Kernel Density and map algebra to convert square degrees to km^2

[MattFondacaro]

Normally I'd ask my professor this question but I haven't heard back from it, so I'm sending it out to the community for help. 

whaleKernelDens = KernelDensity("whales", "n_whales")

This returns values from my data, ranging from 0.001-53,115.309. The value units are in square degrees. Converting it to km2, I did the following (assuming my latitude is 38 degrees North & 1 degree of latitude is 111km):

cos(38 deg N) = .788

111 km x .788 = 87.468 km (1 degree of longitude)

87.468 km squared = 7650.651024 km2 is in one square degree of area

I hope I got my math right.

Now I make my out_raster (which I will call whaleDensKm2) and make an expression that display my results in km2, not square degrees. Am I using KernelDensity() for this? I'm trying to put together something but I get errors:

whaleDensKm2 = KernelDensity("whales", "n_whales", "SQUARE_KILOMETERS")

I have my in point features, I have my population field, I want the results in square kilometers... am I missing something?

[DavidSolari]

Not too familiar with the kernel functions, but if you project your raster into a coordinate system that uses meters that should make it easier to get square kilometers out. I'd go with an equal-area system appropriate for your study area that has the same datum as your current raster to avoid datum translations.