F44b 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:      F4.4 Change Detection
#  Checkpoint:   F44b
#  Author:       Karis Tenneson, John Dilger, Crystal Wespestad, Brian Zutta,
#                Andréa P Nicolau, Karen Dyson
#  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

landsat8 = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").select(
    ["SR_B2", "SR_B3", "SR_B4", "SR_B5", "SR_B6", "SR_B7"],
    ["blue", "green", "red", "nir", "swir1", "swir2"],
)

point = ee.Geometry.Point([-123.64, 42.96])
Map.centerObject(point, 11)

preImage = (
    landsat8.filterBounds(point)
    .filterDate("2013-06-01", "2013-06-30")
    .sort("CLOUD_COVER", True)
    .first()
)

postImage = (
    landsat8.filterBounds(point)
    .filterDate("2020-06-01", "2020-06-30")
    .sort("CLOUD_COVER", True)
    .first()
)

visParam = {"bands": ["swir2", "nir", "red"], "min": 7750, "max": 22200}
Map.addLayer(preImage, visParam, "pre")
Map.addLayer(postImage, visParam, "post")

# Calculate NBR.
nbrPre = preImage.normalizedDifference(["nir", "swir2"]).rename("nbr_pre")
nbrPost = postImage.normalizedDifference(["nir", "swir2"]).rename("nbr_post")

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

# 2-date change.
diff = nbrPost.subtract(nbrPre).rename("change")

palette = [
    "011959",
    "0E365E",
    "1D5561",
    "3E6C55",
    "687B3E",
    "9B882E",
    "D59448",
    "F9A380",
    "FDB7BD",
    "FACCFA",
]
visParams = {"palette": palette, "min": -0.2, "max": 0.2}
Map.addLayer(diff, visParams, "change")

# Classify change
thresholdGain = 0.10
thresholdLoss = -0.10

diffClassified = ee.Image(0)

diffClassified = diffClassified.where(diff.lte(thresholdLoss), 2)
diffClassified = diffClassified.where(diff.gte(thresholdGain), 1)

changeVis = {"palette": "fcffc8,2659eb,fa1373", "min": 0, "max": 2}

Map.addLayer(diffClassified.selfMask(), changeVis, "change classified by threshold")

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

# Add Earth Engine dataset image = ee.Image("USGS/SRTMGL1_003") # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Chapter: F4.4 Change Detection # Checkpoint: F44b # Author: Karis Tenneson, John Dilger, Crystal Wespestad, Brian Zutta, # Andréa P Nicolau, Karen Dyson # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ landsat8 = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2").select( ["SR_B2", "SR_B3", "SR_B4", "SR_B5", "SR_B6", "SR_B7"], ["blue", "green", "red", "nir", "swir1", "swir2"], ) point = ee.Geometry.Point([-123.64, 42.96]) Map.centerObject(point, 11) preImage = ( landsat8.filterBounds(point) .filterDate("2013-06-01", "2013-06-30") .sort("CLOUD_COVER", True) .first() ) postImage = ( landsat8.filterBounds(point) .filterDate("2020-06-01", "2020-06-30") .sort("CLOUD_COVER", True) .first() ) visParam = {"bands": ["swir2", "nir", "red"], "min": 7750, "max": 22200} Map.addLayer(preImage, visParam, "pre") Map.addLayer(postImage, visParam, "post") # Calculate NBR. nbrPre = preImage.normalizedDifference(["nir", "swir2"]).rename("nbr_pre") nbrPost = postImage.normalizedDifference(["nir", "swir2"]).rename("nbr_post") # ----------------------------------------------------------------------- # CHECKPOINT # ----------------------------------------------------------------------- # 2-date change. diff = nbrPost.subtract(nbrPre).rename("change") palette = [ "011959", "0E365E", "1D5561", "3E6C55", "687B3E", "9B882E", "D59448", "F9A380", "FDB7BD", "FACCFA", ] visParams = {"palette": palette, "min": -0.2, "max": 0.2} Map.addLayer(diff, visParams, "change") # Classify change thresholdGain = 0.10 thresholdLoss = -0.10 diffClassified = ee.Image(0) diffClassified = diffClassified.where(diff.lte(thresholdLoss), 2) diffClassified = diffClassified.where(diff.gte(thresholdGain), 1) changeVis = {"palette": "fcffc8,2659eb,fa1373", "min": 0, "max": 2} Map.addLayer(diffClassified.selfMask(), changeVis, "change classified by threshold") # ----------------------------------------------------------------------- # CHECKPOINT # -----------------------------------------------------------------------

Display the interactive map¶

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Map

Map