[Proj] Re: Graduated equidistant projections for convenient co-ordinate transformations

[Michael Ossipoff]

Daan--

You wrote:

It is constant scale along meridians, combined with straight meridians, that 
defines equidistance. The sinusoidal fulfills neither criterion.

I reply:

Ok, I'd just assumed that equidance just meant equidistantly-spaced 
parallels. Though all the projections I've heard called by that name have 
straight meridians too, I didn't know that was also a requirement.

But that doesn't really change anything with respect to what I said in my 
previous posting.

Equidistant or not, the sinusoidal makes it easy to find lat/long for a 
particular point on the map. That's what I was interested in and was talking 
about. Sure, the measurement is easiest of all if both the parallels and 
meridians are straight.

And the definition of equidistance doesn't change the fact that it's 
difficult to come up with a scenario in which someone needs to directly 
measure accurate distances from a range map in a nature guidebook or an 
atlas data map.

To clarify my preferences, I personally would prefer graduated cylindrical 
equidistant for data maps, but I understand that some want equal area for 
some kinds of data, such as forest-type or land-use.
Sinusoidal is a compromise for that.

But 'm willing to work for position information on a data map, which is why 
an incompletely-specified azimuthal equal area data map is the only one that 
I seriously object to, when speaking for myself.  But most map users don't 
want to do calculating work to find positions--other than linear 
interpolation. For them, something like the sinusoidal, or equidistant maps, 
including graduated equidistant, would be the only way they'd get good  
position information from a data map. How many people around the world are 
trying to linearly interpolate positions from azimuthal equal area data 
maps?

Michael Ossipoff