Grid (spatial index)

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In the context of a spatial index, a grid or mesh is a regular[ citation needed ] tessellation of a manifold or 2-D surface that divides it into a series of contiguous cells, which can then be assigned unique identifiers and used for spatial indexing purposes. A wide variety of such grids have been proposed or are currently in use, including grids based on "square" or "rectangular" cells, triangular grids or meshes, hexagonal grids, and grids based on diamond-shaped cells. A "global grid" is a kind of grid that covers the entire surface of the globe.

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Types of grids

Geodesic Grid (ISEA3H) illustrated.png

Square or rectangular grids are frequently used for purposes such as translating spatial information expressed in Cartesian coordinates (latitude and longitude) into and out of the grid system. Such grids may or may not be aligned with the grid lines of latitude and longitude; for example, Marsden Squares, World Meteorological Organization squares, c-squares and others are aligned, while Universal Transverse Mercator coordinate system and various local grid based systems such as the British national grid reference system are not. In general, these grids fall into two classes, "equal angle" or " equal area ". Grids that are "equal angle" have cell sizes that are constant in degrees of latitude and longitude but are unequal in area (particularly with varying latitude). Grids that are "equal area" (statistical grids), that have cell sizes that are constant in distance on the ground (e.g. 100 km, 10 km) but not in degrees of longitude, in particular.

A commonly used triangular grid is the "Quaternary Triangular Mesh" (QTM), which was developed by Geoffrey Dutton in the early 1980s. It eventually resulted in a thesis entitled "A Hierarchical Coordinate System for Geoprocessing and Cartography" that was published in 1999. [1] This grid was also employed as the basis of the rotatable globe that forms part of the Microsoft Encarta product.

Hexagonal grids may also be used. In general, triangular and hexagonal grids are constructed so as to better approach the goals of equal-area (or nearly so) plus more seamless coverage across the poles, which tends to be a problem area for square or rectangular grids since in these cases, the cell width diminishes to nothing at the pole and those cells adjacent to the pole then become 3- rather than 4-sided. Criteria for optimal discrete global gridding have been proposed by both Goodchild and Kimerling [2] in which equal area cells are deemed of prime importance.

Quadtrees are a specialised form of grid in which the resolution of the grid is varied according to the nature and complexity of the data to be fitted, across the 2-d space. Polar grids utilize the polar coordinate system, using circles of a prescribed radius that are divided into sectors of a certain angle. Coordinates are given as the radius and angle from the center of the grid.

Grid-based spatial indexing

In practice, construction of grid-based spatial indices entails allocation of relevant objects to their position or positions in the grid, then creating an index of object identifiers vs. grid cell identifiers for rapid access. This is an example of a "space-driven" or data independent method, as opposed to "data-driven" or data dependent method, as discussed further in Rigaux et al. (2002)). [3] A grid-based spatial index has the advantage that the structure of the index can be created first, and data added on an ongoing basis without requiring any change to the index structure; indeed, if a common grid is used by disparate data collecting and indexing activities, such indices can easily be merged from a variety of sources. On the other hand, data driven structures such as R-trees can be more efficient for data storage and speed at search execution time, though they are generally tied to the internal structure of a given data storage system.

The use of such spatial indices is not limited to digital data; the "index" section of any global or street atlas commonly contains a list of named features (towns, streets, etc.) with associated grid square identifiers, and may be considered a perfectly acceptable example of a spatial index (in this case, typically organised by feature name, though the reverse is conceptually also possible).

Other uses

The individual cells of a grid system can also be useful as units of aggregation, for example as a precursor to data analysis, presentation, mapping, etc. For some applications (e.g., statistical analysis), equal-area cells may be preferred, although for others this may not be a prime consideration.

In computer science, one often needs to find out all cells a ray is passing through in a grid (for raytracing or collision detection); this is called "grid traversal".

See also

Related Research Articles

<span class="mw-page-title-main">Geographic coordinate system</span> System to specify locations on Earth

The geographic coordinate system (GCS) is a spherical or geodetic coordinate system for measuring and communicating positions directly on the Earth as latitude and longitude. It is the simplest, oldest and most widely used of the various spatial reference systems that are in use, and forms the basis for most others. Although latitude and longitude form a coordinate tuple like a cartesian coordinate system, the geographic coordinate system is not cartesian because the measurements are angles and are not on a planar surface.

<span class="mw-page-title-main">Projected coordinate system</span> Cartesian geographic coordinate system

A projected coordinate system – also called a projected coordinate reference system, planar coordinate system, or grid reference system – is a type of spatial reference system that represents locations on Earth using Cartesian coordinates (x, y) on a planar surface created by a particular map projection. Each projected coordinate system, such as "Universal Transverse Mercator WGS 84 Zone 26N," is defined by a choice of map projection (with specific parameters), a choice of geodetic datum to bind the coordinate system to real locations on the earth, an origin point, and a choice of unit of measure. Hundreds of projected coordinate systems have been specified for various purposes in various regions.

A geocode is a code that represents a geographic entity. It is a unique identifier of the entity, to distinguish it from others in a finite set of geographic entities. In general the geocode is a human-readable and short identifier.

The Natural Area Code, or Universal Address, is a proprietary geocode system for identifying an area anywhere on the Earth, or a volume of space anywhere around the Earth. The use of thirty alphanumeric characters instead of only ten digits makes a NAC shorter than its numerical latitude/longitude equivalent.

<span class="mw-page-title-main">Quadtree</span> Tree data structure in which each internal node has exactly four children, to partition a 2D area

A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are the two-dimensional analog of octrees and are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The data associated with a leaf cell varies by application, but the leaf cell represents a "unit of interesting spatial information".

<span class="mw-page-title-main">Z-order curve</span> Mapping function that preserves data point locality

In mathematical analysis and computer science, functions which are Z-order, Lebesgue curve, Morton space-filling curve, Morton order or Morton code map multidimensional data to one dimension while preserving locality of the data points. It is named in France after Henri Lebesgue, who studied it in 1904, and named in the United States after Guy Macdonald Morton, who first applied the order to file sequencing in 1966. The z-value of a point in multidimensions is simply calculated by interleaving the binary representations of its coordinate values. Once the data are sorted into this ordering, any one-dimensional data structure can be used, such as simple one dimensional arrays, binary search trees, B-trees, skip lists or hash tables. The resulting ordering can equivalently be described as the order one would get from a depth-first traversal of a quadtree or octree.

Address geocoding, or simply geocoding, is the process of taking a text-based description of a location, such as an address or the name of a place, and returning geographic coordinates, frequently latitude/longitude pair, to identify a location on the Earth's surface. Reverse geocoding, on the other hand, converts geographic coordinates to a description of a location, usually the name of a place or an addressable location. Geocoding relies on a computer representation of address points, the street / road network, together with postal and administrative boundaries.

QDGC - Quarter Degree Grid Cells are a way of dividing the longitude latitude degree square cells into smaller squares, forming in effect a system of geocodes. Historically QDGC has been used in a lot of African atlases. Several African biodiversity projects uses QDGC, among which The atlas of Southern African Birds is the most prominent one. In 2009 a paper by Larsen et al. describes the QDGC standard in detail.

<span class="mw-page-title-main">Marsden square</span> System dividing part of a world map into a grid of 10°×10° cells

Marsden square mapping or Marsden squares is a system that divides a world map with latitude-longitude gridlines between 80°N and 70°S latitudes into grid cells of 10° latitude by 10° longitude, each with a geocode, a unique numeric identifier. The method was devised by William Marsden, when first secretary of the British Admiralty, for collecting and combining geographically based information about the oceans.

In computer graphics, marching squares is an algorithm that generates contours for a two-dimensional scalar field. A similar method can be used to contour 2D triangle meshes.

The World Geographic Reference System (GEOREF) is a geocode, a grid-based method of specifying locations on the surface of the Earth. GEOREF is essentially based on the geographic system of latitude and longitude, but using a simpler and more flexible notation. GEOREF was used primarily in aeronautical charts for air navigation, particularly in military or inter-service applications, but it is rarely seen today. However, GEOREF can be used with any map or chart that has latitude and longitude printed on it.

<span class="mw-page-title-main">Regular grid</span> Tessellation of n-dimensional Euclidean space by congruent parallelotopes

A regular grid is a tessellation of n-dimensional Euclidean space by congruent parallelotopes. Its opposite is irregular grid.

World Meteorological Organization (WMO) squares is a system of geocodes that divides a world map with latitude-longitude gridlines into grid cells of 10° latitude by 10° longitude, each with a unique, 4-digit numeric identifier. On the plate carrée projection, the grid cells appear square; however, if the Mercator projection is used, the grid cells appear 'stretched' vertically nearer the tops and bottoms of the map. On the actual surface of the Globe, the cells are approximately "square" only adjacent to the Equator, and become progressively narrower and tapered as they approach the poles, and cells adjoining the poles are unique in possessing three faces rather than four.

C-squares is a system of spatially unique, location-based identifiers (geocodes) for areas on the surface of the earth, represented as cells from a latitude- and longitude-based Discrete Global Grid at a hierarchical set of resolution steps, obtained by progressively subdividing 10×10 degree World Meteorological Organization squares; the term "c-square" is also available for use to designate any component cell of the grid. Individual cell identifiers incorporate literal values of latitude and longitude in an interleaved notation, together with additional digits that support intermediate grid resolutions of 5, 0.5, 0.05 degrees, etc.

<span class="mw-page-title-main">Geodesic grid</span> Spatial grid based on a geodesic polyhedron

A geodesic grid is a spatial grid based on a geodesic polyhedron or Goldberg polyhedron.

<span class="mw-page-title-main">Geohash</span> Public domain geocoding invented in 2008

Geohash is a public domain geocode system invented in 2008 by Gustavo Niemeyer which encodes a geographic location into a short string of letters and digits. Similar ideas were introduced by G.M. Morton in 1966. It is a hierarchical spatial data structure which subdivides space into buckets of grid shape, which is one of the many applications of what is known as a Z-order curve, and generally space-filling curves.

<span class="mw-page-title-main">HEALPix</span> Pseudocylindrical equal-area map projection

HEALPix, an acronym for Hierarchical Equal Area isoLatitude Pixelisation of a 2-sphere, is an algorithm for pixelisation of the 2-sphere and the associated class of map projections. The pixelisation algorithm was devised in 1997 by Krzysztof M. Górski at the Theoretical Astrophysics Center in Copenhagen, Denmark, and first published as a preprint in 1998.

A mesh is a representation of a larger geometric domain by smaller discrete cells. Meshes are commonly used to compute solutions of partial differential equations and render computer graphics, and to analyze geographical and cartographic data. A mesh partitions space into elements over which the equations can be solved, which then approximates the solution over the larger domain. Element boundaries may be constrained to lie on internal or external boundaries within a model. Higher-quality (better-shaped) elements have better numerical properties, where what constitutes a "better" element depends on the general governing equations and the particular solution to the model instance.

<span class="mw-page-title-main">Discrete global grid</span> Partition of Earths surface into subdivided cells

A discrete global grid (DGG) is a mosaic that covers the entire Earth's surface. Mathematically it is a space partitioning: it consists of a set of non-empty regions that form a partition of the Earth's surface. In a usual grid-modeling strategy, to simplify position calculations, each region is represented by a point, abstracting the grid as a set of region-points. Each region or region-point in the grid is called a cell.

ICES Statistical Rectangles is a gridded, latitude-longitude based area notation system covering the north-east Atlantic region developed by the International Council for the Exploration of the Sea (ICES) in the 1970s, for simplified analysis and visualization of spatial data of relevance to that organization's interests. The individual rectangles that make up the system each measure 1 degree of longitude by 0.5 degrees of latitude and are intended to be roughly square in real world use in the ICES region of interest, approximately 30 nautical miles by 30 nautical miles at 60°N, although the actual width varies with latitude, gradually becoming wider than they are high south of 60°N, and narrower further north. The grid covers the region from 36°N to 85°30'N and from 44°W to 69°E using a set of alphanumeric identifiers, with row of latitude cited first, then column of longitude. The last used column identifier is M8; column identifiers A4-A9, and prefix "I" i.e. columns "I"0-"I"9 are not used. The resulting grid is 113 columns by 99 rows, comprising 11,187 labelled 1×0.5 degree cells. An example cell designation is 37F3, which designates the 1×0.5 degree rectangle of which the south-west corner is 54°00'N, 03°00'E. The grid covers both land and sea areas across its designated region, but as per the interests of its originating body, is typically employed for use with marine data such as analysis of marine resources, fishing activities, seabed habitat, etc., refer example references below. The full extent of the grid is visible in published figures such as Figs. 5-8 in Williamson et al., 2017.

References

  1. Geoffrey Dutton. "Spatial Effects: Research Papers and Data" Archived 2007-02-19 at the Wayback Machine .
  2. Criteria and Measures for the Comparison of Global Geocoding Systems, Keith C. Clarke, University of California Archived 2010-06-23 at the Wayback Machine
  3. Rigaux, P., Scholl, M., and Voisard, A. 2002. Spatial Databases - with application to GIS. Morgan Kaufmann, San Francisco, 410pp.