however, this ‘best estimate’ value for t doesn’t actually agree with the translation at any of the three known points. we need to compute a statistic that represents the ‘amount of disagreement’ with this estimate among the known points. this is the standard deviation of the three individual t values from the average t value: t(cid:86) (cid:32) ( t white (cid:16) 2 t ) (cid:14) ( t grey (cid:16) 2 t ) (cid:14) ( t black (cid:16) 2 t ) 3 (cid:32) 17.0 so our estimate of t would be written t (cid:32) 2.80 to 3.14 based on the information we have available. it is common to state a range of three standard deviations as a likely range within which the true figure lies, that is, between 2.46 and 3.48. , that is, t could quite probably be anything from (cid:114) 2 97 017 . . so what is the transformation between datum a and datum b? we don’t know exactly, and we can never know exactly. but we have a best estimate and a measure of the likely error in the estimate. the point of all this is that since trfs aren’t perfect, neither are transformations between the datums they realise. in practice, this means that no exact transformation exists between two geodetic coordinate systems. people often assume, quite reasonably, that the transformation between two ellipsoidal datums can be exactly specified, in the way that a map projection can. in theory, this is true, but what use would it be? what you really want to know is what the transformation is for real points on the ground – so you are actually asking a question about trfs. and the answer to such a question is always an approximation. the degree of error in a geodetic transformation will depend on the patterns of errors present in the trfs a and b (which are often characteristic of the methods used to establish the trf in the first place), and also on how carefully the transformation has been designed to take account of those errors. for example, trfs established by triangulation generally contain significant errors in the overall size of the network and often, this scale error varies in different parts of the network. therefore, a real transformation is likely to represent not only the difference between geodetic datums, but also the difference between the trfs that realise those datums due to errors in the original observations. 6.2 helmert datum transformations the ways in which two ellipsoidal datums can differ are (i) position of the origin of coordinates; (ii) orientation of the coordinate axes (and hence of the reference ellipsoid) and (iii) size and shape of the reference ellipsoid. if we work in 3d cartesian coordinates, item (iii) is not relevant (and any position given in latitude, longitude and ellipsoid height coordinates can be converted to 3d cartesian coordinates using the formulae in annexe b). working with 3d cartesian coordinates, therefore, we use six parameters to describe the difference between two datums, which are three parameters to describe a 3d translation between the coordinate origins, and three parameters to describe a 3d rotation between the orientations of the coordinate axes. it has become traditional to add a seventh parameter known as the ‘scale factor’, which allows the scale of the axes to vary between the two coordinate systems. this can be confusing because the scale factor is nothing to do with the conventional definition of the datum expressed by the six parameters mentioned above. it was introduced to cope with transformations between trfs measured by theodolite triangulation, which was the standard method before the latter half of the 20th century. these trfs have the characteristic that network shape (which depends on angle measurement) is well measured, but network size (which depends on distance measurements) is poorly measured, because distances were very hard to measure accurately before electronic techniques arrived in the 1950s. strictly speaking, a cartesian datum transformation has only six parameters, not seven. however, the scale factor is included in the usual formulation of the datum transformation, which is variously known as the ‘helmert transformation’, ‘3d conformal transformation’, ‘3d similarity transformation’, or ‘seven parameter transformation’. all these terms refer to the same thing. a guide to coordinate systems in great britain d00659 v2.3 mar 2015 © crown copyright page 29 of 43