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We analyzed the droughts levels across the US and its possible correlation with wildfires throughout the years 2000 to 2016

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Project1_Droughts_USA

Team Members

  • Roberto Vera
  • Leo Muñoz
  • Salvador Del Cos
  • Ángeles Cruz

We analyzed the droughts levels across the US and its possible correlation with wildfires throughout the years 2000 to 2016.

  • We selected two data sources, one from Kaggle y the other one from MTBS (Monitoring Trends in Burn Severity).
  • We cleaned up the datasets, drop columns we weren't going to use and null values too.
  • The clean up process for both datasets turned into .py functions to avoid huge jupyter notebooks.
  • In the exploration process, we generated different visualization, such as linear and bar plots.
  • We also used a library called Basemap, to draw the US map and avoid using the API from Google.

Findings

  • Based on the droughts levels we generated, throught the year 2000 to 2016, the highest average drought level ocurred in 2012, with a level of 1.4.
  • 2.4 has been the highest average drought level, the top 5 counties are located in the state of Nevada.
  • Out of the 6 drought levels, the number 5 (which is the exceptional drought) didn't decrease drom 2011 to 2016, as it did in previous years.
  • More than 8K wildires had taken place in the US in the same years.
  • 2011 was the year with most wildfires, 846.
  • 2005 was the year with the most sq. miles burned. However, this year wasnt the year with most wildfires. So, the wildfires quantity doesn't mean more sq. miles are burned.
  • In our animated maps, highest drought level locations seem to be located as the wildfires.

Presentation

Data Cleaning

Data Analysis

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We analyzed the droughts levels across the US and its possible correlation with wildfires throughout the years 2000 to 2016

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