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Assessment of Urban Development using Supervised Classification of Remotely Sensed Imageries and GIS, A Case Study of Independence Layout (Part of), Enugu, Nigeria (6388)

Victor, Chukwuemeka Nnam, John, Okwor Nnam and Uchechukwu Godwin Nnam (Nigeria)
Surv. Nnam Victor Chukwuemeka
Principal Consultant
GeoSynergy Services Limited.
Suit C2 Goshen Plaza,38 Garden Avenue
Enugu, Nigeria.
2b, Igwesi Close.
Trans Ekulu, Enugu, Nigeria.
Enugu
234
Nigeria
 
Corresponding author Surv. Nnam Victor Chukwuemeka (email: victor.nnam[at]gmail.com, tel.: +2348032760910)
 

[ abstract ] [ paper ] [ handouts ]

Published on the web 2013-03-08
Received 2012-10-21 / Accepted 2013-02-02
This paper is one of selection of papers published for the FIG Working Week 2013 in Abuja, Nigeria and has undergone the FIG Peer Review Process.

FIG Working Week 2013
ISBN 978-87-92853-05-9 ISSN 2307-4086
http://www.fig.net/resources/proceedings/fig_proceedings/fig2013/index.htm

Abstract

Assessment of Urban Development using Supervised Classification of remotely sensed Imageries and GIS, A Case study of Independence Layout (Part of), Enugu, Nigeria. Nnam, Victor Chukwuemeka, [email protected]; Nnam, Godwin Uchechukwu., [email protected] and Nnam John Okwor, [email protected] GeoSynergy Services Limited. Suit C2 Goshen Plaza, 38 Garden Avenue Enugu, Nigeria ABSTRACT Adequately planned urban development is a key to achieving sustainable environment. Urban planning therefore becomes important as we develop our urban areas. For us to maintain the land use allocation pattern/scheme of our urban areas, we need to assess, monitor and control the trend and the pattern of development as they occur as uncontrolled development (slum developments) may mar the beauty and sustainability of the urban Area. This paper focuses on assessing and analyzing urban development using Object Based image classification of remotely sensed satellite imageries of part of Independence Layout, Enugu urban, Enugu State, Nigeria. Using the Object based classification, a supervised classification of urban structures and other recent physical developments in the study area were achieved. Comparative Analyses were carried out between the classified image of Independence layout Enugu and the originally Town Planning design in order to determine the difference between land use pattern of independence layout Enugu and what was designed . A Quickbird image of 2012 and the original town planning design of Independence Layout were used as primary data; Erdas Imagine 9.2 was used for the object based image classification while ArcGIS 9.3 was used for the analyses. The results show the spatial, graphical (map) as well as statistical analyses of encroachment into public lands, wrong land uses, road width and setback encroachments in the study area. The results of this study are relevant in development control by governmental authorities across the globe. Keywords: Urban development, Supervised Classification, Remote Sensing, Geographic Information System.
 
Keywords: Remote sensing; Cadastre; Land management; Land distribution; Urban development, Supervised Classification, Remote Sensing, Geographic Information System.

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