Awesome
Fire_Pattern_Analysis_CONUS
Project Name: Fire Patterns and Drivers in CONUS
Yuhan Huang
Project Data:
Please refer to the /data folder
Large data was packed into zip files to save space
Fire Occurrence Data: shapefiles
please extract the .zip files and save them in the folder 'wf_occurrence_all_1980_2016' under the /data folder
Data can also be accessed from: https://wildfire.cr.usgs.gov/firehistory/data.html
Burned Area Data: shapefiles
please extract the .zip files and save them in the folder 'US_HIST_FIRE_PERIMTRS_DD83' under the /data folder
Data can also be accessed from: https://rmgsc.cr.usgs.gov/outgoing/GeoMAC/historic_fire_data/
US County Data: shapefiles
please extract the .zip files and save them in the folder 'tl_2017_us_county' under the /data folder
Data can also be assessed from: https://www2.census.gov/geo/tiger/TIGER2017/COUNTY/
Warning: This project also requires Google Earth Engine API, please refer to the following webpage about API registration:
https://developers.google.com/earth-engine/python_install-conda https://developers.google.com/earth-engine/python_install
To use extractions from Earth Engine API directly, please refer to the csv files under the /saved_data folder
Jupyter Notebook
Please refer to the /notebook folder
The folder contains one jupyter notebook file and some .html files which are for those interactive maps.
All scripts are in the jupyter notebook
Note:
Chrome has limitations on rendering large interactive maps, so large maps were saved seperately. Please run the corresponding cell to load the map or uncomment the corresponding script to generate maps and save them as html
Cleaned Data for Analysis
Please refer to the /saved_data folder
Note:
This is a long notebook, so several .csv containing cleaned data were generated. Please uncomment the corresponding script to generate those datasets.