & Dan about why they went for an acquisition and why now, if both companies had both been around for so long. Both companies also have not taken outside investment, which made this acquisition all the more interesting

Dr Este Geraghty is the Chief Medical Officer at ESRI, a former Deputy Director of the California Department of Public Health and a certified public health professional; so the perfect person to talk about how we map diseases, health and all the support around medical care. Este also wrote a book about the learning of mapping applied to covid, which we discuss.

Can Duruk is the co-founder & CTO at Felt, a company working on bringing maps to the browser. In Can's own words they want to make maps fun and collaborative. Think of Felt as the Figma or Notion of Maps.

Zhuang-Fang Nana Yi is a Senior Machine Learning Engineer at Regrow, though today's conversation is about her story from going to school not speaking the language, to mapping rubber tree plantations and ultimately using global satellite imagery methods to solve local problems.

Jed Sundwall is the Executive Director of Radiant Earth, and formerly worked on creating AWS's Open Data Registry, starting by putting Landsat images and then other Earth Observation datasets on the cloud. Radiant Earth is an NGO focused on making geospatial data more accessible, specifically for Machine Learning applications.