AGU session on remote sensing for socio-environmental systems

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AGU session on remote sensing for socio-environmental systems

Ian Bolliger
Hello cryolisters,

I wanted to advertise a session at the upcoming fall meeting. It's not explicitly targeted at the cryosphere section, but we would love to see some submissions that highlight impacts on sea ice, ice sheets, seasonal snow, etc. OR that highlight the impact of changes to these physical properties on societies. Session title and description are below.

Note: Because this session is listed under a policy-related section, AGU's "1 contributed abstract" limit does not apply. So even if you are already submitting an abstract to another session, please consider applying to this session as well!

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Title: "Quantifying impacts in socio-environmental systems through the application of remote sensing and machine learning"

Invited Authors: Marshall Burke (Stanford) and Phil Brodrick (Arizona State)

Conveners: Ian Bolliger (UC Berkeley), Jonathan Proctor (Harvard), Tamma Carleton (U Chicago)

Session Description:
Increases in the quantity and resolution of earth observing satellites are rapidly transforming our ability to monitor and manage global challenges from environmental degradation to poverty alleviation. At the same time, the recent development and application of machine learning techniques to remote sensing enables us to extract more complex social and environmental information from satellite imagery. Together, these trends present novel opportunities to quantify important relationships in coupled socio-environmental systems, from estimating the economic impacts of climate change to evaluating the ecological impacts of environmental policy. We invite two categories of submission to this session. First, research that leverages remote sensing and machine learning to answer policy-relevant questions within environmental science, economics, and particularly at the intersection of these two fields. Second, research that integrates machine learning with remotely sensed information to advance methodologies for monitoring key social and environmental indicators.


Best,
-- 
Ian Bolliger
Berkeley Graduate Fellow
Energy and Resources Group | UC Berkeley


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