Rsampling discrete raster datasets to create smooth landcover for use in bumpmapping
Hello ESRI Cartographers - I am developing a methodology for creating land-use categories for use in the bump mapping workflow. Essentially it is for maps or areas where suitable land-use data is not available. By using freely available ETM+ data (GLCF) and analysing it using NDVI (Normalised Difference Vegetation Index), I can reclassify the resulting raster into land-cover categories (5 or 6 categories - usually water, rock, soil, grass, open woodland/bushes and dense forest). I then seperate these out into vegetation masks using reclassification.
The trouble is the data is 30-60m resolution, and when I get the resulting rasters they are quite blocky, at the scale i am intending. Since the land-cover/bump mapping is to give an impression of land-cover for the reader (rather than for scientific purposes) I would like to resample down the discrete raster (may be to about 5m) and smooth it in to more pleasing, rounded LC parcels.
For the life of me I can't work out which method to use. I have tried resampling and using nieghbourhood statistics, Majority with circle 2-3 or rectangle 3, but with unsatisfactory results (areas of NoData and smaller blocks disappearing).
I have attached a Word file showing a diagram of what I am trying to do. In my example there Idouble the resolution, but in reality I would like to increase it by a factor of 10.
I would like to share my workflow with your readers once I have refined this aspect of it. I have already achieve magnificent results for smaller scale maps, this question relates to my ability to create effective larger scale maps.
Mapping Center Answer:
You will likely find the workflow you are looking for in online help for the Generalization toolset in Spatial Analyst -- here is a link to the online help to get you started: An overview of the Generalization toolset.
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