1 Introduction Many apparently compelling techniques for automatic label placement use sophisticated heuristics for capturing cartographic knowledge, but, as noted by Zoraster (1991), also use inferior optimization strategies for finding good tradeoffs betwe. We present an algorithm for label placement that achieves the twin goals of practical efficiency and high labeling quality by combining simple cartographic heuristics with effective stochastic optimization techniques. On the other hand, no approach to label placement that is based on an efficient optimization technique has been applied to the production of general cartographic maps - those with labeled point, line, and area features - and shown to generate labelings of acceptable quality. Some apparently powerful algorithms for automatic label placement on maps use heuristics that capture considerable cartographic expertise but are hampered by provably inefficient methods of search and optimization. He look of surveillance returns as the displacing gaze of the disciplined, the observer becomes the observed and the partial representation rearticulates the whole notion of identity and alienates it from essence. an instrument of colonial power could be reappropriated by colonized people. Such visualizations from a distance became critical in choreographing the colonial expansion of early modern Europe. Maps were the first step in the appropriation of territory. provide perhaps the most spectacular illustrations of how an anticipatory geography served to frame colonial territories in the minds of statesmen and territorial speculators back in Europe. In order for such disruptive effects to be realized, it is necessary to shuttle between demythologizing and deconstructing the map—two modes of analysis that need to be better distinguished in scholarship that addresses maps as technologies of power/knowledge. And epistemologically, it serves to put into question some of the dominant modes of classifying 'indigenous cartography' within cartographic history. Historically, it disrupts a traditional treatment of native people as at once sacrificial victims and heroic proxies in Canadian national history. Geographically, it displaces the 'new'-ness and emptiness of the Europeans' Newfoundland. Understood as the product of an agent of knowledge, the cartographic work of Shawnadithit (the last known Beothuk survivor in Newfoundland) questions a whole set of essential and Eurocentric notions of identity, space and history. The "Gott equal-area elliptical" projection produces a particularly attractive map of Mars, and the "Gott-Mugnolo azimuthal" projection produces an interesting map of the moon. The "Gott-Mugnolo azimuthal" has the lowest distance errors of any map and is produced by a new technique using "forces" between pairs of points on a map which make them move so as to minimize s. We present new projections: the "Gott equal-area elliptical" with perfect shapes on the central meridian, the "Gott-Mugnolo equal-area elliptical" and the "Gott-Mugnolo azimuthal" with rms logarithmic distance errors of s=0.365, s=0.348, and s=0.341 respectively, which improve on previous projections of their type. For comparison, the Mercator has s=0.444, and the Mollweide has s=0.390. The best previously known projection of the entire sphere for distances is the Lambert equal-area azimuthal with an rms logarithmic distance error of s=0.343. Since it is as bad to have two points on the map at two times their proper separation as to have them at half their proper separation, it is the rms logarithmic distance, s, between random points in the mapped region that we will minimize. Any local error criterion will be minimized ultimately by map projections with multiple interruptions, on which some pairs of points that are close on the globe are far apart on the map. The Chebyshev criterion for minimizing rms (root mean square) local scale factor errors for conformal maps has been useful in developing conformal map projections of continents. It is useful to have mathematical criteria for evaluating errors in map projections.
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