By Fernando Bacao, Maribel Yasmina Santos, Marco Painho

ISBN-10: 3319167863

ISBN-13: 9783319167862

This is a e-book is a set of articles that may be submitted as complete papers to the AGILE annual foreign convention. those papers battle through a rigorous overview strategy and file unique and unpublished primary medical learn. these released hide major examine within the area of geographic details technology platforms. This 12 months the focal point is on geographic info technological know-how as an enabler of smarter towns and groups, therefore we predict contributions that support visualize the position and contribution of GI technological know-how of their development.

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Extra resources for AGILE 2015: Geographic Information Science as an Enabler of Smarter Cities and Communities

Example text

In the previous formula, the variable j stands for either 2 or 3, which corresponds to Inner City or Mariahilferstraße, respectively. We briefly elaborate on the individual feature differences according to Fig. 5: 1. Regarding the density of banks and ATMs, the area found in the Inner City as well as the one around Mariahilferstraße are both relatively close to the area that contains Oxford Street. 2. In terms of the density of tourism attractions Mariahilferstraße is a bit closer to Oxford Street than the Inner City.

0005 degrees, and preprocessed the OSM data by assigning the nodes and their tags to the cells. The rules for our description are based on the following assumptions. , restaurants, fast-foods, cafes). These simple constraints were sufficient to find the commonly-known shopping areas in Vienna, plus many smaller clusters that can be interpreted as local shopping and leisure areas. The segmentation result for Vienna is shown in Fig. 2. Using the same description, we employed the algorithm on the dataset of London and obtained a comparable result (see Fig.

Y. Santos, H. Pundt, W. Cartwright, G. Gartner, L. Meng, & M. P. ), Geospatial Thinking (pp. 163–182). Lecture Notes in Geoinformation and Cartography. Berlin: Springer. , & Gao, S. (2012). Urban land uses and traffic ‘source-sink areas’: Evidence from GPS-enabled taxi data in Shanghai. Landscape Urban Planning, 106(1), 73–87. Martins, B. (2011). Delimiting imprecise regions with georeferenced photos and land coverage data. In K. Tanaka, P. Fröhlich, & K. S. ), Web and wireless geographical information systems (pp.

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