AH_lab5_scripts.py

# Lab 5 scripts

import AH_lab5_functions as l5
import matplotlib.pyplot as plt
import geopandas as gpd
import os

#  Part 1:

#  Assign a variable to the Landsat file 
landsat_file = "Landsat_image_corv.tif"

# Pass this to your new smart raster class
smart_raster = l5.SmartRaster(landsat_file)

# Calculate NDVI and save to and output file
try:
    ndvi_success, ndvi_result = smart_raster.calculate_ndvi()
    if ndvi_success:
        print("NDVI calculated successfully.")
    else:
        print(f"NDVI calculation failed: {ndvi_result}")
except Exception as e:
    print(f"An error occurred while calculating NDVI: {e}")


# Part 2:
# Assign a variable to the parcels data shapefile path
parcels_file = "Benton_County_TaxLots.shp"

#  Pass this to your new smart vector class
import AH_lab5_functions as l5
smart_vector = l5.SmartVector(parcels_file)

#  Calculate zonal statistics and add to the attribute table of the parcels shapefile
try:
    zonal_success = smart_vector.add_zonal_stats("ndvi_output.tif", stat="mean", output_column="mean_ndvi")
    if zonal_success:
        print("Zonal statistics calculated successfully.")
        print(smart_vector.vector.head())
    else:
        print("Zonal statistics calculation failed.")
except Exception as e:
    print(f"An error occurred while calculating zonal statistics: {e}")


#  Part 3: Optional
#  Use matplotlib to make a map of your census tracts with the average NDVI values
try:
    fig, ax = plt.subplots(1, 1, figsize=(10, 10))
    smart_vector.vector.plot(column="mean_ndvi", ax=ax, legend=True, cmap="YlGn")
    ax.set_title("Census Tracts with Average NDVI Values")
    plt.show()
except Exception as e:
    print(f"An error occurred while plotting: {e}")