Data science for the environment | Dan Hammer | TEDxBerkeley
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- Опубліковано 30 тра 2024
- Since the industrial revolution, as human technology has advanced, the environment has suffered. Dan Hammer is looking to turn this paradigm on its head, as he takes a high-tech approach to preserving the environment by using data science and satellite imagery to monitor and protect forests all around the globe.
Dan Hammer received 2017 Pritzker Award for his work to make environmental information more accessible to journalists. He earned his PhD in Environmental Economics from UC Berkeley, where he was a Fellow at the Berkeley Institute for Data Science. Dan works at an environmental and tech nonprofit that he founded alongside two other Berkeley alumni, including the former CEO of The Nature Conservancy and The Moore Foundation. He previously served as a Senior Policy Advisor on data infrastructure in the Obama White House, as well as a Presidential Innovation Fellow at NASA. Dan was the Chief Data Scientist at the World Resources Institute, where he co-founded Global Forest Watch -- an online platform to monitor deforestation from satellite imagery. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at www.ted.com/tedx
This video is very insightful and thought-provoking. It shows how can we use technology in a sustainable way that would help to identify, monitor and assess human involvement in activities that harm the environment and the global dynamics of climate change and its ongoing threats to humanity. Also, I liked how Hammer is aware the importance of presenting your findings in a way that feed and inform environmental policy and practitioners to act, collaborate and tackle environmental threats in both local and international level.
Yes! the gap between research and policy is a real issue. It's sometimes about who you know than what you know.
@@MariamAli-cp1zu Exactly. There's a play of political science in communicating scientific findings in a socially acceptable way that is well understood and can drive progressive collaboration in addressing issues through policy formulation and effective implementation
people deserve to know your insights!
As an Environmental Scientist, This is a great video. Thanks Dan Hammer. We must know that the earth is falling apart and what we can do to keep it together is very important. You can't change what you can't see. Now we can see and still looking
Hello @BADMUS OLADIMEJI, nice to hear from you. I also want to work as Environmental data scientist. I have done work on Indian climate data using nonlinear time series analysis. Is there any way, I can contact you?
@@jayeshdave680bro can you help me. I also want to become environmental data analyst. How should I start
very interesting content...good work Dan Hammer and your colleagues.
Amazing job !
Thanks interesting job as a future environmental engineer.
Well done! and thanks for insight
Best use of data
Interesting stuff.
thanks for the inspiration!
Very interesting information..
love it
love
👏👏👏👏👏
David Guetta is also a data expert apart from being a legendary DJ! 😎
My subject is environmental economics. Which one will better for me 💥Data Science or 💥Big Data analyst
bro, im doing my master's degree in Big Data Analysis, it is pretty similar with data science with some extra knowledge in databases and data warehouses and machine learning skills. after that you are able to work as a data scientist, data engineer, data architect or a data analyst. the choice is yours....either way both subjects are awesome as they specialize in the same field. give me feedback about your choice.
"you can't change what you can't see" is a fundamentally nonsense statement. There are many things humans change that they cannot see for example sound waves, radio waves, certain light waves, extreme small stuff and the list goes on and on.... nice video though
You dont understand the essence of his words.
youre wrong
seeing is not about what you can see with your eyes
@@MMMM-qg7ln I agree with Arthur. Maybe the speaker needs to be explicit in explaining it.
they do it because they use visualization methods to detect them, so they first see those things and then make up the change.