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import folium
import pandas
import geemap.foliumap as geemap
import ee
from datetime import date, timedelta, datetime
def ee_authenticate(token_name="EARTHENGINE_TOKEN"):
geemap.ee_initialize(token_name=token_name)
def maskCloudAndShadows(image):
cloudProb = image.select('MSK_CLDPRB')
snowProb = image.select('MSK_SNWPRB')
cloud = cloudProb.lt(5)
snow = snowProb.lt(5)
scl = image.select('SCL')
shadow = scl.eq(3); # 3 = cloud shadow
cirrus = scl.eq(10); # 10 = cirrus
# Cloud probability less than 5% or cloud shadow classification
mask = (cloud.And(snow)).And(cirrus.neq(1)).And(shadow.neq(1))
return image.updateMask(mask).divide(10000)
# Normalized difference vegetation index (NDVI)
def getNDVI(image):
ndvi = image.normalizedDifference(['B8','B4']).rename("NDVI")
image = image.addBands(ndvi)
return(image)
def addDate(image):
img_date = ee.Date(image.date())
img_date = ee.Number.parse(img_date.format('YYYYMMdd'))
return image.addBands(ee.Image(img_date).rename('date').toInt())
ee_authenticate(token_name="4/1AfJohXleDqw1-fV1879iHUDYgPbM7f5OjCKfxFY3vJiiGqQDn_ff-Luhhhk") #4/1AfJohXkTlWMKd8fPevD3hd4tAq_j-YlD2CabTy7QtM7iu1gNB3XdBEqRehA
map_center=(-43.525650, 172.639847)
popup_message = 'Contact: [email protected]'
crs = "epsg:4326"
band = ['B8','B4','B3']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
Map = geemap.Map(
basemap="HYBRID",
plugin_Draw=True,
Draw_export=True,
locate_control=True,
plugin_LatLngPopup=False, center=map_center, zoom=8,
)
ed = date.today()
sd = ed - timedelta(days=30)
startDate = sd.strftime("%Y-%m-%d") + "T"
endDate = ed.strftime("%Y-%m-%d") + "T"
se2 = ee.ImageCollection('COPERNICUS/S2_SR').filterDate(
startDate,endDate).filter(
ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",80)).map(maskCloudAndShadows).median()
palette = ['FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901', '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01', '012E01', '011D01', '011301']
vis_params = {
'min': 0,
'max': 1,
'palette': palette}
NDVI_data = ee.ImageCollection('COPERNICUS/S2_SR').filterDate(startDate, endDate).filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE",80)).map(maskCloudAndShadows).map(getNDVI)
Map.addLayer(NDVI_data.select('NDVI').median(), vis_params, "Median of NDVI")
band = ['B4','B3','B2']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
titlemap = "Sentinel 2 - Natural Color"
Map.addLayer(se2, rgbViza, titlemap)
band = ['B8','B4','B3']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
titlemap = "Sentinel 2 - Color Infrared"
Map.addLayer(se2, rgbViza, titlemap)
band = ['B11','B8','B2']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
titlemap = "Sentinel 2 - Agriculture"
Map.addLayer(se2, rgbViza, titlemap)
band = ['B11','B8','B4']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
titlemap = "Sentinel 2 - Vegetation Analysis"
Map.addLayer(se2, rgbViza, titlemap)
band = ['B8','B11','B2']
rgbViza = {"min":0.0, "max":0.7,"bands":band}
titlemap = "Sentinel 2 - Healthy Vegetation"
Map.addLayer(se2, rgbViza, titlemap)
folium.Marker(
location=map_center,
popup=popup_message,
icon=folium.Icon(icon="info-sign", color="red")
).add_to(Map)
Map.addLayerControl()
Map.save("index.html")
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