2012
DOI: 10.1016/j.landurbplan.2012.02.016
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The dynamics of urban expansion and its impacts on land use/land cover change and small-scale farmers living near the urban fringe: A case study of Bahir Dar, Ethiopia

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Cited by 157 publications
(88 citation statements)
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“…Many approaches have been used and developed to identify and examine the effects of driving factors on urban expansion, including bivariate regression (BR) (Haregeweyn, Fikadu, Tsunekawa, Tsubo, & Meshesha, 2012;Wu & Zhang, 2012), multiple linear regression (MLR) (Dewan & Yamaguchi, 2009;Müller, Steinmeier, & Küchler, 2010;Seto et al, 2011), analytic hierarchy process (AHP) (Thapa & Murayama, 2010), adaptive Monte Carlo (aMC) (Chen et al, 2002), redundancy analysis (RDA) (Hietel, Waldhardt, & Otte, 2007), canonical correspondence analysis (CCA) (Fu et al, 2006), and logistic regression (Dendoncker, Rounsevell, & Bogaert, 2007;Dubovyk et al, 2011;Long et al, 2012;Reilly, O'Mara, & Seto, 2009). Of these methods, the most widely used is logistic regression, which has the following advantages: 1) it is an effective method to handle binary dependent variables, which is the case in LULC change (change or no change); 2) there is no assumption of normality or a linear relationship between the dependent and independent variables (Cheng & Masser, 2003); 3) the results of logistic regression can be directly used to predict the locations of future urban expansions (Dubovyk et al, 2011;Hu & Lo, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…Many approaches have been used and developed to identify and examine the effects of driving factors on urban expansion, including bivariate regression (BR) (Haregeweyn, Fikadu, Tsunekawa, Tsubo, & Meshesha, 2012;Wu & Zhang, 2012), multiple linear regression (MLR) (Dewan & Yamaguchi, 2009;Müller, Steinmeier, & Küchler, 2010;Seto et al, 2011), analytic hierarchy process (AHP) (Thapa & Murayama, 2010), adaptive Monte Carlo (aMC) (Chen et al, 2002), redundancy analysis (RDA) (Hietel, Waldhardt, & Otte, 2007), canonical correspondence analysis (CCA) (Fu et al, 2006), and logistic regression (Dendoncker, Rounsevell, & Bogaert, 2007;Dubovyk et al, 2011;Long et al, 2012;Reilly, O'Mara, & Seto, 2009). Of these methods, the most widely used is logistic regression, which has the following advantages: 1) it is an effective method to handle binary dependent variables, which is the case in LULC change (change or no change); 2) there is no assumption of normality or a linear relationship between the dependent and independent variables (Cheng & Masser, 2003); 3) the results of logistic regression can be directly used to predict the locations of future urban expansions (Dubovyk et al, 2011;Hu & Lo, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…Subsequently, we calculated the built-up areas within each zone of Praia, applying intersection operation. Thereafter, we calculated the land consumption per capita (LCR) [16] and utilization density of urban areas (UD) [6]. Proceeding in this away, we delineated, mapped, and quantified the urban expansion of the city of Praia from 1969 to 2015 by overlapping the different time-series urban patches and calculating the corresponding areas in a GIS environment.…”
Section: Delineation Of Urban Areas and Mapping Urban Expansionmentioning
confidence: 99%
“…In this study, as shown in Eq. (5), we determine the rate of urban expansion using the Land Use Change Index (LUCI) presented by Haregeweyn (2012), which can be a significant index to assess urban expansion.…”
Section: Urban Expansion Statistical Analysismentioning
confidence: 99%