F20b 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:      F2.0 Image Manipulation: Bands, Arithmetic, Thresholds, and Masks
#  Checkpoint:   F20b
#  Authors:      Karen Dyson, Andrea Puzzi Nicolau, David Saah, and Nicholas Clinton
#  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# Create an NDVI image using Sentinel 2.
seaPoint = ee.Geometry.Point(-122.2040, 47.6221)
seaImage = (
    ee.ImageCollection("COPERNICUS/S2")
    .filterBounds(seaPoint)
    .filterDate("2020-08-15", "2020-10-01")
    .first()
)

seaNDVI = seaImage.normalizedDifference(["B8", "B4"])

# And map it.
Map.centerObject(seaPoint, 10)
vegPalette = ["red", "white", "green"]
Map.addLayer(seaNDVI, {"min": -1, "max": 1, "palette": vegPalette}, "NDVI Seattle")

# Implement a threshold.
seaVeg = seaNDVI.gt(0.5)

# Map the threshold.
Map.addLayer(
    seaVeg, {"min": 0, "max": 1, "palette": ["white", "green"]}, "Non-forest vs. Forest"
)

# Implement .where.
# Create a starting image with all values = 1.
seaWhere = ee.Image(1).clip(seaNDVI.geometry())

# Make all NDVI values less than -0.1 equal 0.
seaWhere = seaWhere.where(seaNDVI.lte(-0.1), 0)

# Make all NDVI values greater than 0.5 equal 2.
seaWhere = seaWhere.where(seaNDVI.gte(0.5), 2)

# Map our layer that has been divided into three classes.
Map.addLayer(
    seaWhere,
    {"min": 0, "max": 2, "palette": ["blue", "white", "green"]},
    "Water, Non-forest, Forest",
)

# Implement masking.
# View the seaVeg layer's current mask.
Map.centerObject(seaPoint, 9)
Map.addLayer(seaVeg.mask(), {}, "seaVeg Mask")

# Create a binary mask of non-forest.
vegMask = seaVeg.eq(1)

# Update the seaVeg mask with the non-forest mask.
maskedVeg = seaVeg.updateMask(vegMask)

# Map the updated Veg layer
Map.addLayer(
    maskedVeg, {"min": 0, "max": 1, "palette": ["green"]}, "Masked Forest Layer"
)

# Map the updated mask
Map.addLayer(maskedVeg.mask(), {}, "maskedVeg Mask")

# Implement remapping.
# Remap the values from the seaWhere layer.
seaRemap = seaWhere.remap([0, 1, 2], [9, 11, 10])  # Existing values.
# Remapped values.

Map.addLayer(
    seaRemap,
    {"min": 9, "max": 11, "palette": ["blue", "green", "white"]},
    "Remapped Values",
)

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

# Add Earth Engine dataset image = ee.Image("USGS/SRTMGL1_003") # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Chapter: F2.0 Image Manipulation: Bands, Arithmetic, Thresholds, and Masks # Checkpoint: F20b # Authors: Karen Dyson, Andrea Puzzi Nicolau, David Saah, and Nicholas Clinton # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Create an NDVI image using Sentinel 2. seaPoint = ee.Geometry.Point(-122.2040, 47.6221) seaImage = ( ee.ImageCollection("COPERNICUS/S2") .filterBounds(seaPoint) .filterDate("2020-08-15", "2020-10-01") .first() ) seaNDVI = seaImage.normalizedDifference(["B8", "B4"]) # And map it. Map.centerObject(seaPoint, 10) vegPalette = ["red", "white", "green"] Map.addLayer(seaNDVI, {"min": -1, "max": 1, "palette": vegPalette}, "NDVI Seattle") # Implement a threshold. seaVeg = seaNDVI.gt(0.5) # Map the threshold. Map.addLayer( seaVeg, {"min": 0, "max": 1, "palette": ["white", "green"]}, "Non-forest vs. Forest" ) # Implement .where. # Create a starting image with all values = 1. seaWhere = ee.Image(1).clip(seaNDVI.geometry()) # Make all NDVI values less than -0.1 equal 0. seaWhere = seaWhere.where(seaNDVI.lte(-0.1), 0) # Make all NDVI values greater than 0.5 equal 2. seaWhere = seaWhere.where(seaNDVI.gte(0.5), 2) # Map our layer that has been divided into three classes. Map.addLayer( seaWhere, {"min": 0, "max": 2, "palette": ["blue", "white", "green"]}, "Water, Non-forest, Forest", ) # Implement masking. # View the seaVeg layer's current mask. Map.centerObject(seaPoint, 9) Map.addLayer(seaVeg.mask(), {}, "seaVeg Mask") # Create a binary mask of non-forest. vegMask = seaVeg.eq(1) # Update the seaVeg mask with the non-forest mask. maskedVeg = seaVeg.updateMask(vegMask) # Map the updated Veg layer Map.addLayer( maskedVeg, {"min": 0, "max": 1, "palette": ["green"]}, "Masked Forest Layer" ) # Map the updated mask Map.addLayer(maskedVeg.mask(), {}, "maskedVeg Mask") # Implement remapping. # Remap the values from the seaWhere layer. seaRemap = seaWhere.remap([0, 1, 2], [9, 11, 10]) # Existing values. # Remapped values. Map.addLayer( seaRemap, {"min": 9, "max": 11, "palette": ["blue", "green", "white"]}, "Remapped Values", ) # ----------------------------------------------------------------------- # CHECKPOINT # -----------------------------------------------------------------------

Display the interactive map¶

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Map

Map