Generate a distance raster based on two data layers

# The code is designed to rasterize hospital locations and then generate a proximity raster showing distances from these hospitals.
# There are several main sections:
# 1. Rasterizing the hospital vector data.
# 2. Generating a proximity map from the rasterized hospitals.
# 3. Correcting the code to meet documentation guidelines and ensuring correct functionality.

import os
from qgis.core import QgsVectorLayer, QgsRasterLayer, QgsProject
import processing
from time import sleep

def generate_distance_raster():
# Define the input paths
hospital_shapefile = ‘C:/Users/17036/Downloads/DEMO/SanFranciscoHospitals/SanFranciscoHospitals.shp’
census_tracts_shapefile = ‘C:/Users/17036/Downloads/DEMO/SanFrancisco_tracts_central/SanFrancisco_tracts_central.shp’

# Define the output directory
base_output_dir = ‘C:/Users/17036/AppData/Roaming/QGIS/QGIS3/profiles/default/python/plugins/SpatialAnalysisAgent-master/Default_workspace/’

# Output file paths for rasterized hospitals and proximity map
rasterized_hospitals_path = os.path.join(base_output_dir, ‘rasterized_hospitals.tif’)
proximity_output_path = os.path.join(base_output_dir, ‘hospital_distance.tif’)

# Check if output file already exists and create a unique name if necessary
if os.path.exists(rasterized_hospitals_path):
base_name, ext = os.path.splitext(rasterized_hospitals_path)
rasterized_hospitals_path = f“{base_name}_1{ext}”

if os.path.exists(proximity_output_path):
base_name, ext = os.path.splitext(proximity_output_path)
proximity_output_path = f“{base_name}_1{ext}”

# The input vector layers for hospitals and census tracts
hospitals_layer = QgsVectorLayer(hospital_shapefile, ‘San Francisco Hospitals’, ‘ogr’)
census_tracts_layer = QgsVectorLayer(census_tracts_shapefile, ‘San Francisco Census Tracts’, ‘ogr’)

# Get the extent of the census tracts to use as the raster extent
census_extent = census_tracts_layer.extent()

# Step 1: Rasterize the hospital locations
rasterize_params = {
‘INPUT’: hospitals_layer,
‘FIELD’: ”,
‘BURN’: 1.0,  # Burn a value of 1.0 where hospitals are located
‘USE_Z’: False,
‘UNITS’: 1,  # Georeferenced units
‘WIDTH’: 100,  # 100 meter resolution
‘HEIGHT’: 100,  # 100 meter resolution
‘EXTENT’: f“{census_extent.xMinimum()},{census_extent.xMaximum()},{census_extent.yMinimum()},{census_extent.yMaximum()}”,
‘NODATA’: 0.0,
‘OUTPUT’: rasterized_hospitals_path,
‘OPTIONS’: ”,
‘DATA_TYPE’: 5  # Float32
}
processing.run(“gdal:rasterize”, rasterize_params)

# Wait for a second to ensure the rasterized layer is created before using it in further processing
sleep(1)

# Load the rasterized layer for the hospitals into QGIS
rasterized_layer = QgsRasterLayer(rasterized_hospitals_path, ‘Rasterized Hospitals’)
QgsProject.instance().addMapLayer(rasterized_layer)

# Step 2: Generate a proximity raster from the rasterized hospital locations
proximity_params = {
‘INPUT’: rasterized_hospitals_path,
‘BAND’: 1,
‘VALUES’: ”,  # All non-zero pixels are considered target pixels
‘UNITS’: 0,  # Georeferenced coordinates
‘MAX_DISTANCE’: 0.0,
‘REPLACE’: 0.0,
‘NODATA’: 0.0,
‘OUTPUT’: proximity_output_path,
‘OPTIONS’: ”,
‘EXTRA’: None,
‘DATA_TYPE’: 5  # Float32
}

# Run the proximity algorithm
processing.run(“gdal:proximity”, proximity_params)

# Load the resulting proximity map layer into QGIS
proximity_layer = QgsRasterLayer(proximity_output_path, ‘Proximity Map’)
QgsProject.instance().addMapLayer(proximity_layer)

# Execute the function to generate the distance raster
generate_distance_raster()