Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing

Moniruzzaman, Md; Thakur, Praveen K.; Kumar, Pramod; Alam, Ashraful; Garg, Vaibhav; Rousta, Imán; Ólafsson, Haraldur

doi:10.3390/rs13010083

Cited by 69 publications

(33 citation statements)

References 77 publications

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“…The increase in population requires many residential, commercial, industrial activities and many urban facilities, including education, health, civic services, which directly affect the dynamics of the LULC change. For example, a high rate of urbanization led to the conversion of wetland to the built-up area of Dhaka, causing rainfall-induced waterlogging and urban flooding in many parts of the city [80].…”

Section: Land Use Land Cover Change Dynamicsmentioning

confidence: 99%

Impact of Land Use and Land Cover Changes on Urban Ecosystem Service Value in Dhaka, Bangladesh

Rahman

Szabó

2021

Land

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Urban ecosystem services provide a wide range of services to sustain life, social relation, health, etc., and address most of the challenges, including climate change and environmental pollution. While it is recognized that the urban ecosystem substantially contributes to human well-being in cities, there is less attention to consider the value of urban ecosystem service in urban planning and policymaking. This study analyzed the land use and land cover (LULC) dynamics of city of Dhaka over the past three decades (1990–2020) to evaluate the impact of LULC on ecosystem services value (ESV). The estimation of ESV in relation to LULC has been done using the globally used benefits transfer method (BTM). Findings of the study show that built-up area has increased by 188.35% from 1990 to 2020, with an average annual growth rate is about 6.28%. The analysis of ESV shows that it has decreased by 59.55% (85 million USD) from 142.72 million USD in 1990 to 57.72 million USD in 2020 due to the development of the built-up area through conversion of agricultural land, waterbodies, and forest and vegetation land. This study also identified that waterbodies are the greatest contributor to ESV. The result on the elasticity of ESV in relation to LULC implies that about 1% transition in LULC would result in about 0.33% change in total ESV during the study period. We believe that the findings of this study would serve as a reference for the policy maker and urban planner to devise appropriate land use decision to ensure sustainable urban development of Dhaka.

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Section: Land Use Land Cover Change Dynamicsmentioning

confidence: 99%

Impact of Land Use and Land Cover Changes on Urban Ecosystem Service Value in Dhaka, Bangladesh

Rahman

Szabó

2021

Land

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“…Hyperspectral Imaging (HSI) has been extensively utilized for many real-world applications [1]-for instance, crop monitoring [2], vegetation coverage [3], precision agriculture [4], land resources [5], oil spills [6], water quality [7], meat adulteration [8,9], adulteration in household products such as color adulteration in red chili [10,11], microbial spoilage, and shelf-life of bakery products [12].…”

Section: Introductionmentioning

confidence: 99%

Regularized CNN Feature Hierarchy for Hyperspectral Image Classification

Mazzara

Distefano

2021

Remote Sensing

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Convolutional Neural Networks (CNN) have been rigorously studied for Hyperspectral Image Classification (HSIC) and are known to be effective in exploiting joint spatial-spectral information with the expense of lower generalization performance and learning speed due to the hard labels and non-uniform distribution over labels. Therefore, this paper proposed an idea to enhance the generalization performance of CNN for HSIC using soft labels that are a weighted average of the hard labels and uniform distribution over ground labels. The proposed method helps to prevent CNN from becoming over-confident. We empirically show that, in improving generalization performance, regularization also improves model calibration, which significantly improves beam-search. Several publicly available Hyperspectral datasets are used to validate the experimental evaluation, which reveals improved performance as compared to the state-of-the-art models with overall 99.29%, 99.97%, and 100.0% accuracy for Indiana Pines, Pavia University, and Salinas dataset, respectively.

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“…Flooding is considered one of the most catastrophic disasters because of its magnitude of devastating impacts on overall human well-being [1,2]. It contributed to about 39.26% of worldwide natural disasters and caused USD 397.3 billion worth of damage between 2000 and 2014 [3,4].…”

Section: Introductionmentioning

confidence: 99%

GIS-Based Urban Flood Risk Assessment and Management—A Case Study of Delhi National Capital Territory (NCT), India

et al. 2021

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Urban floods are very destructive and have significant socioeconomic repercussions in regions with a common flooding prevalence. Various researchers have laid down numerous approaches for analyzing the evolution of floods and their consequences. One primary goal of such approaches is to identify the areas vulnerable to floods for risk reduction and management purposes. The present paper proposes an integrated remote sensing, geographic information system (GIS), and field survey-based approach for identifying and predicting urban flood-prone areas. The work is unique in theory since the methodology proposed finds application in urban areas wherein the cause of flooding, in addition to heavy rainfall, is also the inefficient urban drainage system. The work has been carried out in Delhi’s Yamuna River National Capital Territory (NCT) area, considered one of India’s most frequently flooded urban centers, to analyze the causes of its flooding and supplement the existing forecasting models. Research is based on an integrated strategy to evaluate and map the highest flood boundary and identify the area affected along the Yamuna River NCT of Delhi. In addition to understanding the causal factors behind frequent flooding in the area, using field-based information, we developed a GIS model to help authorities to manage the floods using catchment precipitation and gauge level relationship. The identification of areas susceptible to floods shall act as an early warning tool to safeguard life and property and help authorities plan in advance for the eventuality of such an event in the study area.

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Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing

Cited by 69 publications

References 77 publications

Impact of Land Use and Land Cover Changes on Urban Ecosystem Service Value in Dhaka, Bangladesh

Impact of Land Use and Land Cover Changes on Urban Ecosystem Service Value in Dhaka, Bangladesh

Regularized CNN Feature Hierarchy for Hyperspectral Image Classification

GIS-Based Urban Flood Risk Assessment and Management—A Case Study of Delhi National Capital Territory (NCT), India

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