I want to plot true-color Planet image from bands reflectance. I found the code in https://docs.sentinel-hub.com/api/latest/data/planet/planet-scope/examples/#true-color-full-3-meter-resolution; however, how to achieve that by Python code?
Solved
How to plot true-color Planet image by Python
+1Best answer by elyhienrich
Hi
There are two Python-based approaches to render true color from PlanetScope reflectance imagery.
Option A — Using Sentinel Hub Process API (PlanetScope ARD in BYOC)
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This uses an evalscript that maps red/green/blue to RGB and scales reflectance (DN ~ 0–10000) to 0–1 with a small brightness boost. Replace your BYOC collection ID, bbox/geometry, and time interval as needed.
Option B — Local GeoTIFF (Analytic SR) with Rasterio and NumPy
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If you already have PlanetScope analytic SR GeoTIFFs (scaled by 10000), map bands to RGB and apply a simple display stretch. Try clipping and a non-linear curve for best visual results; a simple linear scaling works as a start.
I would recommend using the Ask Ai widget you can find in the banner here on Planet Community, you can share how your bands are named/ordered and whether you’re using local GeoTIFFs or Sentinel Hub BYOC, and the AI widget can tailor the python code to your exact setup.
+17- Community Manager 🌎
+1Hi
First of all, thank you for your reply.
I only downloaded the reflectance images and I cannot download visual images now. Therefore, I have to use reflectance image to get the true-color image. Do you have any other recommendation?
+17- Community Manager 🌎
- Answer
Hi
There are two Python-based approaches to render true color from PlanetScope reflectance imagery.
Option A — Using Sentinel Hub Process API (PlanetScope ARD in BYOC)
-
This uses an evalscript that maps red/green/blue to RGB and scales reflectance (DN ~ 0–10000) to 0–1 with a small brightness boost. Replace your BYOC collection ID, bbox/geometry, and time interval as needed.
Option B — Local GeoTIFF (Analytic SR) with Rasterio and NumPy
-
If you already have PlanetScope analytic SR GeoTIFFs (scaled by 10000), map bands to RGB and apply a simple display stretch. Try clipping and a non-linear curve for best visual results; a simple linear scaling works as a start.
I would recommend using the Ask Ai widget you can find in the banner here on Planet Community, you can share how your bands are named/ordered and whether you’re using local GeoTIFFs or Sentinel Hub BYOC, and the AI widget can tailor the python code to your exact setup.
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