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Abstract
Panama Canal had a severe drought crisis during the rainy season of the year 2019 (link). It obligates to reduce the traffic crossing the Canal. In this research, we applied the Machine Learning K-Means algorithm to European Copernicus Sentinel III images to classify what is resilient and the most affected regions during the rainy months of 2019 from May to October. This research shows the utility of segmentation to define different strategies for a drought low moisture period event.
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Title
Lake Gatun Panama Canal: Machine Learning grouping high vegetable activity regions during the year 2019 droughts
Description
Panama Canal had a severe drought crisis during the rainy season of the year 2019 (link). It obligates to reduce the traffic crossing the Canal. In this research, we applied the Machine Learning K-Means algorithm to European Copernicus Sentinel III images to classify what is resilient and the most affected regions during the rainy months of 2019 from May to October. This research shows the utility of segmentation to define different strategies for a drought low moisture period event.
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