https://github.com/yuhhuang/Fire_Pattern_Analysis_CONUS

Analysis of fire patterns and drivers in CONUS
https://github.com/yuhhuang/Fire_Pattern_Analysis_CONUS

Last synced: about 1 month ago
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Analysis of fire patterns and drivers in CONUS

• Host: GitHub
• URL: https://github.com/yuhhuang/Fire_Pattern_Analysis_CONUS
• Owner: yuhhuang
• Created: 2020-03-19T07:52:17.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-09-21T06:25:50.000Z (almost 4 years ago)
• Last Synced: 2024-05-08T04:11:08.558Z (about 2 months ago)
• Language: HTML
• Homepage:
• Size: 31.1 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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• awesome-earthobservation-code - Fire_Pattern_Analysis_CONUS - Analysis of fire patterns and drivers in CONUS `Python` (Earth Engine / Testing your code)

README

        
# 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.