Fibonacci lattices for the evaluation and optimization of map projections

Abstract Latitude-longitude grids are frequently used in geosciences for global numerical modelling although they are remarkably inhomogeneous due to meridian convergence. In contrast, Fibonacci lattices are highly isotropic and homogeneous so that the area represented by each lattice point is virtually the same. In the present paper we show the higher performance of Fibonacci versus latitude-longitude lattices for evaluating distortion coefficients of map projections. In particular, we obtain first a typical distortion for the Lambert Conformal Conic projection with their currently defined parameters and geographic boundaries for Europe that has been adopted as standard by the INSPIRE directive. Further, we optimize the defining parameters of this projection, lower and upper standard parallel latitudes, so that the typical distortion for Europe is reduced a 10% when they are set to 36° and 61.5°, respectively. We also apply the optimization procedure to the determination of the best standard parallels for using this projection in Spain, whose values remained unspecified by the National decree that commanded its official adoption, and obtain optimum values of 37° and 42° and a resulting typical distortion of 828 ppm.

[1]  Frank Canters,et al.  The World in Perspective: A Directory of World Map Projections , 1989 .

[2]  S. Baselga Second Order Design of Geodetic Networks by the Simulated Annealing Method , 2011 .

[3]  John P. Snyder,et al.  Map Projections: A Working Manual , 2012 .

[4]  N. J. A. Sloane,et al.  Sphere Packings, Lattices and Groups , 1987, Grundlehren der mathematischen Wissenschaften.

[5]  Vittorio Loreto,et al.  Congestion Transition in Air Traffic Networks , 2015, PloS one.

[6]  Inés Santé-Riveira,et al.  Algorithm based on simulated annealing for land-use allocation , 2008, Comput. Geosci..

[7]  Frank Canters,et al.  Small-Scale Map Projection Design , 2002 .

[8]  First-order design of geodetic networks using the simulated annealing method , 2004 .

[9]  E. Gilbert Distortion in Maps , 1974 .

[10]  Bojan Savric,et al.  Automating the selection of standard parallels for conic map projections , 2016, Comput. Geosci..

[11]  C. Crǎciun Homogeneity and EPR metrics for assessment of regular grids used in CW EPR powder simulations. , 2014, Journal of magnetic resonance.

[12]  Shashi Prakash Sharma,et al.  VFSARES - a very fast simulated annealing FORTRAN program for interpretation of 1-D DC resistivity sounding data from various electrode arrays , 2012, Comput. Geosci..

[13]  Bernhard Jenny Adaptive Composite Map Projections , 2012, IEEE Transactions on Visualization and Computer Graphics.

[14]  A. Mercer,et al.  Predictability of US tornado outbreak seasons using ENSO and northern hemisphere geopotential height variability , 2016 .

[15]  Thomas Koshy,et al.  Fibonacci and Lucas Numbers With Applications , 2018 .

[16]  Hadi Mokhtari,et al.  Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization , 2016, Comput. Geosci..

[17]  Donald Fenna,et al.  Cartographic Science: A Compendium of Map Projections, with Derivations , 2006 .

[18]  Xiao Song,et al.  Averaged ratio between complementary profiles for evaluating shape distortions of map projections and spherical hierarchical tessellations , 2016, Comput. Geosci..

[19]  R. Swinbank,et al.  Fibonacci grids: A novel approach to global modelling , 2006 .

[20]  Álvaro González Measurement of Areas on a Sphere Using Fibonacci and Latitude–Longitude Lattices , 2009, 0912.4540.

[21]  Luís Paulo Santos,et al.  Spherical Fibonacci Point Sets for Illumination Integrals , 2013, Comput. Graph. Forum.

[22]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[23]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[24]  Sylvie Le Hégarat-Mascle,et al.  Using simulated annealing algorithm to move clod boundaries on seedbed digital elevation model , 2013, Comput. Geosci..

[25]  Wolfgang Wagner,et al.  Optimisation of global grids for high-resolution remote sensing data , 2014, Comput. Geosci..