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valleyforge
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valleyforge
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import ee
import numpy as np
import matplotlib.pyplot as plt
import shapefile
import pandas as pd
#ee.Authenticate(force=True)
# Token generated with all permissions 29 May 2024, DMK
ee.Authenticate()
ee.Initialize(project = 'ee-fortschthomas52')
sf = shapefile.Reader("/Users/hydro3/Documents/USGSSites/shape_files/pennsylvania/Valley_Forge.shp")
shapes = sf.shapes()
points = shapes[0].points
aoi = ee.Geometry.Polygon(points)
#aoi = ee.Geometry.Polygon(
# [[-75.46058743999999763, 40.07998496999999816],
# [-75.46054359999999406, 40.07955842999999874],
# [-75.46041832296344865, 40.07940505999999914],
# [-75.46060622999999623, 40.0785279999999986],
# [-75.46062502403982819, 40.07838421818735242],
# [-75.4609507348268238, 40.07834587628676815],
# [-75.46090688914397049, 40.0786238545767759],
# [-75.46081919777823543, 40.07929003930824763],
# [-75.46091315281292111, 40.0797836827827112],
# [-75.46104468999999426, 40.07996579999999653]], None, False)
start = pd.date_range(start= '2018-10-06' , end='2024-06-21' ,
freq='5d')
end = pd.date_range(start='2018-10-10' , end='2024-06-26' ,
freq='5d')
dates = pd.DataFrame ({'start': start , 'end': end})
def pulldata(startDate, endDate):
# Define source data
image = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')\
.filterDate(startDate, endDate)\
.select('B2', 'B3', 'B4', 'B8', 'B11')
#.filterMetadata('CLOUDY_PIXEL_PERCENTAGE', 'less_than', 10)\
# CRS is not the same.
# proj = image.first().select('B2').projection() # EPSG:32656, UTM zone 56N (Siberia?)
# proj = balule.projection() # EPSG:4326
# Export arrays
# https://gist.github.com/jdbcode/f4d56d72f7fc5beeaa3859999b1f5c3d
# https://gist.github.com/jdbcode/f4d56d72f7fc5beeaa3859999b1f5c3d?permalink_comment_id=3355627#gistcomment-3355627
mosaic = image.median().reproject(crs='EPSG:32736', scale=1) # This allows us to set the resolution.
band_arrs = mosaic.sampleRectangle(region=aoi)
# Get individual band arrays.
band_arr_b2 = band_arrs.get('B2') # Blue
band_arr_b3 = band_arrs.get('B3') # Green
band_arr_b4 = band_arrs.get('B4') # Red
band_arr_b8 = band_arrs.get('B8') # NIR
band_arr_b11 = band_arrs.get('B11') # SWIR
# Transfer the arrays from server to client and cast as np array.
b2 = np.array(band_arr_b2.getInfo()) # b2 Blue
b3 = np.array(band_arr_b3.getInfo()) # b3 Green
b4 = np.array(band_arr_b4.getInfo()) # b4 Red
b8 = np.array(band_arr_b8.getInfo()) # b8 NIR
b11 = np.array(band_arr_b11.getInfo()) # b11 SWIR
if(np.max(b2)!=0):
#np_arr_b4 = np.expand_dims(b4, 2)
#np_arr_b3 = np.expand_dims(b3, 2)
#np_arr_b2 = np.expand_dims(b2, 2)
#rgb_img = np.concatenate((np_arr_b4, np_arr_b3, np_arr_b2), 2)
#rgb_img = (255*((rgb_img)/3000)).astype('uint8')
#plt.imshow(rgb_img)
#plt.show()
# Normalized Difference Water Index (NDWI)
# NDWI = ( G - NIR ) / ( G + NIR )
ndwiG = (b3-b8)/(b3+b8) # Gao
# NDWI = ( NIR - SWIR ) / ( NIR + SWIR )
ndwiM = (b8-b11)/(b8+b11) # McFeeters
# NDWI = ( G - SWIR ) / ( G + SWIR )
mndwi = (b3-b11)/(b3+b11) # Modified NDWI
water = ndwiG > -0.02
TSS1 = np.NAN
Secchi1 = np.NAN
TSS2 = np.NAN
Secchi2 = np.NAN
TSS3 = np.NAN
Secchi3 = np.NAN
TSS4 = np.NAN
Ratio = np.NAN
TSS1 = (b3+b4)/2
TSS1 = TSS1 * water
#plt.imshow(TSS1 , cmap= "summer")
#plt.colorbar(orientation="vertical")
#plt.show
TSS1 = np.sum(TSS1) / np.sum(TSS1>0)
#print(TSS1)
Secchi1 = (b2/b4)
Secchi1 = Secchi1 * water
Secchi1 = np.sum(Secchi1)/ np.sum(Secchi1>0)
TSS2 = (b3/b4)
TSS2 = TSS2 * water
TSS2 = np.sum(TSS2) / np.sum(TSS2>0)
Secchi2 = (b4/b3)
Secchi2 = Secchi2 * water
Secchi2 = np.sum(Secchi2)/ np.sum(Secchi2>0)
TSS3 = (b8/b3 , b8/b4)
TSS3 = TSS3 * water
TSS3 = np.sum(TSS3) / np.sum(TSS3>0)
Secchi3 = (b4/b2)+b2
Secchi3 = Secchi3 * water
Secchi3 = np.sum(Secchi3)/ np.sum(Secchi3>0)
TSS4 = (b4/b3)+b8
TSS4 = TSS4 * water
TSS4 = np.sum(TSS4) / np.sum(TSS4>0)
Ratio = (ndwiG/ndwiM)
Ratio = Ratio * water
Ratio = np.sum(Ratio)/ np.sum(Ratio>0)
f = open("Valley_Forge10day.txt", "a")
f.write(str(startDate) + ", " + str(endDate) + ", " +
str(TSS1) + ", " + str(Secchi1) + ", " +
str(TSS2) + ", " + str(Secchi2) + ", " +
str(TSS3) + ", " + str(Secchi3) + ", " +
str(TSS4) + "," + str(Ratio) + '\n')
f.close()
for i in range(len(dates)):
pulldata(dates["start"][i], dates["end"][i])