I have processed some LiDAR data to create a canopy height .TIF image. When I view the canopy height in arc map, in the table of contents, it says that the range of the is from -20 to 61. I'm curious where the data is that's below zero, especially where it's -20. Is there a way to query the image and find places where the pixel value is below zero and then zoom to that location in the map?
When you have a large number of rows and columns, the classification might not visualize isolated pixels that have the negative canopy height. As an alternative you could use the Extract By Attributes tool (SA) to extract the pixels that you are interested in followed by Raster to Point (Conversion) to create a point featureclass with a point in the pixels you're interested in.
Well, you could symbolize your lidar using classified, and then manually change the classification so that the first class is -20-0, and then examine the raster for that class visually.
When you have a large number of rows and columns, the classification might not visualize isolated pixels that have the negative canopy height. As an alternative you could use the Extract By Attributes tool (SA) to extract the pixels that you are interested in followed by Raster to Point (Conversion) to create a point featureclass with a point in the pixels you're interested in.
You could also just use the tool Data management tools > Raster > Raster properties > Calculate raster attribute table to get a table for your raster. Since you are working with integers (?) this should do the trick. You can now open the table, sort the table entries by value and select all sub-zero values.
I would assume that the canopy height based on LiDAR to be floating, but true if the data is integer you could do this, but still single isolated pixels will be hard to spot is the extent (rows x cols) is big. It might be displaying pyramids not showing those isolated pixels.
Thanks for your help.. My raster image is a TIF and it stores float values, so I couldn't use the Data management tools > Raster > Raster properties > Calculate raster attribute table tool. I was able ot use the approach which Xander gave and it helped me find the places where the canopy height was calculated to be negative.
