Urban Expansion Assessment by Using Remotely Sensed Data and the Relative Shannon Entropy Model in GIS: A Case Study of Tripoli, Libya

By Alsharif, Abubakr A. A.; Pradhan, Biswajeet et al. | Theoretical and Empirical Researches in Urban Management, February 2015 | Go to article overview

Urban Expansion Assessment by Using Remotely Sensed Data and the Relative Shannon Entropy Model in GIS: A Case Study of Tripoli, Libya


Alsharif, Abubakr A. A., Pradhan, Biswajeet, Mansor, Shattri, Shafri, Helmi Zulhaidi Mohd, Theoretical and Empirical Researches in Urban Management


1. INTRODUCTION

Rapid urbanization has been recorded in developing countries during the last century, thus providing an indication of increasing urban issues and environmental problems in such areas (Angel et al., 2005; Kumar et al., 2007). The rapid economic development of various developing countries has caused noticeable changes in urban landscapes (Yeh, Xia, 2001). Urbanization progression is considered the most prominent driver of land cover change in the history of human civilization (Deka et al., 2010; Weng, 2001). Uncontrolled population growth causes uncontrolled urban sprawl, which leads to serious problems such as food insufficiency, illegal settlements, environmental pollution, environmental deterioration, occupation of fertile farming lands, forest destruction, reduction of surface water bodies, and permanent changes in land cover (Al-sharif et al., 2013a; Benfield et al., 1999; Grimm et al., 2000; Hedblom and Soderstrom, 2008; Maktav et al., 2005; Pathan et al., 1991; Weng et al., 2007). Information on the amount and process of urban expansion is important for conducting land and water resource management, facility allocation, urban planning, and so on. Urban sprawl assessment, prediction, and monitoring represent the necessary information for urban development plans. Urban planners require handy tools to achieve smart and balanced growth, examine and understand current land-use status, and measure future requirements (Alpopi et al., 2011; Baptista de Silva, et al.,2012; Huang, et al.. 2009; Jat, et al.. 2008; Wang and Mountrakis, 2010). Sandhya and Joshi (2013) reported that studying and analyzing changes and monitoring different time series are difficult by using traditional techniques of surveying. However, remote sensing systems are practical tools for collecting data in a quick and cost effective manner. In urban studies, analyzing and understanding the behavior of spatiotemporal changes in urban expansions and patterns are needed. The urbanization process can be analyzed by using geographic information systems (GIS), remote sensing, and the ground information of the study area (Al-shalabi, et al., 2013a, b; Al-sharif and Pradhan, 2014a, 2014b). Furthermore, detecting and mapping forms of urban sprawl patterns on landscapes can be achieved efficiently by using the aforementioned approaches (Barnes, et al., 2001; Bhatta, 2009; Sui, 1998). However, researchers have reported that urban sprawl lacks a specific definition (Bhatta, et al., 2010b). Nonetheless, urban sprawl can be defined simply as the quantity of urbanized area and the amount of its dispersal in the study area landscape.

Thus, areas with impervious surfaces increase in urban sprawl and the further spreading of impervious surfaces corresponds to higher intensity sprawl (Jaeger, et al., 2010). The definition of urban sprawl can be used to describe and explain both situations, that is, the process (the change of urban sprawl in a landscape) and pattern (the amount of urban sprawl in a landscape) (Sarvestani, et al., 2011). Several measures and factors are used to identify and quantify urban sprawl, although many of these measures exhibit several limitations (Bhatta, et al., 2010b; Ramachandra, et al., 2013). Shannon's entropy was used for several statistical data analyses. Shannon's entropy technique can verify and identify the disparity of urban sprawl and urban areas (Alabi, 2009; Kumar, et al., 2007; Lata et al., 2001; Li and Yeh, 2004; Sudhira, et al., 2004; Yeh and Xia, 2001).

The aforementioned model is commonly used in urban geographic studies. Nevertheless, all former urban research have illustrated Shannon's entropy method in different spatial zones divisions either to analyze the urban patterns (Yeh and Xia, 2001) or to identify the urban sprawl of a specific area for a specific period (Kumar, et al., 2007).However, entropy divisions have not considered sprawl direction, sprawl variation, and distance to central business districts (CBDs). …

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