Cartographic Projection
every map is wrong, and by exactly how much
Concept

Local minimum — where it appears

A point at which an objective is smaller than everywhere nearby but not smaller than everywhere. The three-parameter aspect objective has twenty-six to thirty-four of them on a coarse grid, so a downhill search from an arbitrary start reaches the best one only sometimes.

Named by 5 essays across one field — each of them below, with the objects they name alongside it.

Where the projection's pole should go, and the answer the third rotation moves it to. Every dot is a pole position the search tried, sized by the best score it can reach there when the third rotation is also free — the score is the distortion of Robinson over Europe by Kavrayskiy's criterion, so smaller is better and the large green dots are the good regions. The circled mark is the two-parameter optimum and the square is the three-parameter one: they are 74 pixels apart on this map, which is a different aspect rather than a refinement of the same one. The search costs 8 times the evaluations of the two-parameter one. Drawn in Mollweide.

The third parameter, run

An aspect has three numbers and this site has been searching two of them, with a note admitting it. Searching all three is worth up to 2.1 times — and the obvious way to do it, starting from the two-parameter answer and letting the third move, finds a fraction of that or nothing at all.

choosing · Choosing One slice of the aspect objective, at the best γ. The Kavrayskiy score for Robinson over Japan, as the pole is moved over the whole sphere with the third rotation held at the value the search settled on. Dark is good. The marks are local minima of the full three-dimensional grid that happen to lie in this slice: there are 6 of them here and 58 in the cube, and a search that walks downhill from a random start reaches the best of them 7 per cent of the time.

The landscape the search walks on

The three-parameter aspect search was run and its answer recorded with a note admitting nothing proved it global. Mapping the objective finds 26 to 34 local minima for every projection and region tried, a downhill walk from a random start reaching the best of them 6 to 35 per cent of the time — and one seed from the coarse grid the search already uses reaching it in all four cases. The score is reproducible to two per cent across a sevenfold refinement; the pole it names moves 60 degrees.

choosing · Choosing The set of aspects within a stated distance of the best, for Robinson over Japan. Each row takes every point of a 36 × 19 × 24 grid in the three aspect parameters that scores within (1 + t) of the best, joins neighbouring points, and identifies the pieces the exact degeneracy relates. At t = 3 it is one connected piece spanning 170° of pole; by t = 1 it has broken into 2 pieces; and by t = 0.3 the largest of them spans 11°. So it is not one valley and it is not one basin — it is a sheet that fractures.

The shape of the valley

An aspect search returns three numbers, two searches return triples that differ by a hemisphere, and the maps they produce agree. One cause is an exact degeneracy and the rest was called a valley and left unmeasured. Sampled densely, it is neither a valley nor a basin: a connected sheet spanning 170° of pole that splits in two at twice the best score and into thirteen pieces by 1.7 times it.

choosing · Choosing Where Robinson's valley breaks, against how large the region is. The threshold at which the set of near-optimal aspects stops being one connected piece, for square regions of growing size at 38° north. It falls from 2.10 at 6° to 0.27 at 30°, a factor of 7.9. The earlier measurement was made at one region and quoted "about twice the optimum"; that value belongs to a small region, and the prediction that it should fall as the region grows is what this tests.

Where the valley breaks in two

A near-optimal set is one connected sheet at a loose threshold and thirteen basins at a tight one, and the transition was explained without being tested. The explanation is a prediction about region size and projection sharpness: swept over both, the threshold falls from 2.10 to 0.27 as a region grows from 6° to 30°, three projections lie on nearly one curve, and a fourth declines to join for a reason worth having.

choosing · Choosing The piece count rises and falls. The number of connected pieces of the near-optimal aspect set for Robinson over Japan, swept finely through the threshold rather than sampled once below it. It is one piece at a wide threshold, reaches 13 at 1.010, and returns to one as the set shrinks onto the single best aspect. The set first disconnects at 1.941, which is above the peak: the pieces keep multiplying after the first break. This is the sweep the earlier measurement could not afford and it costs one grid, because every threshold reads the same 4992 evaluations.

The threshold is not a percolation

The near-optimal aspect set was found breaking into twelve pieces rather than two, the transition was called a percolation, and the exponent went unmeasured. Swept finely, the piece count rises from one to thirteen and falls back to one — and refining the grid by a factor of fifteen moves the peak from ten to nineteen, at the rate the surface's own minima grow, while an uncorrelated field on the same lattice grows by a factor of twelve.

choosing · Choosing

Named alongside it

The objects these essays reach for when they reach for this one.

AspectOptimisationSearchDegeneracyIdentifiabilityLevel setObjective functionParameter searchReproducibilitySymmetryKavrayskiy's criterionOblique projection

All concepts