99 landsat 9

Uncomment the following line to install geemap if needed.

Landsat 9 was successfully launched on Sept. 27, 2021. USGS has been providing Landsat data to the public since Feb. 10, 2022. Landsat 9 data can be downloaded from EarthExplorer. The Earth Engine team has been ingesting Landsat 9 into the Public Data Catalog. As of Feb. 14, 2022, although Landsat 9 data have not been publicly listed on the Earth Engine Datasets page, you can access the data through ee.ImageCollection('LANDSAT/LC09/C02/T1_L2') .

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# !pip install geemap

# !pip install geemap

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()

Map = geemap.Map()

Find out how many Landsat imgaes are available.

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collection = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2")
print(collection.size().getInfo())

collection = ee.ImageCollection("LANDSAT/LC09/C02/T1_L2") print(collection.size().getInfo())

Create a median composite.

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median = collection.median()

median = collection.median()

Apply scaling factors. See https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C02_T1_L2#bands

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def apply_scale_factors(image):
    opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2)
    thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0)
    return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)

def apply_scale_factors(image): opticalBands = image.select("SR_B.").multiply(0.0000275).add(-0.2) thermalBands = image.select("ST_B.*").multiply(0.00341802).add(149.0) return image.addBands(opticalBands, None, True).addBands(thermalBands, None, True)

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dataset = apply_scale_factors(median)

dataset = apply_scale_factors(median)

Specify visualization parameters.

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vis_natural = {
    "bands": ["SR_B4", "SR_B3", "SR_B2"],
    "min": 0.0,
    "max": 0.3,
}

vis_nir = {
    "bands": ["SR_B5", "SR_B4", "SR_B3"],
    "min": 0.0,
    "max": 0.3,
}

vis_natural = { "bands": ["SR_B4", "SR_B3", "SR_B2"], "min": 0.0, "max": 0.3, } vis_nir = { "bands": ["SR_B5", "SR_B4", "SR_B3"], "min": 0.0, "max": 0.3, }

Add data layers to the map.

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Map.addLayer(dataset, vis_natural, "True color (432)")
Map.addLayer(dataset, vis_nir, "Color infrared (543)")
Map

Map.addLayer(dataset, vis_natural, "True color (432)") Map.addLayer(dataset, vis_nir, "Color infrared (543)") Map

Create linked maps for visualizing images with different band combinations. For more information on common band combinations of Landsat 8/9, see https://gisgeography.com/landsat-8-bands-combinations/

Specify visualization parameters.

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vis_params = [
    {"bands": ["SR_B4", "SR_B3", "SR_B2"], "min": 0, "max": 0.3},
    {"bands": ["SR_B5", "SR_B4", "SR_B3"], "min": 0, "max": 0.3},
    {"bands": ["SR_B7", "SR_B6", "SR_B4"], "min": 0, "max": 0.3},
    {"bands": ["SR_B6", "SR_B5", "SR_B2"], "min": 0, "max": 0.3},
]

vis_params = [ {"bands": ["SR_B4", "SR_B3", "SR_B2"], "min": 0, "max": 0.3}, {"bands": ["SR_B5", "SR_B4", "SR_B3"], "min": 0, "max": 0.3}, {"bands": ["SR_B7", "SR_B6", "SR_B4"], "min": 0, "max": 0.3}, {"bands": ["SR_B6", "SR_B5", "SR_B2"], "min": 0, "max": 0.3}, ]

Specify labels for each layers.

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labels = [
    "Natural Color (4, 3, 2)",
    "Color Infrared (5, 4, 3)",
    "Short-Wave Infrared (7, 6 4)",
    "Agriculture (6, 5, 2)",
]

labels = [ "Natural Color (4, 3, 2)", "Color Infrared (5, 4, 3)", "Short-Wave Infrared (7, 6 4)", "Agriculture (6, 5, 2)", ]

Create linked maps.

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geemap.linked_maps(
    rows=2,
    cols=2,
    height="400px",
    center=[40, -100],
    zoom=4,
    ee_objects=[dataset],
    vis_params=vis_params,
    labels=labels,
    label_position="topright",
)

geemap.linked_maps( rows=2, cols=2, height="400px", center=[40, -100], zoom=4, ee_objects=[dataset], vis_params=vis_params, labels=labels, label_position="topright", )

Create a split-panel map for comparing Landsat 8 and 9 images.

Retrieve two sample images.

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landsat8 = ee.Image("LANDSAT/LC08/C02/T1_L2/LC08_015043_20130402")
landsat9 = ee.Image("LANDSAT/LC09/C02/T1_L2/LC09_015043_20211231")

landsat8 = ee.Image("LANDSAT/LC08/C02/T1_L2/LC08_015043_20130402") landsat9 = ee.Image("LANDSAT/LC09/C02/T1_L2/LC09_015043_20211231")

Apply scaling factors.

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landsat8 = apply_scale_factors(landsat8)
landsat9 = apply_scale_factors(landsat9)

landsat8 = apply_scale_factors(landsat8) landsat9 = apply_scale_factors(landsat9)

Generate Earth Engine layers.

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left_layer = geemap.ee_tile_layer(landsat8, vis_natural, "Landsat 8")
right_layer = geemap.ee_tile_layer(landsat9, vis_natural, "Landsat 9")

left_layer = geemap.ee_tile_layer(landsat8, vis_natural, "Landsat 8") right_layer = geemap.ee_tile_layer(landsat9, vis_natural, "Landsat 9")

Create a split-panel map.

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Map = geemap.Map()
Map.split_map(left_layer, right_layer)
Map

Map = geemap.Map() Map.split_map(left_layer, right_layer) Map

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