GISC 6317 Lab 9 Homework

Ashleigh Frank

import fiona

airports = fiona.open("C:\\Users\\ashle\\Downloads\\lab9\\mi_airports.shp")
airports

<open Collection 'C:\Users\ashle\Downloads\lab9\mi_airports.shp:mi_airports', mode 'r' at 0x1cf7d8bd1d0>

num_features = len(airports)
geom_type = airports.schema['geometry']
print(f"Number of features: {num_features}")
print(f"Geometry type: {geom_type}")

Number of features: 539
Geometry type: Point

ingham_airports = [f for f in airports if f['properties']['COUNTY'] == 'Ingham']
print(f"Number of airports in Ingham County: {len(ingham_airports)}")

Number of airports in Ingham County: 10

highest_airport = max(airports, key=lambda f: f['properties']['ELEVATION'])
    
name = highest_airport['properties']['NAME']
elevation = highest_airport['properties']['ELEVATION']
county = highest_airport['properties']['COUNTY']

print(f"The airport with the highest elevation is {name} in {county} County with an elevation of {elevation} feet.")

The airport with the highest elevation is Marenisco Landing Field in Gogebic County with an elevation of 1638 feet.

import rasterio

raster = rasterio.open("C:\\Users\\ashle\\Downloads\\lab9\\LE70220492002106EDC00_stack.gtif")
raster
raster.count

red = raster.read(3).astype('float32')
nir = raster.read(4).astype('float32')
import numpy as np

# Ignore divide by zero warnings
np.seterr(divide='ignore', invalid='ignore')

ndvi = (nir - red) / (nir + red)
print (ndvi)

[[0.37269557 0.39126167 0.44422984 ... 0.36966395 0.4064792  0.51700085]
 [0.32503662 0.3498452  0.39703378 ... 0.38437596 0.39950526 0.42797118]
 [0.33222115 0.3498452  0.373062   ... 0.37700787 0.37754792 0.415     ]
 ...
 [0.27515724 0.27947816 0.26802585 ... 0.29664874 0.3252385  0.3444754 ]
 [0.28249028 0.28341427 0.27947816 ... 0.37880737 0.3679616  0.2972973 ]
 [0.29672006 0.30234933 0.28967643 ... 0.3462555  0.31332746 0.27264014]]

import matplotlib.pyplot as plt
plt.figure(figsize=(8, 6))
ndvi_plot = plt.imshow(ndvi, cmap='RdYlGn', vmin=-1, vmax=1)
plt.title('NDVI (Normalized Difference Vegetation Index)')
plt.colorbar(ndvi_plot, label='NDVI Value')
plt.xlabel('Column #')
plt.ylabel('Row #')
plt.show()