Climate Change Adaptation: Difference between revisions

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* Providing annotation: Extracting actionable information or labels from unstructured raw data.
* Promoting exchange: Making it easier to share resources and information to pool and reduce risk.
== Data ==
Satellite imagery are used for ecological and social observation. Some public sources include,
 
== Machine Learning Application Areas ==
* [https://github.com/chrieke/awesome-satellite-imagery-datasets awesome-satellite-imagery-datasets]: A github repository of accessible satellite imagery data.
*
 
== RecommendedBackground Readings ==
There have also been competitions revolving around climate change adaptation issues,
 
* [https://app.wandb.ai/wandb/droughtwatch/benchmark DroughtWatch] revolves around drought monitoring in Kenya.
* [https://www.drivendata.co/case-studies/promoting-digital-financial-services-in-tanzania/ Promoting Digital Financial Services in Tanzania] describes an attempt to mobile money effort to improve financial inclusion and resilience.
* The [https://zindi.africa/competitions/ibm-malaria-challenge IBM Malaria Challenge] is a competition around Improved disease surveillance and response, which is motivated by the spread of vector borne disease resulting from climate change.
 
This competition describes an attempt to use mobile money effort to improve financial inclusion and resilience.
 
Improved disease surveillance and response is an important part of adaptation – here is one competition with this goal in mind.
 
== Methods and Software ==
 
== Recommended Readings ==
 
* Quinn, J. et al. Computational sustainability and artificial intelligence in the developing world<ref>{{Cite journal|last=Quinn|first=John|last2=Frias-Martinez|first2=Vanessa|last3=Subramanian|first3=Lakshminarayan|date=2014-09-29|title=Computational Sustainability and Artificial Intelligence in the Developing World|url=http://dx.doi.org/10.1609/aimag.v35i3.2529|journal=AI Magazine|volume=35|issue=3|pages=36|doi=10.1609/aimag.v35i3.2529|issn=0738-4602}}</ref> (2014).
* Agrawal, A., and Perrin, N. Climate adaptation, local institutions and rural livelihoods. (2009)
* Shi, L. et al. Roadmap towards justice in urban climate adaptation research. (2016)
 
== Online Courses and Course Materials ==
 
== Community ==
=== Journals and conferences ===
 
* [https://channels.plos.org/rtcc PLOS Responding to Climate Change]
* [https://acmcompass.org/ ACM Compass]
* [https://www.itu.int/en/ITU-T/AI/2018/Pages/default.aspx AI for Good Global Summit]
* [https://www.thelancet.com/climate-and-health Lancet Health and Climate Change]
 
=== Societies and organizations ===
=== Past and upcoming events ===
 
== ImportantLibraries considerationsand Tools ==
 
== Next stepsData ==
Satellite imagery are used for ecological and social observation. Some public sources include,
 
* [https://github.com/chrieke/awesome-satellite-imagery-datasets awesome-satellite-imagery-datasets]: A github repository of accessible satellite imagery data.
*
 
There have also been competitions revolving around climate change adaptation issues,
 
* [https://app.wandb.ai/wandb/droughtwatch/benchmark DroughtWatch] revolves around drought monitoring in Kenya.
* [https://www.drivendata.co/case-studies/promoting-digital-financial-services-in-tanzania/ Promoting Digital Financial Services in Tanzania] describes an attempt to mobile money effort to improve financial inclusion and resilience.
* The [https://zindi.africa/competitions/ibm-malaria-challenge IBM Malaria Challenge] is a competition around Improved disease surveillance and response, which is motivated by the spread of vector borne disease resulting from climate change.
 
This competition describes an attempt to use mobile money effort to improve financial inclusion and resilience.
 
Improved disease surveillance and response is an important part of adaptation – here is one competition with this goal in mind.
 
== References ==
<references/>
 
[[category:Application areas]]