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Returns a HTML that when rendered using an HTML viewer or via a Jupyter Notebook, displays the raster as a square image of side length imageWidth. Optionally, an imageWidth parameter can be passed to RS_AsImage in order to increase the size of the rendered image (default: 200).
This function only works for rasters with byte data, and bands ≤ 4 (Grayscale - RGBA). You can check the data type of an existing raster by using RS_BandPixelType or create your own raster by passing 'B' while using RS_MakeEmptyRaster.

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Signatures

RS_AsImage(raster: Raster, imageWidth: Integer = 200)

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Parameters

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raster
Raster
required
The input raster.
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imageWidth
Integer
default:"200"
required
The image width value.

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Return type

A string representation.

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Examples

SELECT RS_AsImage(raster, 500) from rasters
SELECT RS_AsImage(raster) from rasters

"<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAECAAAAABjWKqcAAAAIElEQVR42mPgPfGfkYUhhfcBNw+DT1KihS6DqLKztjcATWMFp9rkkJgAAAAASUVORK5CYII=\" width=\"200\" />";

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Display raster in Jupyter

SedonaUtils.display_image(df) is a Python wrapper that renders raster images directly in a Jupyter notebook. It automatically detects raster columns in the DataFrame and applies RS_AsImage under the hood, so you don’t need to call RS_AsImage yourself. You can also pass a DataFrame with pre-applied RS_AsImage HTML. 
from sedona.spark import SedonaUtils

df = (
    sedona.read.format("binaryFile")
    .load(DATA_DIR + "raster.tiff")
    .selectExpr("RS_FromGeoTiff(content) as raster")
)

# Pass the raw raster DataFrame directly — RS_AsImage is applied automatically
SedonaUtils.display_image(df)

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— with explicit RS_AsImage

htmlDF = df.selectExpr("RS_AsImage(raster, 500) as raster_image")
SedonaUtils.display_image(htmlDF)
Output

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Text-based visualization