Linking socioeconomic classes and land cover data in Lima, Peru: Assessment through the application of remote sensing and GIS

International Journal of Applied Earth Observation and Geoinformation

Volumn 11, Issue 1, 2009, Pages 27-37

  Avelar, Silvania ^a   Zah, Rainer ^a   Tavares Corrêa, Carlos ^b  

^a SWISS FEDERAL LABORATORIES FOR MATERIALS SCIENCE AND TECHNOLOGY   (Switzerland)

^b PONTIFICIA UNIVERSIDAD CATÓLICA DEL PERÚ   (Peru)

Author keywords

Accuracy assessment; GIS analysis; Grid based approach; Socioeconomic classes; Supervised classification

Indexed keywords

ACCURACY ASSESSMENT; DATA PROCESSING; GIS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE RESOLUTION; LAND COVER; REMOTE SENSING; SOCIOECONOMIC IMPACT; SPATIAL DISTRIBUTION; URBAN AREA; URBAN DEVELOPMENT;

LATIN AMERICA; LIMA [PERU]; PERU; SOUTH AMERICA;

EID: 57049152470     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2008.05.001     Document Type: Article

References (23)

1. APOYO, 2005a. Perfiles zonales de Lima Metropolitana. APOYO Opinión y Mercado, Lima, 114 pp. (in Spanish).
2. APOYO, 2005b. MAPINSE de Lima Metropolitana 2005 - IV, Distritos de Santiago de Surco y San Juan de Miraflores. APOYO Opinión y Mercado, Lima, 9 pp. (in Spanish).
3. Barros, J., 2004. Urban Growth in Latin American Cities: Exploring Urban Dynamics through Agent-based Simulation. PhD Thesis. University College London, 289 pp.
4. Campbell J.B. Introduction to Remote Sensing. third ed. (2002), Taylor and Francis, London
5. Foody G.M. Status of land cover classification accuracy assessment. Remote Sensing of Environment 80 (2002) 185-201
6. In: Fox J., Rindfuss R.R., Walsh S.J., and Mishra V. (Eds). People and the Environment: Approaches for Linking Household and Community Surveys to Remote Sensing and GIS (2003), Kluver Academic Publishers, Massaschusetts, US
7. Gibson P.J., and Power C.H. Introductory Remote Sensing: Principles and Concepts + Digital Image Processing and Applications (2000), Taylor and Francis Group, Routeledge
8. Herold M., Hemphill J., and Clarke K.C. Remote sensing and urban growth theory. In: Wang Q., and Quattochi D.A. (Eds). Urban Remote Sensing (2007), CRC Press, Taylor and Francis Group, Boca Raton, US
9. Huang C., Davis L.S., and Townshend J.R.G. An assessment of support vector machines for land cover classification. International Journal of Remote Sensing 23 4 (2002) 725-749
10. Jensen J.R., and Cowen D.C. Remote sensing of urban/suburban infrastructure and socio-economic attributes. Photogrammetric Engineering & Remote Sensing 65 5 (1999) 611-622
11. Landis, F., Avelar, S., Orbanz, P., Zah, R., Buhmann, J., 2005. Preparatory study for the Seed Project. Internal Report, Swiss Federal Institute for Materials Testing and Research (Empa), Switzerland.
12. Lavigne D.A., Hong G., and Zhang Y. Performance assessment of automated feature extraction tools on high resolution imagery. MAPPS/ASPRS 2006 Fall Conference. Nov. 6-10, San Antonio, Texas (2006)
13. Lyndolph P.E. On the causes of aridity along selected group of coasts. In: Aminan D.H.K., and Wilson A.W. (Eds). Coastal Deserts-Their Natural and Human Environments (1973), The University of Arizona Press 62-72
14. Mesev V. Remotely Sensed Cities (2003), Taylor & Francis, London
15. Shutz, E., 1996. Ciudades en América Latina: desarrollo barrial y vivienda. Santiago de Chile, Ediciones Sur. (in Spanish).
16. Sembler, C.R., 2006. Estratificación social y clases sociales. Una revisión analítica de los sectores medios. ONU, CEPAL, División de Desarrollo Social, Serie Políticas Sociales 125, 75 pp. (in Spanish). http://www.eclac.cl/publicaciones/xml/6/27586/sps125_lcl2637.pdf.
17. Stefanov W.L., Ramsey M.S., and Christensen P.R. Monitoring urban land cover changes: an expert system approach to land cover classification of semiarid to arid urban centers. Remote Sensing of Environment 77 (2001) 173-185
18. Sutton, P.C., Taylor, M.J., Anderson, S., Elvidge, C.D., 2007. Sociodemographic characterization of urban areas using nighttime imagery, Google Earth, Landsat, and "social" ground truthing. Urban Remote Sensing, CRC Press, pp. 291-310.
19. Tapiador, F.J., Casanova, J.L., 2003. Land-use mapping methodology using remote sensing for the regional planning directives in Segovia, Spain. Landscape and urban planning 62 (2), pp. 103-115, Elsevier Science, Amsterdam.
20. Taubenbock, H., Esch, T., Roth, A., 2006. An Urban Classifi{ligature}cation Approach on an Object-Oriented Analysis of High Resolution Satellite Imagery for a Spatial Structuring within Urban Areas. Workshop of SIG Urban Remote Sensing. Humboldt-University, Berlin, 2-3 March, 2006.
21. UN, 2006. World Urbanization Prospects: The 2005 Revision. United Nations, New York, 185 pp. http://www.un.org/esa/population/.
22. Wang Q., and Quattrochi D.A. Urban Remote Sensing (2007), CRC Press, Taylor and Francis Group, Boca Raton, US
23. Zhang G., and Foody G.M. Fullly-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and artificial neural network approaches. International Journal of Remote Sensing 22 (2001) 615-628