Well, who'd have thought there was such an obvious explanation? Good stuff!
Adrian Custer wrote: > On Mon, 2007-09-17 at 10:46 -0700, Jody Garnett wrote: > >> Edgar Soldin wrote: >> >>> just one question .. what is this bursa wolf parameter option? >>> > > ... > > >> My impression is that this is scary math I never quite understood. The >> javadocs describe it all detail (and have links to papers etc..). >> > > > Well, Bursa was a 9 year old bicyclist from the Alps and...no, no, no, i > lie. Actually it's not particularly scary math and quite easy to > understand. All you really need to remember is that no one has ever been > to the center of the earth. > > So everyone started surveying (mostly so the repressive central > governments could exploit taxes from people and have lots of jolly wars > where people could slog through the mud and kill each other so they'd be > blood and suffering for all). Each group started from some random place > on the surface of the earth. Right away, it becomes obvious to everyone > that euclidean rules don't work so well. Some didn't care so much since > taxes are basically arbitrary anyway and getting serious about it means > you'd have to walk through fields and woods and get lots of mud on your > shoes. Others kept at it and resorted to spherical geometry. Once you > start doing that precisely and at continental scales you realize that > doesn't really work either so you decide to try the next hardest thing, > an ellipsoid of rotation. Now how do you know which one to choose? Well > you pick one that minimizes your squared errors. All good and nice but > (1) you are surveying the ground which is anything but an ellipsoid > since it has all those ditches you keep falling into and that keep > getting your clothes covered in mud and (2) you are not perfect > especially with all that mud on your paper. So you have a bunch of > errors. Well everyone that does this comes up with lots of different > ellipsoids that work really nice for their data and everyone is sure > they clearly have found the 'one true ellipsoid' and they decide to use > that for all their work. Then everyone guesses where they actually are > on each of their particular ellipsoids which involves lots of going > outside at night and looking up from the mud at the stars. But then it's > not like the edges of each survey was nice and level on these ellipsoids > either --- think of the eastern USA. You can start nice and clean and > warm and dry at an inn in Boston on the edge of the sea drinking clam > chowder and having a good time but a few months later it will be bitter, > bitter cold in that tiny town of Denver because you are somewhere like a > mile high up in the air and you're wet and covered in mud from slogging > through the plains in a snowstorm. So you've got a pretty good idea that > your data is on a major slant but, well, you'll do your best to make up > for it but it really doesn't help the effort any, especially what with > all that mud that's still itching in your hair. So your errors may be a > wee bit big but hey it's all right: it's good enough to wage lots of > good wars with lots of mud and blood and to keep collecting lots of > taxes so no one cares too much. > > Fast forward to more recent times where some people want to talk to lots > of different governments and work with lots of different data. They take > everyone's guess and try to line them up. Well it turns out, when you > try to line everything up, that the center points of all the different > ellipses aren't really the same points and even the orientation of the > three axes are all a bit off because of how everyone guessed where their > were on their ellipsoids. So now, to go from one data set to another so > they line up "the best," you need estimates of how much to rotate each > of the axes and how to shift the center point around; all this beyond > even the obvious stuff of changing between the different definition of > all those "one true" ellipsoids. > > When you do this mathematically, you need a bunch of parameters: these > now have the names of the wolf and the bursa. Generally, you can only > come up with good parameters if you have lots of data to compare and > some good software to do the comparing. That's what the EPSG did for > everyone. The guys in the pickup trucks that went out looking for oil > kept falling into ditches along the way and getting mud on their faces > but when they got back to the office they had a good sense of what lined > up with what and could say: "yep, that hill there is the same as this > squiggle here and there's this big ditch right here that cost us our > third flat tire and..." So they collected as much data as they could and > compared it and came up with a database of parameters by which you go > from one data set to another. So that's it. That's why we use their > data; we don't have to fall in any ditches and can avoid getting mud on > our clothes. They give us their parameters and we can mostly line up > data from one survey against data from another. But you do need some > good parameters because the earlier folk had a harder time of the mud > and the data they created don't just line up the way we would like them > to. > > Actually doing the math is a bit harder but the concept is pretty > straight forward: geographic data all ultimately gets tied into points > on the earth surface and that requires estimating where the points > really are and how they line up on the estimated ellipsoid being used. > That in turn means none of ellipsoids quite line up and we need > parameters to move between them. > > --adrian > > > ------------------------------------------------------------------------- > This SF.net email is sponsored by: Microsoft > Defy all challenges. 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