This Python script demonstrates how to generate a collection of rectangular polygons within a given boundary defined by a GeoJSON file. The script uses the shapely library to check for intersections between the rectangles and the boundary polygon.
The code provided demonstrates an implementation of Inverse Distance Weighting (IDW) interpolation using the idw_interpolation function. IDW interpolation is a spatial interpolation technique that estimates values at target points based on known values at surrounding points.
The idw_interpolation function takes in three parameters: points, values, and target_points. The points parameter is an array of known points with their coordinates, the values parameter is an array of known values corresponding to the points, and the target_points parameter is an array of points where the interpolated values are to be estimated. The function also takes an optional power parameter to control the influence of nearby points on the interpolation.
The code snippet provided includes the estimate_new_pm25 function, which is used to estimate new PM2.5 values based on previous values and wind parameters.
The provided code snippet demonstrates the process of loading and processing data from JSON files for further analysis and calculations.
After loading the data, the code performs IDW interpolation for each target ID separately. It utilizes the idw_interpolation function, passing the known points, known values, and target points as inputs.
The code snippet calculates the new PM2.5 values based on the previously interpolated values and other parameters.
The code snippet includes the create_aqi_colored_geojson function, which generat sarts a GeoJSON file to an HTML file for visualization using Folium.
A sample of image for heatmap of Ahmedabad(dummy data as of now)
