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I have been manually digitizing drone imagery to create a training data set for different land cover classifications. I have created a feature class dataset and digitized my different land cover classes, but cannot for the life of me figure out how to stitch these together so I can export it as a singular dataset/training image.

I have tried merge which did not maintain the land cover classes and then tried converting each shapefile into a raster and stitching the rasters together using the mosaic to new raster tool. None of these options have successfully created a singular image where the land cover classes are maintained separately. I know there has to be an easy solution to this that I am overlooking, but GIS is not my strong suit and I am having a difficult time.

Any suggestions? I have included a picture of my digitized image and land cover classes below.

Digitized Image

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    You state that you used the merge tool but merge help states that 'by default, the output includes all fields from the input datasets.' Sounds like a field mapping issue. Can you post a screen shot of your merge tool from the history? Or maybe try again with all of your shapefiles: pro.arcgis.com/en/pro-app/latest/tool-reference/data-management/…
    – GBG
    Commented Nov 20, 2023 at 19:46
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    Welcome to GIS SE. As a new user, please take the Tour. Your Question is unclear, because it simultaneously references shapefiles (vectors) and a resulting image (raster). An Append will assemble multiple sources as a single feature class, but you need to have clear attribution in common columns or it will get quite difficult to preserve data
    – Vince
    Commented Nov 20, 2023 at 19:47

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To be aggregated together, each layer should have the same fields. Add a new field category to each of your individual layer, and populate it (ex, for the white_ash layer, all features will have the white_ash value in the category field), then merge the layer as you wish.

At last, do the symbology for this new layer.

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  • This worked thank you!
    – greg684
    Commented Nov 20, 2023 at 20:04

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