
Geo
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Bilan de l’atelier cartographie libre sur Open street map | Montpellier Territoire Numérique
Cartographie, cartes vectorielles, fonds de cartes - InterCarto
Un grand choix de cartes vectorielles à télécharger Des cartes vectorielles complètes, esthétiques et modifiables à volonté Vos cartes sur mesureProcessing geo information in Wikipedia articles - Creative Coding - Tutorial
This page presents a variety of calculations for latitude/longitude points, with the formulæ and code fragments for implementing them. All these formulæ are for calculations on the basis of a spherical earth (ignoring ellipsoidal effects) – which is accurate enough * for most purposes… [In fact, the earth is very slightly ellipsoidal; using a spherical model gives errors typically up to 0.3% – see notes for further details]. Distance This uses the ‘ haversine ’ formula to calculate the great-circle distance between two points – that is, the shortest distance over the earth’s surface – giving an ‘as-the-crow-flies’ distance between the points (ignoring any hills, of course!). The haversine formula 1 ‘remains particularly well-conditioned for numerical computation even at small distances’ – unlike calculations based on the spherical law of cosines . The ‘versed sine’ is 1-cosθ, and the ‘half-versed-sine’ (1-cosθ)/2 = sin²(θ/2) as used above.
Calculate distance and bearing between two Latitude/Longitude points using Haversine formula in JavaScript
Acetate | GeoIQ Developer
GeoPlanet Explorer
Welcome to the GeoPlanet Explorer. Here you can explore the geographical information provided by Yahoo in the GeoPlanet API and data set . Simply enter a location in the form above and submit it to get detailed information about the place you are looking for - including its ancestors, siblings, children and other relationships. Here's the information about the location you requested. Click any of the links to reload this page to learn more about this location.This open-source application maps the information that your iPhone is recording about your movements. It doesn't record anything itself, it only displays files that are already hidden on your computer. Download the application Read the FAQ Authors Alasdair Allan (alasdair@babilim.co.uk) @aallan on Twitter Pete Warden (pete@petewarden.com) @petewarden on Twitter
petewarden/iPhoneTracker @ GitHub
There’s an increasing amount of useful packages that allow for spatial analysis in python. Having said that, actually drawing a map remains relatively tricky, here I am sharing a few of the methods that I have come up with recently to help in this area. Firstly, let’s consider the basic set of prerequisites that you should have installed to do some useful things in Python. Numpy and Scipy – easy_install Numpy / easy_install Scipy Numeric Python and Scientific Python vastly extend the scientific programming capabilities of Python. Numpy adds the array() object which, for numeric matters, is far superior to the standard Python List, as well as numerous mathematical methods.
Volunteered Geographic Information » Drawing maps with Python
Over the past few months we have been harvesting geospatial data from Twitter with the aim of creating a series of new city maps based on Twitter data. Via a radius of 30km around New York, London, Paris, Munich we have collated the number of Tweets and created our New City Landscape Maps. New York New City Landscape Image by urbanTick using the GMap Image Cutter / New York New City Landscape -Use the Google Maps style zoom function in the top right corner to zoom into the map and explore it in detail. Explore areas you know close up and find new locations you have never heard of. Click HERE for a full screen view.
New City Landscapes - Interactive Tweetography Maps
Sciences : Cartographie
Recent talk: Exploratory Data Analysis: Tasks, Tools, Principles , invited talk at HPI in Potsdam, 27/09/2005 (PDF, 1297 KBytes) Teaching materials: Lecture 1: Interactive maps lection1.pdf , 3698 KBytes Lecture 2: Dynamically linked views lection2.pdf , 901 KBytes Lecture 3: Analysis of spatial time series lection3.pdf , 1340 KBytes Lecture 4: Computationally enhanced visualisation lection4.pdf , 1436 KBytes Lecture 5: Multi-criteria decision making lection5.pdf , 269 KBytes Examples (some of the dasets used in the book) For all requests concerning the software please refer to www.commongis.com and Fraunhofer Institute IAIS .

