<jupyter_start><jupyter_text>Visualize Proba-V NDVI Comparison**Author:** <NAME>**Description:** Comparison on Proba-V NDVI (Normalized Difference Vegetation Index) Imagery with help of Google Earth Engine Python API. One NDVI is derived on the fly, the other one is the actual NDVI band provided by Proba-V.<jupyter_code>%matplotlib inline
from IPython.display import Image
import ee
import folium
ee.Initialize()<jupyter_output><empty_output><jupyter_text>Load Proba-V image collection<jupyter_code>probav = ee.ImageCollection('VITO/PROBAV/C1/S1_TOC_100M')

# Reduce image collection to mean
probav_mean = probav.mean()

# Set location to Europe (Proba-V Footprint: X18Y02) 
point = ee.Geometry.Point(49.612485,6.134136)
luxembourg = point.buffer(50000).bounds().getInfo()['coordinates']<jupyter_output><empty_output><jupyter_text>Calculate and plot Proba-V NDVI This example is not using the NDVI band, instead it will be calculated from NIR and RED band.<jupyter_code>ndvi = probav_mean.normalizedDifference(["NIR", "RED"])
vis_ndvi= {'region':luxembourg,
           'min':-0.5,
           'max':0.5,
           'palette':['ffffe5','f7fcb9','d9f0a3','addd8e','78c679','41ab5d','238443','006837','004529']}

mapid = ndvi.getMapId(vis_ndvi)
map = folium.Map(location=[49.612485,6.134136],zoom_start=7, height=500,width=700)
folium.TileLayer(
    tiles=mapid['tile_fetcher'].url_format,
    attr='Map Data &copy; <a href="https://earthengine.google.com/">Google Earth Engine</a>',
    overlay=True,
    name='Proba-V NDVI 100M',
  ).add_to(map)

map.add_child(folium.LayerControl())
map<jupyter_output><empty_output><jupyter_text>Plot Proba-V NDVI This example is using the NDVI band.<jupyter_code>vis_ndvi= {'region':luxembourg,
           'min':0,
           'max':255,
           'bands':['NDVI'],
           'palette':['ffffe5','f7fcb9','d9f0a3','addd8e','78c679','41ab5d','238443','006837','004529']}

mapid = probav_mean.getMapId(vis_ndvi)

map = folium.Map(location=[49.612485,6.134136],zoom_start=7, height=500,width=700)
folium.TileLayer(
    tiles=mapid['tile_fetcher'].url_format,
    attr='Map Data &copy; <a href="https://earthengine.google.com/">Google Earth Engine</a>',
    overlay=True,
    name='Proba-V NDVI 100M',
  ).add_to(map)

map.add_child(folium.LayerControl())
map<jupyter_output><empty_output>
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