Literature DB >> 29541867

The potential of volunteered geographic information to investigate peri-urbanization in the conservation zone of Mexico City.

Katharina Heider1, Juan Miguel Rodriguez Lopez2, Jürgen Scheffran2.   

Abstract

Due to the availability of Web 2.0 technologies, volunteered geographic information (VGI) is on the rise. This new type of data is available on many topics and on different scales. Thus, it has become interesting for research. This article deals with the collective potential of VGI and remote sensing to detect peri-urbanization in the conservation zone of Mexico City. On the one hand, remote sensing identifies horizontal urban expansion, and on the other hand, VGI of ecological complaints provides data about informal settlements. This enables the combination of top-down approaches (remote sensing) and bottom-up approaches (ecological complaints). Within the analysis, we identify areas of high urbanization as well as complaint densities and bring them together in a multi-scale analysis using Geographic Information Systems (GIS). Furthermore, we investigate the influence of settlement patterns and main roads on the peri-urbanization process in Mexico City using OpenStreetMap. Peri-urbanization is detected especially in the transition zone between the urban and rural (conservation) area and near main roads as well as settlements.

Keywords:  GIS; Hot spots; Informal settlements; Multi-scale analysis; OpenStreetMap (OSM); Remote sensing

Mesh:

Year:  2018        PMID: 29541867     DOI: 10.1007/s10661-018-6597-3

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  8 in total

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3.  Internet encyclopaedias go head to head.

Authors:  Jim Giles
Journal:  Nature       Date:  2005-12-15       Impact factor: 49.962

4.  Free access to Landsat imagery.

Authors:  Curtis E Woodcock; Richard Allen; Martha Anderson; Alan Belward; Robert Bindschadler; Warren Cohen; Feng Gao; Samuel N Goward; Dennis Helder; Eileen Helmer; Rama Nemani; Lazaros Oreopoulos; Joh Schott; Prasad S Thenkabail; Eric F Vermote; James Vogelmann; Michael A Wulder; Randolph Wynne
Journal:  Science       Date:  2008-05-23       Impact factor: 47.728

5.  Combining satellite imagery and machine learning to predict poverty.

Authors:  Neal Jean; Marshall Burke; Michael Xie; W Matthew Davis; David B Lobell; Stefano Ermon
Journal:  Science       Date:  2016-08-19       Impact factor: 47.728

6.  The tragedy of the commons. The population problem has no technical solution; it requires a fundamental extension in morality.

Authors:  G Hardin
Journal:  Science       Date:  1968-12-13       Impact factor: 47.728

7.  Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples.

Authors:  Maged N Kamel Boulos; Bernd Resch; David N Crowley; John G Breslin; Gunho Sohn; Russ Burtner; William A Pike; Eduardo Jezierski; Kuo-Yu Slayer Chuang
Journal:  Int J Health Geogr       Date:  2011-12-21       Impact factor: 3.918

8.  Human and remote sensing data to investigate the frontiers of urbanization in the south of Mexico City.

Authors:  Juan Miguel Rodriguez Lopez; Katharina Heider; Jürgen Scheffran
Journal:  Data Brief       Date:  2016-12-29
  8 in total

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