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2

GeoServer provides rendering transformations that can do exactly this. The manual contains an example using Jiffle that calculates NDVI on the fly from multiband Sentinel data. <Transformation> <ogc:Function name="ras:Jiffle"> <ogc:Function name="parameter"> <ogc:Literal>coverage</ogc:Literal> ...


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Here is a code i adapted for you, it worked on my qgis 2.18.28: b = iface.activeLayer() fni = b.fieldNameIndex("rgb") unique_values = b.uniqueValues(fni) # fill categories categories = [] for unique_value in unique_values: red, blue, green = unique_value.split(",") # initialize the default symbol for this geometry type ...


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You could try to define visualization parameters and then make a new variable where you add the visualization. It would look something like this: var vis = { min: 0, max: 3000, bands:['B4','B3','B2'], }; var ffa_db_new = ffa_db.visualize(vis); And then you export the new variable ffa_db_new instead of the old one.


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Having only RGB you cannot calculate the NDVI. As stated in the comment, you need as well the NIR (near-infrared) channel (https://gisgeography.com/ndvi-normalized-difference-vegetation-index/)


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Try to build a Virtual Raster. Make sure to check Place each input file into a separate band


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Looks like you haven't defined a variable called image - which is what you pass along to the visualize() function. Try changing your visualize line to: var imageRGB = dataset.median().visualize({bands: ['B4', 'B3', 'B2'], min: 0, max: 2500}); print("rgb",imageRGB); You’ll also need to update the geometry in your export because ‘image’ doesn’t ...


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The palr package has a function image_raster for the task of baking in the palette to RGB version of the raster. (You can set the extent and projection using raster itself as usual). library(raster) #> Loading required package: sp r <-raster(volcano) library(palr) ## apply the colours used by raster plot() itself rgb0 <- image_raster(r, col = ...


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