International Journal of Geography and Geology

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Online ISSN: 2305-7041
Print ISSN: 2306-9872
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No. 5

Improving the Geological Understanding of the Niger Delta Basin of Nigeria Using Airborne Gravity Data

Pages: 97-103
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Improving the Geological Understanding of the Niger Delta Basin of Nigeria Using Airborne Gravity Data

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DOI: 10.18488/journal.10/2016.5.5/10.5.97.103

Citation: 1

Eke, P. O , Okeke, F.N , Ezema, P.O

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Eke, P. O , Okeke, F.N , Ezema, P.O (2016). Improving the Geological Understanding of the Niger Delta Basin of Nigeria Using Airborne Gravity Data. International Journal of Geography and Geology, 5(5): 97-103. DOI: 10.18488/journal.10/2016.5.5/10.5.97.103
Airborne gravity anomaly over parts of Niger delta basin of Nigeria has been interpreted qualitatively and quantitatively. The residual anomaly was obtained from the observed field data through a second order polynomial method and then enhanced by a filtering process. The qualitative interpretation of the gridded data reveals NS, EW and NE-SW trending subsurface structures. The inverse and forward modeling results show spherical and dyke-like anomaly structures at depths of between 1,090 m to 3,538 m, while the density contrast of formations identifies areas of  possible hydrocarbon occupation. The Euler deconvolution windowed solutions reveal depth to anomalous sources of between 2,000 m to 9,300 m for structural index of one, and depths of between 3,200 m to 10,600 m for structural index of two. The source parameter imaging reveals depth ranges of between 1,700 m to 10,600 m. The work reveals that the maximum depth to basement in the study area is 10,600 m.

Contribution/ Originality
This study contributes to the existing literature on the structure, stratigraphy and depths to basement information of parts of the southern Niger delta of Nigeria using airborne gravity data. The papers primary contribution is in determining the maximum depths to basement in this region as lying between 9,300 m to 10, 600 m.

An Analysis of Effective Factors on Spatial Distribution of Poverty in Rural Regions of Hamedan Province

Pages: 86-96
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An Analysis of Effective Factors on Spatial Distribution of Poverty in Rural Regions of Hamedan Province

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Microsoft Academic Search
Cite

DOI: 10.18488/journal.10/2016.5.5/10.5.86.96

Citation: 2

Mohammad-Reza Peirovedin , Masood Mahdavi , Yousef-ali Ziyari

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Mohammad-Reza Peirovedin , Masood Mahdavi , Yousef-ali Ziyari (2016). An Analysis of Effective Factors on Spatial Distribution of Poverty in Rural Regions of Hamedan Province. International Journal of Geography and Geology, 5(5): 86-96. DOI: 10.18488/journal.10/2016.5.5/10.5.86.96
The aim of this paper is to examine the spatial distribution of poverty in order to show the effects of poverty rate of a region on the poverty of other rural regions of Hamadan province by making use of spatial econometric approach. The statistical population of the study included 383 rural households participating in the survey of household expenditure and income in 2012 is nine cities of Hamedan province. To analyze the data and to provide the poverty map, Spatial Econometrics and Matlab software and GIS were used as research tools. Initially, the poverty line and the estimated volume of poverty and deprivation were calculated and then, by measuring its volume, the distribution of poverty of the regions and its influence in the cities of the province were provided. Moran’s I-statistic was obtained for poverty equals 0.211 which is significant at the 1% level and shows spatial autocorrelation. Poverty is not distributed equally in rural regions of Hamadan province and the geographical location of households living in the rural areas is effective on poverty. The results of the research showed that in calculating the model by Ordinary Least Squares (OLS) methods and spatial errors due to the spatial dependence in error terms, spatial error methods is better results than the OLS method. Variables such as average household size (+), gender of household head (-) and the proportion of households with housing (-) are statistically significant in identifying the poor people at less than 1% level and the type of jobs (+) at the 5% level respectively.

Contribution/ Originality
In Iran had not been carried out any specific statistical analysis about the spatial distribution of poverty in rural areas. This study is one of few studies which have investigated the effective factors on poverty and to determine poverty map in rural areas with the use of spatial econometric approach.