Standardize kernel density data?

Discussion created by bethyp on Dec 13, 2010
Latest reply on Aug 18, 2011 by lyn.g
Hi there,

I have transect survey data with animal counts that I successfully calculated kernel density for.  However, there are >20 transects total, and in some areas (not all), multiple transects were conducted.  Thus, the densities for these areas are inflated.  I would like to standardize my data for number of transects conducted within a certain cell. 

I have pondered this and tried a few things.  First, I tried to extract the kernel density raster and join to the table with transect data.  However, this doesn't work as my original table has >18,000 points, and the raster extraction then tries to match to each point.  Is there a way to extract kernel densities and match to the metadata (e.g., transect name)?  I don't think so, given how kernels work...

My next thought was to calculate kernel densities for each individual transect (>20), and then try to calculate mean density for all transects within cells.  However, I got stuck with this, as the cell statistics only seem to allow input of two different rasters at a time. 

I suppose I could calculate mean # animals/transect in advance, but each point is an individual location, and I would have to first bin the data into cells (say, 3-km), which I'm trying to avoid (unless anyone has advice on an easy way to do this!)...

Does anyone have any other ideas?

Thanks in advance...