1

I have a bunch of .tiff files with lichen cover data, one for each three year period from 1986 to 2021, and I want to use either (or both) the Analyze change using LandTrendr/CCDC tools in ArcGIS Pro to analyze the changes over time.

So following a very general guideline, I created a mosaic dataset (coord:NAD_1983_CSRS_UTM_Zone_19N, product definition: Landsat OLI because the .tiff files are landsat data), but am unable to add any of my rasters to it. I'm using the Add Rasters to Mosaic Dataset tool, Raster type:Landsat 8, processing template: Multispectral (because I don't know really understand how to use templates and that's what it defaulted to), and I've tried the file and database Input Data parameters. The .tiff files have their own geodatabase in my project.

Whenever I try to add rasters to the mosaic, it processes for a bit before finishing with a yellow warning symbol and spitting out:

Error: 8004205f: No new mosaic dataset item was added.

Is there any way I could work around or solve this problem?

My end goal is simply to do continuous change analysis, so other tools would work too.

9
  • Have you tried changing the Product Definition or not specifying one? It may not be reading those files because the Product Definition isn't matching up. Commented Jan 29, 2022 at 20:29
  • I did not try that! It worked! thank you
    – James CW
    Commented Jan 29, 2022 at 20:56
  • Awesome! Could you mark my comment as an answer? Commented Jan 29, 2022 at 21:38
  • How exactly do I do that? I'm very new to this website
    – James CW
    Commented Jan 30, 2022 at 0:19
  • also, while I'm able to add the rasters now, I want to create a multidimensional raster, and this tutorial (pro.arcgis.com/en/pro-app/latest/help/data/imagery/…) is telling me to use NetCDF, and once changing the raster type the files are no longer adding to the mosaic. Do you have any idea how I could work around this? Would changing the file type help? If you don't know I'll post another question
    – James CW
    Commented Jan 30, 2022 at 0:33

0