A18a 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:      A1.8 Monitoring Gold Mining Activity using SAR
#  Checkpoint:   A18a
#  Authors:      Lucio Villa, Sidney Novoa, Milagros Becerra,
#                Andréa Puzzi Nicolau, Karen Dyson, Karis Tenneson, John Dilger
#  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

###########################
# / Section One
###########################

# Define the area of study.
aoi = ee.FeatureCollection("projects/gee-book/assets/A1-8/mdd")

# Center the map at the aoi.
Map.centerObject(aoi, 9)

# Create an empty image.
empty = ee.Image().byte()

# Convert the area of study to an EE image object
# so we can visualize only the boundary.
aoiOutline = empty.paint({"featureCollection": aoi, "color": 1, "width": 2})

# Select the satellite basemap view.
Map.setOptions("SATELLITE")

# Add the area of study boundary to the map.
Map.addLayer(aoiOutline, {"palette": "red"}, "Area of Study")


# Function to mask the SAR images acquired with an incidence angle
# lower or equal to  31 and greater or equal to 45 degrees.
def maskAngle(image):
    angleMask = image.select("angle")
    return image.updateMask(angleMask.gte(31).And(angleMask.lte(45)))


# Function to get the SAR Collection.
def getCollection(dates, roi, orbitPass0):
    sarCollFloat = (
        ee.ImageCollection("COPERNICUS/S1_GRD_FLOAT")
        .filterBounds(roi)
        .filterDate(dates[0], dates[1])
        .filter(ee.Filter.eq("orbitProperties_pass", orbitPass0))
    )
    return sarCollFloat.map(maskAngle).select(["VV", "VH"])


# Define variables: the period of time and the orbitpass.
listOfDates = ["2021-08-01", "2021-08-12"]
orbitPass = "DESCENDING"

# Apply the function to get the SAR mosaic.
sarImageColl = getCollection(listOfDates, aoi, orbitPass).mosaic().clip(aoi)
print("SAR Image Mosaic", sarImageColl)

# Apply logarithmic scale.
sarImageScaled = sarImageColl.log10().multiply(10.0)

# Visualize results.
sarVis = {"bands": ["VV", "VH", "VV"], "min": [-18, -23, 3], "max": [-4, -11, 15]}
Map.addLayer(sarImageScaled, sarVis, "Sentinel-1 / SAR Mosaic")

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

# Add Earth Engine dataset image = ee.Image("USGS/SRTMGL1_003") # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Chapter: A1.8 Monitoring Gold Mining Activity using SAR # Checkpoint: A18a # Authors: Lucio Villa, Sidney Novoa, Milagros Becerra, # Andréa Puzzi Nicolau, Karen Dyson, Karis Tenneson, John Dilger # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ########################### # / Section One ########################### # Define the area of study. aoi = ee.FeatureCollection("projects/gee-book/assets/A1-8/mdd") # Center the map at the aoi. Map.centerObject(aoi, 9) # Create an empty image. empty = ee.Image().byte() # Convert the area of study to an EE image object # so we can visualize only the boundary. aoiOutline = empty.paint({"featureCollection": aoi, "color": 1, "width": 2}) # Select the satellite basemap view. Map.setOptions("SATELLITE") # Add the area of study boundary to the map. Map.addLayer(aoiOutline, {"palette": "red"}, "Area of Study") # Function to mask the SAR images acquired with an incidence angle # lower or equal to 31 and greater or equal to 45 degrees. def maskAngle(image): angleMask = image.select("angle") return image.updateMask(angleMask.gte(31).And(angleMask.lte(45))) # Function to get the SAR Collection. def getCollection(dates, roi, orbitPass0): sarCollFloat = ( ee.ImageCollection("COPERNICUS/S1_GRD_FLOAT") .filterBounds(roi) .filterDate(dates[0], dates[1]) .filter(ee.Filter.eq("orbitProperties_pass", orbitPass0)) ) return sarCollFloat.map(maskAngle).select(["VV", "VH"]) # Define variables: the period of time and the orbitpass. listOfDates = ["2021-08-01", "2021-08-12"] orbitPass = "DESCENDING" # Apply the function to get the SAR mosaic. sarImageColl = getCollection(listOfDates, aoi, orbitPass).mosaic().clip(aoi) print("SAR Image Mosaic", sarImageColl) # Apply logarithmic scale. sarImageScaled = sarImageColl.log10().multiply(10.0) # Visualize results. sarVis = {"bands": ["VV", "VH", "VV"], "min": [-18, -23, 3], "max": [-4, -11, 15]} Map.addLayer(sarImageScaled, sarVis, "Sentinel-1 / SAR Mosaic") # ----------------------------------------------------------------------- # CHECKPOINT # -----------------------------------------------------------------------

Display the interactive map¶

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Map

Map