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Project Rasters-  What are the best practices for continuous data?

Question asked by jbrengel on Feb 18, 2019
Latest reply on Feb 18, 2019 by jbrengel

I'm trying to project a PRISM precipitation raster to match a vector data's projected coordinate system so that I can perform zonal statistics on it.   The original raster data has a GCS of NAD 1983 and I'm trying to project it into Albers Equal Area Conic.  What should be the anticipated effect of using the Project Raster GP tool (ArcMap 10.4, SP1) on my original raster dataset?  

 

It appears that the cell size, extent, and spatial location have all changed between my original dataset and my projected dataset.  I used measure tool to check cell size.  Also, the suggested resampling technique for continuous precipitation data should either be cubic of bilinear, but regardless of what resampling I choose, there are changes to the original dataset.

 

I'm not sure if these changes are to be expected and acceptable.  From my couple days of research and discussions with coworkers, there are not a lot of available resources on the topic of raster projection and its best practices. 

 

Should I just scrap the idea of projecting the raster and use the dataset's original GCS for my zonal statistic analysis?

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