141 image array viz

Visualizing in-memory raster datasets and image arrays

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# !pip install -U geemap

# !pip install -U geemap

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import ee
import geemap

import ee import geemap

Use a Landsat image covering San Francisco Bay Area.

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m = geemap.Map()
image = ee.Image("LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318").select(
    ["B5", "B4", "B3"]
)
vis_params = {
    "min": 0.0,
    "max": 0.4,
}
m.add_layer(image, vis_params, "False Color (543)")
m.centerObject(image)
m

m = geemap.Map() image = ee.Image("LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318").select( ["B5", "B4", "B3"] ) vis_params = { "min": 0.0, "max": 0.4, } m.add_layer(image, vis_params, "False Color (543)") m.centerObject(image) m

Retrieve the projection information from the image.

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projection = image.select(0).projection().getInfo()
crs = projection["crs"]
crs

projection = image.select(0).projection().getInfo() crs = projection["crs"] crs

Read the Earth Engine image into an Xarray DataArray.

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ds = geemap.ee_to_xarray(
    image, crs="EPSG:32610", scale=300, geometry=image.geometry(), ee_mask_value=0
)
ds

ds = geemap.ee_to_xarray( image, crs="EPSG:32610", scale=300, geometry=image.geometry(), ee_mask_value=0 ) ds

Save the DataArray as a Cloud Optimized GeoTIFF.

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geemap.xee_to_image(ds, filenames=["landsat.tif"])

geemap.xee_to_image(ds, filenames=["landsat.tif"])

Calculate the NDVI and save it to the DataArray.

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ndvi = (ds["B5"] - ds["B4"]) / (ds["B5"] + ds["B4"])

ndvi = (ds["B5"] - ds["B4"]) / (ds["B5"] + ds["B4"])

Create an in-memory raster dataset from the DataArray.

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ndvi_image = geemap.array_to_image(ndvi, source="landsat.tif")

ndvi_image = geemap.array_to_image(ndvi, source="landsat.tif")

Visualize the in-memory raster dataset.

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m.add_raster("landsat.tif", indexes=[1, 2, 3], nodata=-1, layer_name="Landsat 7")
m.add_raster(ndvi_image, colormap="Greens", layer_name="NDVI")
m

m.add_raster("landsat.tif", indexes=[1, 2, 3], nodata=-1, layer_name="Landsat 7") m.add_raster(ndvi_image, colormap="Greens", layer_name="NDVI") m

Save the in-memory raster dataset to a GeoTIFF file.

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geemap.array_to_image(ndvi, output="ndvi.tif", source="landsat.tif")

geemap.array_to_image(ndvi, output="ndvi.tif", source="landsat.tif")