GIS-Based Climate Change Induced Flood Risk Mapping in Uhunmwonde Local Government Area, Edo State, Nigeria

Ibanga, Obot Akpan; Idehen, Osaretin Friday

doi:10.9734/ijecc/2020/v10i930225

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…Population flow is a double-edged sword. It optimizes the allocation of resources and improves the whole social and economic welfare and driven the development of ecological economy，but at the same time, it has a certain resistance to the improvement of the whole social and economic welfare [3][4]. Obviously, population mobility plays an important role in social and economic welfare [5][6].…”

Section: Introductionmentioning

confidence: 99%

The Economics of Using Data Processing to Analyze Changes in Population Flows

Zhao¹

2023

Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022

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with the deepening of China's reform, the scale of autonomous population flow is not increasing. In particular, Southwest China is relatively backward in economic development, relatively fast in population growth, complicated ecological environment, frequent population flow and relatively concentrated ethnic minorities. Population flow is the key factor for the rapid development of China's social economy as a whole, and the change of population flow will inevitably lead to the change of economic welfare. This paper aims to study the changes of Economics under different types of population mobility. Taking the four provinces in Southwest China as the research object, this paper boldly tries to combine the theory of population mobility with the theory of economic welfare, and uses the grey correlation analysis method and Data processing method to explore the value of population mobility on economic welfare; on the basis of summing up the successful experience of predecessors in establishing the economic welfare index system, this paper constructs the economic welfare index system of Southwest China, and analyzes the specific aspects of the impact of population flow on the social and economic welfare of Southwest China. Through data analysis, it is found that the flow of population in the province has the greatest impact on the level of economic welfare, the grey correlation coefficient is 0.7565, and its impact is still increasing; although the inter provincial population flow has an impact on the economic welfare level, it is not as big as the intra provincial population flow, and its grey correlation degree is only 0.4988; the impact of inter provincial population inflow on economic welfare is becoming prominent.

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Section: Introductionmentioning

confidence: 99%

The Economics of Using Data Processing to Analyze Changes in Population Flows

Zhao¹

2023

Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022

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Application of geographical information system-based analytical hierarchy process modeling for flood susceptibility mapping of Krishna District in Andhra Pradesh

Penki¹,

Basina²,

Tanniru

2022

Environ Sci Pollut Res

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Flooding is one of the most catastrophic natural disasters in terms of provoking socioeconomic losses.The current study is to foster a ood susceptibility map of Krishna District in Andhra Pradesh (AP) through integrating remote sensing data, geographical information system (GIS), and the Analytical hierarchy process (AHP). Eleven factors including elevation, slope, aspect, land-use/land-cover (LULC), drainage density, topographic wetness index, stream power index, lithology, soil, precipitation, distance from the streams, are considered for identifying and evaluating the spatial distribution of critical ood susceptible regions. Thematic maps of different factors were derived in GIS using remote sensing data obtained from Sentinel-2A (satellite sensor), shuttle radar topography mission digital elevation model (SRTM DEM -v3), and other scienti c data products. An analytical hierarchy process is a mathematical approach for decision support, primarily based on the weight and rank of different causative factors. AHP technique is implemented for ood hazard modeling and ascertaining the Flood Hazard Index (FHI) to produce a ood susceptibility map. Different thematic maps weighed with the AHP framework are combined using overlay analysis to produce the Flood Susceptibility map of the study region. The outcomes of the study demonstrate the potential of GIS and AHP in providing a premise to recognize the vulnerable areas that are susceptible to ood. According to the ndings, the Flood Hazard Index is 42% and the study region is classi ed into high, moderate, and low susceptible respectively. on. Furthermore, the lack of high-temporal-scale remote sensing data is a key impediment to ood mapping.The AHP model's ood vulnerability zone was classi ed into three groups (high, moderate, and low). The ndings clearly show that regions with low elevation and slope, high TWI, low SPI, high drainage density, and high precipitation are primarily risk-prone due to the high potential of ooding in such areas. The AHP technique used expert judgment and expertise to determine the best weights for the components that contribute to ood risk. The ease of handling, exibility, and low cost of the applicable technique make it possible to employ, particularly in such a location with relatively limited data and information. In the present preliminary assessment of ood hazards, the AHP technique serves its purpose.As, food risk management is a crucial segment of all social and environmental processes aimed at minimizing loss of life, injury, and property damage. The ndings of this research will assist decisionmakers in carrying out adequate ood management in future. Finally, the present study's maps may be utilized as a reference for ood prevention and preparedness by planners, developers, and the government. Knowledge of high-risk zones is essential for local governments to adequately control ooding and plan the execution of necessary ood prevention systems.

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GIS-Based Climate Change Induced Flood Risk Mapping in Uhunmwonde Local Government Area, Edo State, Nigeria

Cited by 2 publications

References 10 publications

The Economics of Using Data Processing to Analyze Changes in Population Flows

The Economics of Using Data Processing to Analyze Changes in Population Flows

Application of geographical information system-based analytical hierarchy process modeling for flood susceptibility mapping of Krishna District in Andhra Pradesh

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