Agriculture: Difference between revisions

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Savolainen, S. Schlomer, C. von Stechow, T. Zwickel, J.C. Minx}}</ref>(and this may be an underestimate<ref>{{Cite journal|title=Are the impacts of land use on warming underestimated in climate policy?|url=https://iopscience.iop.org/article/10.1088/1748-9326/aa836d|coauthors=Natalie M Mahowald, Daniel S Ward, Scott C Doney, Peter G Hess, and James T Randerson|date=2017}}</ref>). In addition to this direct release of carbon through human actions, the permafrost is now melting, peat bogs are drying, and forest fires are becoming more frequent as a consequence of climate change itself – all of which release yet more carbon<ref>{{Cite journal|title=The study of Earth as an integrated system|url=https://climate.nasa.gov/nasa_science/science/#:~:text=The%20Study%20of%20Earth%20as%20an%20Integrated%20System&text=Earth%20system%20science%20is%20the,whole%2C%20including%20its%20changing%20climate.}}</ref>.
 
The large scale of this problem allows for a similar scale of positive impact. According to one estimate<ref>{{Cite book|title=Drawdown: The most comprehensive plan ever proposed to reverse global warming|author=Paul Hawken|date=2015}}</ref>, about a third of GHG emissions reductions could come from better land management and agriculture. ML can play an important role in some of these areas. Precision agriculture could reduce carbon release from the soil and improve crop yield, which in turn could reduce the need for deforestation. Satellite images make it possible to estimate the amount of carbon sequestered in a given area of land, as well as track GHG emissions from it. ML can help monitor the health of forests and peatlands, predict the risk of fire, and contribute to sustainable forestry. These areas represent highly impactful applications, in particular, of sophisticated computer vision tools, though care must be taken in some cases to avoid negative consequences via the Jevons paradox.
== Data ==
Satellite imagery are often useful for monitoring land use. Some widely accessed resources include,
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* [https://developers.google.com/earth-engine/datasets/catalog/ Earth Engine Data Catalog]
* [https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-methane?tab=overview Methane detection from satellite]
 
Forestry related data have also been the focus of machine learning competitions, including
 
* [https://www.kaggle.com/c/planet-understanding-the-amazon-from-space Planet: Understanding the Amazon from space]
* [https://idtrees.org/ IDTReeS: Integrating Data science with Trees and Remote Sensing]
 
== Methods and Software ==
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* [https://medium.com/sentinel-hub/introducing-eo-learn-ab37f2869f5c eo-learn]: A python package maintained by the European Space Agency, giving easy access to imagery from Sentinel satellites, as well as utilities for data processing
*[https://www.agr.gc.ca/eng/scientific-collaboration-and-research-in-agriculture/agricultural-research-results/holos-software-program/?id=1349181297838 Holos]: A crop simulator for Canadian farms.
* [https://github.com/mapbox/robosat robosat]: A package mapbox.
* [https://solaris.readthedocs.io/en/latest/ solaris]: A package from CosmiQ Works (SpaceNet Challenge).
 
== Recommended Readings ==
 
* [https://www.nature.com/articles/s41598-019-54386-6 ''Monitoring tropical forest carbon stocks and emissions using Planet satellite data'']
* ''[https://link.springer.com/article/10.1007/s11069-017-3106-x Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices]''
* ''[https://www.naturemdpi.com/articles/s41558-0202072-0762-84292/11/6/676 Remote Sensing NorthernTechniques Lakefor Soil Organic Carbon Estimation: MethaneA EbullitionReview]''
 
== Community ==
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=== Journals and conferences ===
 
*[https://www.journals.elsevier.com/computers-and-electronics-in-agriculture Computers and Electronics in Agriculture] ([https://www.resurchify.com/all_ranking_details_2.php?id=4686 ranking])
* [https://www.grss-ieee.org/earthvision2020/ EARTHVISION] is regularly held at computer vision conferences.
*[https://www.springer.com/journal/11119 Precision Agriculture] ([https://www.resurchify.com/all_ranking_details_2.php?id=6580 ranking])
* [https://groups.google.com/forum/#!category-topic/ml-news/b56zx6rIw2Q Space and AI] is organized by the ESA-CLAIRE AI Special Interest Group on Space.
 
=== Societies and organizations ===