A16h Checkpoint

Import libraries¶

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import ee
import geemap

import ee import geemap

Create an interactive map¶

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Map = geemap.Map(center=[40, -100], zoom=4)

Map = geemap.Map(center=[40, -100], zoom=4)

Add Earth Engine Python script¶

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# Add Earth Engine dataset
image = ee.Image("USGS/SRTMGL1_003")

#  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#  Chapter:      A1.6 Health Applications
#  Checkpoint:   A16h
#  Author:       Dawn Nekorchuk
#  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# Section 8: Viewing external analyses results

# This is using *synthetic* malaria data.
# For demonstration only, not to be used for epidemiological purposes.
epidemiaResults = ee.FeatureCollection(
    "projects/gee-book/assets/A1-6/amhara_pilot_synthetic_2018W32"
)
# Filter to only keep pilot woredas with forecasted values.
pilot = epidemiaResults.filter(ee.Filter.neq("inc_n_fc", None))
nonpilot = epidemiaResults.filter(ee.Filter.eq("inc_n_fc", None))

Map.setCenter(38, 11.5, 7)

# Paint the pilot woredas with different colors for forecasted* incidence
# fc_n_inc here is the forecasted incidence (cut into factors)
# made on (historical) 2018W24 (i.e. 8 weeks in advance).
# * based on synthetic data for demonstration only.
# Incidence per 1000
# 1 : [0 - 0.25)
# 2 : [0.25 - 0.5)
# 3 : [0.5 - 0.75)
# 4 : [0.75 - 1)
# 5 : > 1

empty = ee.Image().byte()
fill_fc = empty.paint(
    {
        "featureCollection": pilot,
        "color": "inc_n_fc",
    }
)
palette = ["fee5d9", "fcae91", "fb6a4a", "de2d26", "a50f15"]
Map.addLayer(fill_fc, {"palette": palette, "min": 1, "max": 5}, "Forecasted Incidence")

# Paint the woredas with different colors for the observed* incidence.
# * based on synthetic data for demonstration only
fill_obs = empty.paint(
    {
        "featureCollection": pilot,
        "color": "inc_n_obs",
    }
)
palette = ["fee5d9", "fcae91", "fb6a4a", "de2d26", "a50f15"]
# Layer is off by default, users change between the two in the map viewer.
Map.addLayer(
    fill_obs, {"palette": palette, "min": 1, "max": 5}, "Observed Incidence", False
)

# Add gray fill for nonpilot woredas (not included in study).
fill_na = empty.paint({"featureCollection": nonpilot})
Map.addLayer(fill_na, {"palette": "a1a9a8"}, "Non-study woredas")

# Draw borders for ALL Amhara region woredas.
outline = empty.paint({"featureCollection": epidemiaResults, "color": 1, "width": 1})
# Add woreda boundaries to map.
Map.addLayer(outline, {"palette": "000000"}, "Woredas")

#  -----------------------------------------------------------------------
#  CHECKPOINT
#  -----------------------------------------------------------------------

# Add Earth Engine dataset image = ee.Image("USGS/SRTMGL1_003") # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Chapter: A1.6 Health Applications # Checkpoint: A16h # Author: Dawn Nekorchuk # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Section 8: Viewing external analyses results # This is using *synthetic* malaria data. # For demonstration only, not to be used for epidemiological purposes. epidemiaResults = ee.FeatureCollection( "projects/gee-book/assets/A1-6/amhara_pilot_synthetic_2018W32" ) # Filter to only keep pilot woredas with forecasted values. pilot = epidemiaResults.filter(ee.Filter.neq("inc_n_fc", None)) nonpilot = epidemiaResults.filter(ee.Filter.eq("inc_n_fc", None)) Map.setCenter(38, 11.5, 7) # Paint the pilot woredas with different colors for forecasted* incidence # fc_n_inc here is the forecasted incidence (cut into factors) # made on (historical) 2018W24 (i.e. 8 weeks in advance). # * based on synthetic data for demonstration only. # Incidence per 1000 # 1 : [0 - 0.25) # 2 : [0.25 - 0.5) # 3 : [0.5 - 0.75) # 4 : [0.75 - 1) # 5 : > 1 empty = ee.Image().byte() fill_fc = empty.paint( { "featureCollection": pilot, "color": "inc_n_fc", } ) palette = ["fee5d9", "fcae91", "fb6a4a", "de2d26", "a50f15"] Map.addLayer(fill_fc, {"palette": palette, "min": 1, "max": 5}, "Forecasted Incidence") # Paint the woredas with different colors for the observed* incidence. # * based on synthetic data for demonstration only fill_obs = empty.paint( { "featureCollection": pilot, "color": "inc_n_obs", } ) palette = ["fee5d9", "fcae91", "fb6a4a", "de2d26", "a50f15"] # Layer is off by default, users change between the two in the map viewer. Map.addLayer( fill_obs, {"palette": palette, "min": 1, "max": 5}, "Observed Incidence", False ) # Add gray fill for nonpilot woredas (not included in study). fill_na = empty.paint({"featureCollection": nonpilot}) Map.addLayer(fill_na, {"palette": "a1a9a8"}, "Non-study woredas") # Draw borders for ALL Amhara region woredas. outline = empty.paint({"featureCollection": epidemiaResults, "color": 1, "width": 1}) # Add woreda boundaries to map. Map.addLayer(outline, {"palette": "000000"}, "Woredas") # ----------------------------------------------------------------------- # CHECKPOINT # -----------------------------------------------------------------------

Display the interactive map¶

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Map

Map