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Earthsight
cr458
4 episodes
6 days ago
Chris and Krishna share big thoughts about the geospatial industry. Chris is a data scientist currently working in weather, but has previously worked at Los Alamos National Lab, The Earth Genome, Gro Intelligence and Demeter Labs. At those places he used earth observation data to solve problems such as crop mapping, yield prediction, change detection etc... Krishna is a data journalist who uses satellite imagery for news coverage. Previously he worked at Descartes Labs, Impact Observatory, The Earth Genome, Ceres Imaging and more. Krishna is an adjunct professor at The Cooper Union.
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Science
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Chris and Krishna share big thoughts about the geospatial industry. Chris is a data scientist currently working in weather, but has previously worked at Los Alamos National Lab, The Earth Genome, Gro Intelligence and Demeter Labs. At those places he used earth observation data to solve problems such as crop mapping, yield prediction, change detection etc... Krishna is a data journalist who uses satellite imagery for news coverage. Previously he worked at Descartes Labs, Impact Observatory, The Earth Genome, Ceres Imaging and more. Krishna is an adjunct professor at The Cooper Union.
Show more...
Science
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Geospatial Failures, Problem Selection, Being an Analyst/Scientist is Hard
Earthsight
59 minutes 10 seconds
6 days ago
Geospatial Failures, Problem Selection, Being an Analyst/Scientist is Hard

(00:00) Experimental failures. Krishna won't let Chris forget about his failed SimCLR experiments.

(04:30) Geographic generalization discussion. Husky vs Malamute vs Wellpad.

(11:32) Chris fails to map coconut palm because it's hard. Read the paper carefully.

(15:30) Krishna maps oil slicks, but it's hard.

(20:30) Cognitive debt, problem selection and failure modes in geospatial.

(31:00) The sales cycle, promises, inflated expectations. Limitations in geospatial.

(34:00) Problem selection in journalism. Are we running out of ideas?

(37:00) Turning a failure into a success. Cover crop mapping is hard.

(45:00) Turning failure into a success: predicting sugarcane yield is hard.

(49:00) Is building tooling easier than solving modeling problems?

(53:00) Vertical seems better than horizontal. Solutions are multi-modal.




Earthsight
Chris and Krishna share big thoughts about the geospatial industry. Chris is a data scientist currently working in weather, but has previously worked at Los Alamos National Lab, The Earth Genome, Gro Intelligence and Demeter Labs. At those places he used earth observation data to solve problems such as crop mapping, yield prediction, change detection etc... Krishna is a data journalist who uses satellite imagery for news coverage. Previously he worked at Descartes Labs, Impact Observatory, The Earth Genome, Ceres Imaging and more. Krishna is an adjunct professor at The Cooper Union.