The longitude and latitude components (decimal degrees) are as defined by the World Geodetic System of 1984 (WGS84). KML/KMZ became an international standard of the Open Geospatial Consortium in 2008. KML was developed by Keyhole Inc which was later acquired by Google.KMZ (KML-Zipped) replaced KML as being the default Google Earth geospatial format because it is a compressed version of the file. ![]() This GIS format is XML-based and is primarily used for Google Earth. This is because GML results in more data for the same amount of information. ![]() There is generally more overhead when comparing GML with GeoJSON. Each feature has a list of properties, geometry (points, lines, curves, surfaces, and polygons), and a spatial reference system. Similar to GeoJSON, GML can be updated in any text editor. GML stores geographic entities (features) in the form of text. And eXtensible Markup Language (XML) is both human-readable and machine-readable. GML allows for the use of geographic coordinates extension of XML. Fortunately, JavaScript can convert JSON to binary. But JavaScript only understands binary objects. Webmaps browsers understand JavaScript so by default GeoJSON is a common web format. GeoJSON has a straightforward syntax that you can modify in any text editor. GeoJSON store objects within curly braces and in general have less markup overhead (compared to GML). This includes vector points, lines and polygons as well as tabular information. GeoJSON stores coordinate as text in JavaScript Object Notation (JSON) form. The GeoJSON format is mostly for web-based mapping. Geographic JavaScript Object Notation (GeoJSON) ![]() PRJ is the projection system metadata.XML is the associated metadata.SBN is the spatial index for optimizing queries.SBX optimizes loading times.You can optionally include these files but are not completely necessary. It’s so ubiquitous that it’s become the industry standard.īut you’ll need a complete set of three files that are mandatory to make up a shapefile. All commercial and open source accept shapefile as a GIS format. # Load required packages library(dplyr) library(tidyr) library(sp) library(raster) library(rgeos) library(rgbif) library(viridis) library(gridExtra) library(rasterVis) library(rgdal) #' load geographical data from GDAM for Great Britain study_area % disaggregate %>% geometry study_area % %>% study_area plot(study_area, col = "grey50", bg = "light blue", axes = TRUE, cex = 20) text(81.5, 9.5, "Study Area:\nGB") hex_points <- spsample(study_area, type = "hexagonal", cellsize = 0.5) hex_grid <- HexPoints2SpatialPolygons(hex_points, dx = 0.5) plot(study_area, col = "grey50", bg = "light blue", axes = TRUE) plot(hex_points, col = "black", pch = 20, cex = 0.The shapefile is BY FAR the most common geospatial file type you’ll encounter. Overlaying hexagonal grid on Great Britain mapįollowing is a sample code to create a hexagonal grid for a geographical area. Analysis on areas, such as neighborhoods within a city, is much more practical. Such analysis at the finest granularity, the exact location where an event happens, is very difficult and expensive. For example, to identify areas with high demand than supply and adjust pricing in response or identify users in close proximity who have requested UberPool service. ![]() Uber uses spatial analysis to better understand and optimize the marketplace for users. Users request rides, locate nearest drivers, and deliver food to people staying at home, among other.Īlso Uber’s future plans for air travel such as Uber Elevate, Uber Air and Uber Copter, that would take riders over long distances will need accurate pricing over long distances in real time. Uber’s business relies heavily on accurately mapping geographic areas to offer their services. Regular hexagons are the closest shape to a circle and can be effectively used for the regular tessellation of a geographic area.įor businesses such as ride sharing apps that rely on accurate mapping of geographical areas for their services, it is critical to choose a grid map that minimizes distortions and quantization error introduced when users move through a city.
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