What is special about Geospatial?

The book “Geospatial Analysis” can freelay be accessed online. This book should be a comprehensive independent guide to principles, techniques and software tools as stated at the online. The authors, de Smith, Goodchild and Longley, are quite prominet.

Topics covered include:

Principal concepts of geospatial analysis, their origins and methodological context
Core components of geospatial analysis, including distance and directional analysis, geometrical processing, map algebra, and grid models
Exploratory spatial data analysis (ESDA) and spatial statistics, including spatial autocorrelation and spatial regression
Surface analysis, including surface form analysis, gridding and interpolation methods
Network and locational analysis, including shortest path calculation, travelling salesman problems, facility location and arc routing
Geocomputational methods, including agent-based modelling, artifical neural networks and evolutionary computing.

View the whole Book online!

Written and submitted from Home, using my 802.11g WiFi network.

The OpenStreetMap project is growing. The project can be compared with wikipadia. OpenStreetMap is a free editable map of the whole world. It is made by people like you. OpenStreetMap allows you to view, edit and use geographical data in a collaborative way from anywhere on Earth.

“OpenStreetMap is a project aimed squarely at creating and providing free geographic data such as street maps to anyone who wants them. The project was started because most maps you think of as free actually have legal or technical restrictions on their use, holding back people from using them in creative, productive or unexpected ways.“

Contributors to OpenStreetMap take handheld GPS devices with them on journeys, or go out specially to record GPS tracks. They record street names, village names and other features using notebooks, digital cameras, and voice-recorders.

Back at the computer, contributors upload those GPS logs showing where they travelled, and trace-out the roads on OpenStreetMap’s collaborative database. Using their notes, contributors add the street names, information such as the type of road or path, and the connections between roads.

That data is then processed to produce detailed street-level maps, which can be published freely on sites such as Wikipedia, used to create handheld or in-car navigation devices, or printed and copied without restriction.

This Animation showing the development of OSM in the area Munich, the capital of Bavaria, Germany. Time shown: August 2006 until September 2007. This animation is also shown at the German page on Munich.

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GeoNames is a geographical data base freely available and accessible through various Web services, under a Creative Commons attribution license.

The GeoNames database contains over 8,000,000 geographical names corresponding to over 6,500,000 unique features. All features are categorized into one out of nine feature classes and further subcategorized into one out of 645 feature codes. Beyond names of places in various languages, data stored include latitude, longitude, elevation, population, administrative subdivision and postal codes. All coordinates use the WGS84 system (World Geodetic System 1984). Those data are accessible free of charge through a number of Web services and a daily database export. The Web services include direct and reverse geocoding, finding places through postal codes, finding places next to a given place, and finding Wikipedia articles about neighbouring places.

Each GeoNames feature is represented as a Web resource identified by a stable URI. This URI provides access, through content negotiation, either to the HTML wiki page, or to a RDF description of the feature, using elements of the GeoNames ontology. This ontology describes the GeoNames features properties using the Web Ontology Language, the feature classes and codes being described in the SKOS language. Through Wikipedia articles URL linked in the RDF descriptions, GeoNames data are linked to DBpedia data and other RDF Linked Data.

Desnsity Feature map. Bright areas indicates a high feature density for GeoNames. Dense regions are Bosnia Herzegowina (1.008 features per km²) , Germany (0.447), North Korea (0.318), Pakistan (0.154) and the east coast of the US.

[www.geonames.org]

Written and submitted from Home, using my 802.11g WiFi network.