Converts Global Forest Watch integrated deforestation alerts to CSV output

gfw_alerts_to_csv.py

# derived from a question to ChatGPT
# How could I use Python code to derive a CSV with 4 fields: longitude, latitude, date, and confidence level from a raster which has the following encoding/syntax?:
# Each pixel (alert) encodes the date of disturbance and confidence level in one integer value. The leading integer of the decimal representation is 2 for a low-confidence alert, 3 for a high-confidence alert, and 4 for an alert detected by multiple alert systems, followed by the number of days since December 31, 2014. 0 is the no-data value. For example:
# 20001 is a low confidence alert on January 1st, 2015
# 30055 is a high confidence alert on February 24, 2015
# 21847 is a low confidence alert on January 21, 2020
# 41847 is a highest confidence alert (detected by multiple alert systems) on January 21, 2020. Alert date represents the earliest detection
# 0 represents no alert

import rasterio
import numpy as np
import csv

# Open the raster file and read in the data
with rasterio.open('path/to/raster/file.tif') as src:
    data = src.read(1)

# Get the spatial information from the raster file
transform = src.transform
width = src.width
height = src.height

# Create a list to hold the output data
output = []

# Loop over each pixel in the data array
for y in range(height):
    for x in range(width):
        # Get the alert value from the data array
        alert = data[y,x]
        
        # If the alert value is 0, skip to the next pixel
        if alert == 0:
            continue
        
        # Determine the confidence level and number of days since Dec 31, 2014
        conf = int(str(alert)[0])
        days = int(str(alert)[1:])
        date = np.datetime64('2014-12-31') + np.timedelta64(days, 'D')
        
        # Convert the pixel coordinates to longitude and latitude
        lon, lat = rasterio.transform.xy(transform, y, x)
        
        # Add the data to the output list
        output.append([lon, lat, date, conf])

# Write the output list to a CSV file
with open('output_file.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerow(['Longitude', 'Latitude', 'Date', 'Confidence'])
    writer.writerows(output)