ageller

license: mit
height: 505

ageller

# define the area of interest, using the Earth Engines geometry object
coords = [
     [lon - sze/2., lat - sze/2.],
     [lon + sze/2., lat - sze/2.],
     [lon + sze/2., lat + sze/2.],
     [lon - sze/2., lat + sze/2.],
     [lon - sze/2., lat - sze/2.]
]
aoi = ee.Geometry.Polygon(coords)

ageller

# define the bands that I want to use.  B4 is red, B3 is green, B2 is blue
# https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR#bands
bands = ['B4', 'B3', 'B2']

# export geotiff images, these go to Drive and then are downloaded locally
for selection in bands:
    task = ee.batch.Export.image.toDrive(image=db.select(selection),
                                 description=selection,
                                 scale=30,
                                 region=aoi,

ageller

# open the images
B2 = rasterio.open('B2.tif')
B3 = rasterio.open('B3.tif')
B4 = rasterio.open('B4.tif')

 #get the scaling
image = np.array([B2.read(1), B3.read(1), B4.read(1)]).transpose(1,2,0)
p2, p98 = np.percentile(image, (2,98))

# use the B2 image as a starting point so that I keep the same parameters

ageller

conda create --name geo_forge
conda activate geo_forge
conda config --env --add channels conda-forge
conda config --env --set channel_priority strict
conda install python=3.9 jupyter numpy matplotlib earthengine-api rasterio

ageller

import ee
import rasterio
from rasterio.plot import show as showRasterio

# my script
from EarthEngineToGeoTIFF import getSentinalS2SRImage

import matplotlib.pyplot as plt

# Trigger the authentication flow.

ageller

# Chicago central latitude, longitude and approximate size
lat = 41.8781
lon = -87.6298
sze = 0.65
_ = getSentinalS2SRImage(lon, lat, sze, 'ChicagoGeoTIFF.tif')

ageller

f,ax = plt.subplots(figsize=(15,15))

chicago = rasterio.open('ChicagoGeoTIFF.tif')
showRasterio(chicago.read(), ax = ax, transform=chicago.transform)

chicago.close()

ageller

conda activate geo_forge
conda install geopandas pandas

ageller

import rasterio
import pandas as pd
import geopandas as gpd
df = pd.read_csv('311_Service_Requests_-_Pot_Holes_Reported_-_Historical.csv')
gdf = gpd.read_file('Boundaries_ZIP_Codes/geo_export_94cfa385-03be-4b00-b827-c9e4fdd73a8f.shp')
chicago = rasterio.open('ChicagoGeoTIFF.tif')