Remote Sensing of Sustainable Rural-Urban Land Use in Mexico City: A Qualitative Analysis for Reliability and Validity

Abstract | Mexico City is one of the largest cities on the globe and a site where important transformations of nature reserves into urban areas have been taking place . This paper compared the southern part of Mexico City based on free images available (Landsat – 30m) and high-resolution imagery (RapidEye – 5m) from an explorative qualitative perspective in the logic of reliability and validity . We argue that the resolution of the free imagery available for the assessment of urban development on the structural level of land use is not sufficient to identify the development of specific parts of the city . Despite the fact that the general pattern of changes in land use is observable, changes within the urban structure are difficult to see with a resolution of 30 meters per pixel in the Landsat images . For validity, this analysis is merely graphic, and it shows a promising matching of urban development with environmental and land complaints, nevertheless, a numerical analysis is needed in the future.

[1]  G. Delgado-Ramos.  Water and the political ecology of urban metabolism: the case of Mexico City , 2015 .

[2]  Aditya Mohanty.  Urban Political Geographies: A Global Perspective , 2012 .

[3]  Alfred Stein,et al.  An ontology of slums for image-based classification , 2012, Comput. Environ. Urban Syst..

[4]  Kultar Singh,et al.  Quantitative Social Research Methods , 2007 .

[5]  E. Swyngedouw,et al.  In the Nature of Cities: Urban Political Ecology and the Politics of Urban Metabolism , 2006 .

[6]  A. Rango,et al.  Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico , 2004 .

[7]  Yadira Méndez-Lemus.  Urban growth and transformation of the livelihoods of poor campesino households: the difficulties of making a living in the periphery of Mexico City , 2012 .

[8]  Stéphane Dupuy,et al.  An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data , 2012, Remote. Sens..

[9]  Oleksandr Kit,et al.  Texture-based identification of urban slums in Hyderabad, India using remote sensing data , 2012 .

[10]  L. Rodríguez-Sánchez,et al.  Farming dynamics and social capital: A case study in the urban fringe of Mexico City , 2008 .

[11]  Jason Corburn,et al.  Urban slum structure: integrating socioeconomic and land cover data to model slum evolution in Salvador, Brazil , 2013, International Journal of Health Geographics.

[12]  F. Achard,et al.  A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals associated with deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation , 2012 .

[13]  H. Taubenböck,et al.  The physical face of slums: a structural comparison of slums in Mumbai, India, based on remotely sensed data , 2014 .

[14]  Victor Jupp,et al.  The SAGE Dictionary of Social Research Methods , 2006 .

[15]  J. Odindi,et al.  Remote sensing land-cover change in Port Elizabeth during South Africa's democratic transition , 2012 .

[16]  Peter M. Ward,et al.  Self-help housing and informal homesteading in peri-urban America: Settlement identification using digital imagery and GIS ☆ , 2007 .

[17]  Oleksandr Kit,et al.  Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery , 2013 .

[18]  Undermining the Rule of Law: Democratization and the Dark Side of Police Reform in Mexico , 2006, Latin American Politics and Society.

[19]  Thomas M. Stoker,et al.  The Economics of Slums in the Developing World , 2013 .

[20]  Thomas Esch,et al.  Can the Future EnMAP Mission Contribute to Urban Applications? A Literature Survey , 2011, Remote. Sens..

[21]  Stephen D. Lapan,et al.  Foundations for Research : Methods of Inquiry in Education and the Social Sciences , 2004 .