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Monitoring Forests with David Marvin from Planet
Manage episode 412634579 series 3401994
Bringing transparency and accuracy to the marketplace by producing high-quality data on all types of hard problems is a main focus for today’s guest and the company he works for. I am pleased to welcome David Marvin to Impact AI. David was the Co-Founder and CEO of Salo Sciences, which was acquired by Planet last year, and is now the Product Lead for Forest Ecosystems there! He joins me today to talk about monitoring forests. We delve into his background and path to Salo Sciences and their eventual acquisition by Planet; including the original mission and vision and what they worked to accomplish at Salo. David then explains his goals and focus at Planet, and unpacks the types of satellite imagery, models, and sensors they incorporate into their data and outputs. He highlights their approach to validation, how they are reducing bias, and how they are integrating extensive knowledge to empower their machine learning developers to create powerful models.
Key Points:
- David shares details about his background and path to Salo Sciences and Planet.
- The original vision and mission of Salo Sciences and what they did there.
- He explains how they leveraged large-scale airborne LiDAR collections and deep learning to create maps of vegetation fuels.
- His goals and focus at Planet.
- David unpacks the types of satellite imagery, models, and sensors they incorporate into their data and outputs.
- How they validate that their models work in places where they do not have Airborne LiDAR.
- Reducing the bias that results from only having data in a heterogeneous distribution of LiDAR sites around the world.
- How they integrate their extensive knowledge to empower their machine-learning developers in creating powerful models.
- The business benefits he’s seen from publishing and making it a priority.
- His advice to other leaders of AI-powered startups.
- His thoughts on the impact of the forest monitoring efforts at Planet in three to five years.
Quotes:
“A company like Planet was essentially probably the only company we would have really ever been acquired by just given their vision and the fact that they have their own satellites and we’re a satellite software company.” — David Marvin
“[At Salo Sciences] we leveraged high-quality airborne LiDAR measurements of forests all over California. Airborne LiDAR is one of these technologies, these sensors, that was on that airplane back in my post-doc lab. It shoots out hundreds of thousands of pulses of laser light per second and reflects back to the sensor, and it can basically recreate in three dimensions a forest, or a city, whatever your mapping target is. It's extremely precise. It's centimeter-level accuracy, and it's very high-quality data. We consider that the gold standard of forest measurement.” — David Marvin
“Ultimately, we want to produce a near-tree-level map of the world's forests, and we're well on our way to doing that and expect to be releasing that later this summer, or in the fall.” — David Marvin
“We approach the validation aspect from a few different angles, trying to source as many different independent data sets as possible to do validation. Then we also like to do comparisons to well-known public data sets; either from academia or from governments.” — David Marvin
“You really do have to have the three legs of the stool to be able to build a quality operational product that is meant for forest monitoring.” — David Marvin
“Making sure you have scientists on your team, making sure you're still active in the scientific publishing community, that you're up on the latest papers that are coming out, and basically acting like a scientist in an industry position is crucial to make any product work; especially in branding markets, like forest monitoring and carbon markets.” — David Marvin
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.
Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
Foundation Model Assessment – Foundation models are popping up everywhere – do you need one for your proprietary image dataset? Get a clear perspective on whether you can benefit from a domain-specific foundation model.
108 odcinków
Manage episode 412634579 series 3401994
Bringing transparency and accuracy to the marketplace by producing high-quality data on all types of hard problems is a main focus for today’s guest and the company he works for. I am pleased to welcome David Marvin to Impact AI. David was the Co-Founder and CEO of Salo Sciences, which was acquired by Planet last year, and is now the Product Lead for Forest Ecosystems there! He joins me today to talk about monitoring forests. We delve into his background and path to Salo Sciences and their eventual acquisition by Planet; including the original mission and vision and what they worked to accomplish at Salo. David then explains his goals and focus at Planet, and unpacks the types of satellite imagery, models, and sensors they incorporate into their data and outputs. He highlights their approach to validation, how they are reducing bias, and how they are integrating extensive knowledge to empower their machine learning developers to create powerful models.
Key Points:
- David shares details about his background and path to Salo Sciences and Planet.
- The original vision and mission of Salo Sciences and what they did there.
- He explains how they leveraged large-scale airborne LiDAR collections and deep learning to create maps of vegetation fuels.
- His goals and focus at Planet.
- David unpacks the types of satellite imagery, models, and sensors they incorporate into their data and outputs.
- How they validate that their models work in places where they do not have Airborne LiDAR.
- Reducing the bias that results from only having data in a heterogeneous distribution of LiDAR sites around the world.
- How they integrate their extensive knowledge to empower their machine-learning developers in creating powerful models.
- The business benefits he’s seen from publishing and making it a priority.
- His advice to other leaders of AI-powered startups.
- His thoughts on the impact of the forest monitoring efforts at Planet in three to five years.
Quotes:
“A company like Planet was essentially probably the only company we would have really ever been acquired by just given their vision and the fact that they have their own satellites and we’re a satellite software company.” — David Marvin
“[At Salo Sciences] we leveraged high-quality airborne LiDAR measurements of forests all over California. Airborne LiDAR is one of these technologies, these sensors, that was on that airplane back in my post-doc lab. It shoots out hundreds of thousands of pulses of laser light per second and reflects back to the sensor, and it can basically recreate in three dimensions a forest, or a city, whatever your mapping target is. It's extremely precise. It's centimeter-level accuracy, and it's very high-quality data. We consider that the gold standard of forest measurement.” — David Marvin
“Ultimately, we want to produce a near-tree-level map of the world's forests, and we're well on our way to doing that and expect to be releasing that later this summer, or in the fall.” — David Marvin
“We approach the validation aspect from a few different angles, trying to source as many different independent data sets as possible to do validation. Then we also like to do comparisons to well-known public data sets; either from academia or from governments.” — David Marvin
“You really do have to have the three legs of the stool to be able to build a quality operational product that is meant for forest monitoring.” — David Marvin
“Making sure you have scientists on your team, making sure you're still active in the scientific publishing community, that you're up on the latest papers that are coming out, and basically acting like a scientist in an industry position is crucial to make any product work; especially in branding markets, like forest monitoring and carbon markets.” — David Marvin
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.
Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
Foundation Model Assessment – Foundation models are popping up everywhere – do you need one for your proprietary image dataset? Get a clear perspective on whether you can benefit from a domain-specific foundation model.
108 odcinków
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