Journal of Environment Protection and Sustainable Development
Articles Information
Journal of Environment Protection and Sustainable Development, Vol.1, No.3, Jul. 2015, Pub. Date: May 26, 2015
Detection of Urban Change and Urban Sprawl of Madurai City, Tamilnadu Using GIS and RS
Pages: 107-120 Views: 6652 Downloads: 2872
Authors
[01] Tamilenthi S., Dept. of Geography, Kalinga University, Raipur, India.
[02] Arul P., Dept. of Geography, Govt. Arts College (Auto), Salem, India.
[03] Chandramohan K., UGC-Academic Staff College, Madurai Kamaraj University, Madurai, Tamil Nadu, India.
Abstract
There has been rapid change in the land use and land-cover types in Madurai city, Tamilnadu in the past 26 years. The major change is the conversion of agriculture and forest lands into urban areas mostly in an un-planned manner making urban sprawl characterizing the urban change dynamics. The principal aim of this research was to apply remotely sensed data, geospatial tools to detect, quantify, analyze, and detect the urban land use changes of Madurai city. Madurai City, located in South Central Tamil Nadu, is the second largest city after Chennai and is the headquarters of Madurai District. In 2011, the jurisdiction of the Madurai Corporation was expanded from 72 wards to 100 wards covering area 151 Sq.Kms. It is extended geographically from 9o50‟ North latitude to 10o North latitude and 78o 02‟ East longitude to 78º12‟ East longitude, and approximately 100 m above MSL. The corporation limit was extended from 52.18 km2 to 147.9 km2 in 2011. As per 2011 census the population of the city is 15.35 lakhs. The city spreads over 147.9 km2 which divided into 100 wards for administrative purpose. The ultimate objective of the research is to detect the land use/land-cover change of Madurai city from 1980 to 2006. Satellite images of Madurai city at different periods, 1980, 1990, and 2006 were analyzed. The software programs that have been used in this study to process, quantify, analyze and change detection are ArcGIS 9.2, ArcMap and ERADAS 2013.Change detection techniques namely post classification comparison (indirect method) and image-to-image comparison change detection (direct method) were employed. Post-classification comparison change detection was conducted to reveal the areas that have changed over the period of 26 years.
Keywords
Urban Change, Urban Sprawl, GIS, Madurai Corporation
References
[01] Adeniyi P.O and Omojola A. (1999) Landuse Land cover change evaluation in Sokoto –Rima Basin of North Western Nigeria based on Archival of the Environment (AARSE)on Geoinformation Technology Applications for Resource and Environmental Management in Africa. Pp 143-172.
[02] Barr, S. L. (1992). Object-based Re-classification of High Resolution Digital Imagery for Urban Land-Use Monitoring. International Archives of Photogrammetry and Remote Sensing (ISPRS, Washington, D.C.1992). Vol. XXIX, Part B7, Commission VII, 969-76.
[03] Barnsley, M.J., Barr, S. L., and Sadler, G. J. (1991) Spatial Re-classification of Remote Sensed Images for Urban Land Use Monitoring. Proc. Spatial Data 2000, 17-20 September1991, Oxford University, (Nottingham: Remote Sensing Society), 106-117.
[04] Campbell, James B (1983) "Mapping the Land Aerial Imagery for Land Use Information" Resource Publications in Geography, Association of American Geographers, Washington D.C.
[05] Olorunfemi J.F (1983). Monitoring Urban Land – Use in Developed Countries – An aerial photographic approach, Environmental Int.9, 27 – 32.
[06] Santos,A.P.;Foresti,C.;Novo,E.M.L.M.;Niero,M.;Lombardo,M.A. (1981).Metodologia deinterpretação de dados de sensoriamento remoto e aplicações no uso da terra.São José dos Campos,INPE.61 (INPE-2261-MD/016).
[07] Tamilenthi.S et al (2011) Dynamics of urban sprawl, changing direction and mapping: A case study of Salem city, Tamilnadu ,India. Archives of Applied Science Research, 2011, 3 (1):277-286.
[08] Tamilenthi.S and Baskaran.R(2011) Detecting Urban Change of Salem City of Tamil Nadu, India from 1990 to 2010 Using Geospatial Technology International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 2 No.2. 183-195.
[09] Tonjes, R., Growe S., Bucker J.and Liedtke C.–E. (1999).Knowledge-Based Interpretation ofRemote Sensing Images Using Semantic Nets. Photogrammetric Engineering & Remote Sensing, 65, 811-821.
[10] 10)Vieira,I.M.;Kurkdjian, M.L.N.O. (1993).Integração de dados de expansão urbana e dados geotécnicos como subsídio ao estabelecimento de critérios de oupação em áreas urbanas. In: simpósio brasileiro de sensoriamento remoto, 7.Curitiba, PR.Anais. Curitiba.v. 1.163-171.
[11] Valerio Filho,M. (1998).Técnicas de Sensoriamento remoto e geoprocessamento aplicadas ao planejamento regional. VI Simpósio Nacional de Controle de Erosão. Presidente Prudente, São Paulo.CD-ROM.
[12] White house, S. (1990). A spatial land use classification of an urban environment using high resolution multispectral satellite data.Proc.16th Ann. Conf. Remote Sensing Society Remote Sensing and Global Change, University Collage Swansea,19-21 September 1990, (Nottingham: Remote Sensing Society), 433-437.
[13] Welch, R., (1982). Spatial resolution requirements for urbans studies. International Journal of Remote sensing, 3(2): 139-146.
[14] Young, Anthony, Feb. (1994), Towards an international classification of land use, Consultancy report to UNEP/FAO, page 6. Visited on 11/11/2007 from URL:http://www.fao. org/ag/agl/agll/landuse/docs/young1994.doc.
[15] Yuan, D., and Elvidge, C. (1998). NALC land cover change detection pilot study: Washington D.C. area experiments. Remote Sensing of Environment, 66, 166-178.
600 ATLANTIC AVE, BOSTON,
MA 02210, USA
+001-6179630233
AIS is an academia-oriented and non-commercial institute aiming at providing users with a way to quickly and easily get the academic and scientific information.
Copyright © 2014 - American Institute of Science except certain content provided by third parties.