Modeling Urban Land Cover Growth Dynamics Using Multi‑Temporal Satellite Images: A Case Study of Dhaka, Bangladesh

Ahmed, Bayes; Ahmed, Raquib

doi:10.3390/ijgi1010003

Cited by 216 publications

(149 citation statements)

References 22 publications

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“…The MLP is one of the most suitable algorithms for classification and prediction of LULC changes and able to solve non-linear separable problems (Ahmed & Ahmed, 2012). Based on the supervized Backpropagation (BP) algorithm, the MLP is a feed forward artificial neural network model that maps sets of input data into a set of appropriate output.…”

Section: Transition Potential Modelingmentioning

confidence: 99%

“…Several studies have revealed that the integrated MultiLayer Perceptron-Markov chain analysis (MLP-MCA) method is a robust tool to quantify and model the spatio-temporal LULC changes that combines remote sensing and GIS efficiently (Ahmed & Ahmed, 2012;Mishra et al, 2014;Ozturk, 2015). In the MLP-MCA hybrid model, the MLP neural network is trained by supervized backpropagation (BP) algorithm with efficient generalization capability for each LULC transition and simulation (Maithani, 2015), while the MCA model determines transition probability areas to predict likely LULC changes in the future (Dadhich & Hanaoka, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

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An accurate information on the amount and location of Land use and land cover (LULC) changes is necessary to develop and implement a sustainable-urban planning.This research investigates the potential of an integrated Multi-Layer Perceptron and Markov Chain Analysis (MLP-MCA) to map and accurately predict the future LULC change scenarios in Lagos Metropolitan Region of Nigeria. Multi-temporal LULC datasets derived from remotely sensed Landsat images from 1984, 2000 and 2015 were used for modeling, validation and prediction. Predicted LULC changes for 2030 and 2050 were performed based on the LULC map of 2015 using MLP-MCA method. The result reveals a significant expansion of built-up areas during the whole study period. Analysis of LULC distribution in Lagos metropolitan region shows that about 50% of urban land expansion happened beyond the administrative boundary of Lagos State during the period of 2000-2015. It is predicted that more than 75% of future urban growth will occur across the border of Lagos State, in the neighbouring Ogun State by 2050. These results imply that a strong and consistent collaboration between different states is crucial to establish an effective regional planning framework and ensure a proper planned growth of the metropolitan region.ARTICLE HISTORY

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Section: Transition Potential Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

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“…The overall accuracy was calculated separately for each time point (1995, 2005 and 2015) [38]. The result accuracies of the accuracy assessment of the LULC classification were 77.4%, 79.6% and 76.8% for 1995, 2005, and 2015, respectively [39]. (See Appendix A for more details).…”

Section: Assessing the Accuracy Of Lulc Mapsmentioning

confidence: 99%

Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models

Wang

Murayama

2017

IJGI

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Abstract:In recent years, urban areas have been expanding rapidly in the world, especially in developing countries. With this rapid urban growth, several environmental and social problems have appeared. Better understanding of land use and land cover (LULC) change will facilitate urban planning and constrain these potential problems. As one of the four municipalities in China, Tianjin has experienced rapid urbanization and such trend is expected to continue. Relying on remote sensing (RS) and geographical information system (GIS) tools, this study investigates LULC change in Tianjin city. First, we used RS to generate classification maps for 1995, 2005, and 2015. Then, simulation models were applied to evaluate the LULC changes. Analysis of the 1995, 2005, and 2015 LULC maps shows that more than 10% of the cropland areas were transformed into built-up areas. Finally, by employing the Markov model and cellular automata (CA) model, the LULC in 2025 and 2035 were simulated and forecasted. Our analysis contributes to the understanding of the development process in the Tianjin area, which will facilitate future planning, as well as constraining the potential negative consequences brought by future LULC changes.

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“…However, other non-structural measures such as land use planning can play important role for reducing flood risk. Dewan and Yamaguchi (2009) and Ahmed and Ahmed (2012) …”

Section: Resultsmentioning

confidence: 99%

An integrated approach of flood risk assessment in the eastern part of Dhaka City

et al. 2015

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The flood risk is a function of the flood hazard, the exposed values and their vulnerability. In addition to extreme hydrological events, different anthropogenic activities such as extensive urbanization and land use play an important role in producing catastrophic floods.Considerations of both physical and social dimensions are therefore equally important in flood risk assessment. However, very often the risk assessment studies either focus on physical or social dimensions. In addition, the available studies often focus on economic valuation of only direct tangible costs. In this study, we provide an integrated flood risk assessment approach that go beyond valuation of direct tangible costs, through incorporating physical dimensions in hazard and exposure and social dimensions in vulnerability. The method has been implemented in the Dhaka City, Bangladesh, an area internationally recognized hotspot for flood risk. In this study, flood hazards for different return periods are calculated in spatial environment using a hydrologic model, HEC-RAS. Vulnerability is assessed through aggregation of various social dimensions i.e., coping and adaptive capacities, susceptibility. We assess vulnerability for both baseline and improved scenario. In the baseline scenario, current early warning for study area is considered. In the alternative scenario, the warning system is expected to improve. Aggregating hazard, exposure and vulnerability, risk maps (in terms of both tangible and intangible costs) of several return period floods are produced for both baseline and improved scenario. Compared to traditional assessments, the integrated assessment approach used in this study generates more information about the flood risk. Consequently, the results are useful in evaluating policy alternatives and minimizing property loss in the study area.

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Modeling Urban Land Cover Growth Dynamics Using Multi‑Temporal Satellite Images: A Case Study of Dhaka, Bangladesh

Cited by 216 publications

References 22 publications

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models

An integrated approach of flood risk assessment in the eastern part of Dhaka City

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