scholarly journals AUTOMATIC LINEAMENTS MAPPING AND EXTRACTION IN RELATIONSHIP TO NATURAL HYDROCARBON SEEPAGE IN UGWUEME, SOUTH-EASTERN NIGERIA

2021 ◽  
Vol 47 (1) ◽  
pp. 34-44
Author(s):  
Mfoniso Asuquo Enoh ◽  
Francis Ifeanyi Okeke ◽  
Uzoma Chinenye Okeke

The study focus on the integration of Remote Sensing and Geographic Information System for identification and delineation of lineaments in relation to natural hydrocarbon seepage, which occur in Ugwueme, South-Eastern Nigeria. To achieve this objective, remotely sensed data (ASTER Digital Elevation Model and Landsat 8 OLI/TIRS) were used to depict the surface expression of faults, folds and fractures which are expressed in the form of lineaments. The global positioning system (GPS) was also used for ground verification. The geology map of the study area, which is elucidated in the geology of Nigeria was used to show the distribution of rocks and other geologic structures. The delineation of lineament features was done automatically with the PCI Geomatica while the Rock ware was used to generate the Rose diagram for demonstration of the direction of the extracted lineaments. The classification of the lineaments density and the lineaments intersection analysis were categorized as very low, low, moderate, high and very high classes respectively. Areas classified as very high to high lineaments density are potential zone, which act as conduits for hydrocarbon seepage. The result shows that a total lineament frequency of 947 km and a total lineament length of 946 km were delineated from the satellite data. The result further shows that areas with high lineaments density are concentrated in the southwest, south, central and northern part of the study area while areas with low lineament density were found within the eastern part of Ugwueme. The Rose diagram highlight the major trend in the (NE-SW), (N-S) and (NW-SE) directions, and the minor trend in the (W-E) direction. These directional trends depict the directions of lineaments which act as conduits zones for hydrocarbon seepage in the region. The overall findings of the study shows that lineament density, lineament intersection and rose diagrams are concepts applicable in hydrocarbon oil and gas seepages.

2020 ◽  
Vol 61 (4) ◽  
pp. 11-24
Author(s):  
Thao Phuong Thi Do ◽  
Chinh Mai Thi Duong ◽  
Tai Anh Le ◽  
Vinh Tuyet Thi Tran ◽  
Ha Thu Thi Nguyen ◽  
...  

Drought is one of the natural phenomena that seriously affects to society in general as well as the lives of people in particular. Therefore, determining early drought is necessary. Remote sensing and GIS technology with extracting and overlaping tools which can assess the extent of drought from geospatial informations in a wide area. Experimental area is Ninh Thuan province, where drought often occur. Five indexes (TCI, VCI, SAVI, WWSVI, TVDI) are extracted from Landsat 8. The weights according to the level of influence is determine by Analytic Hierarchy Process (AHP). Results shows current drought in five levels: no drought; low; medium; high and very high, then compared with the drought warning system in the South-central region. The areas of Ninh Phuoc, Ninh Son and Phan Rang are higher drought phenomena at the time of dry season (accounting for about 60% of the total provincial area).


Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 669
Author(s):  
Abid Sarwar ◽  
Sajid Rashid Ahmad ◽  
Muhammad Ishaq Asif Rehmani ◽  
Muhammad Asif Javid ◽  
Shazia Gulzar ◽  
...  

The changing climate and global warming have rendered existing surface water insufficient, which is projected to adversely influence the irrigated farming systems globally. Consequently, groundwater demand has increased significantly owing to increasing population and demand for plant-based foods especially in South Asia and Pakistan. This study aimed to determine the potential areas for groundwater use for agriculture sector development in the study area Lower Dir District. ArcGIS 10.4 was utilized for geospatial analysis, which is referred to as Multi Influencing Factor (MIF) methodology. Seven parameters including land cover, geology, soil, rainfall, underground faults (liniment) density, drainage density, and slope, were utilized for delineation purpose. Considering relative significance and influence of each parameter in the groundwater recharge rating and weightage was given and potential groundwater areas were classified into very high, high, good, and poor. The result of classification disclosed that the areas of 113.10, 659.38, 674.68, and 124.17 km2 had very high, high, good, and poor potential for groundwater agricultural uses, respectively. Field surveys for water table indicated groundwater potentiality, which was high for Kotkay and Lalqila union councils having shallow water table. However, groundwater potentiality was poor in Zimdara, Khal, and Talash, characterized with a very deep water table. Moreover, the study effectively revealed that remote sensing and GIS could be developed as potent tools for mapping potential sites for groundwater utilization. Furthermore, MIF technique could be a suitable approach for delineation of groundwater potential zone, which can be applied for further research in different areas.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Akshaya Beluru Jana ◽  
Arkal Vittal Hegde

The coastal zones are highly resourceful and dynamic. In recent times, increased events of tropical cyclones and the devastating impact of the December 2004 tsunami have brought forth the importance of assessing the vulnerability of the coast to hazard-induced flooding and inundation in coastal areas. This study intends to develop coastal vulnerability index (CVI) for the administrative units, known astalukasof the Karnataka state. Seven physical and geologic risk variables characterizing the vulnerability of the coast, including rate of relative sea level change, historical shoreline change, coastal slope, coastal regional elevation, mean tidal range, and significant wave height derived using conventional and remotely sensed data, along with one socioeconomic parameter “population,” were used in the study. A total of 298 km of shoreline are ranked in the study. It was observed that about 68.65 km of the shoreline is under very high vulnerable category and 79.26 km of shoreline is under high vulnerable category. Of the remaining shoreline, 59.14 km and 91.04 km are of moderate and low vulnerable categories, respectively.


2018 ◽  
Vol 10 (10) ◽  
pp. 1521 ◽  
Author(s):  
Yugang Tian ◽  
Hui Chen ◽  
Qingju Song ◽  
Kun Zheng

The distribution and dynamic changes in impervious surface areas (ISAs) are crucial to understanding urbanization and its impact on urban heat islands, earth surface energy balance, hydrological cycles, and biodiversity. Remotely sensed data play an essential role in ISA mapping, and numerous methods have been developed and successfully applied for ISA extraction. However, the heterogeneity of ISA spectra and the high similarity of the spectra between ISA and soil have not been effectively addressed. In this study, we selected data from the US Geological Survey (USGS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral libraries as samples and used blue and near-infrared bands as characteristic bands based on spectral analysis to propose a novel index, the perpendicular impervious surface index (PISI). Landsat 8 operational land imager data in four provincial capital cities of China (Wuhan, Shenyang, Guangzhou, and Xining) were selected as test data to examine the performance of the proposed PISI in four different environments. Threshold analysis results show that there is a significant positive correlation between PISI and the proportion of ISA, and threshold can be adjusted according to different needs with different accuracy. Furthermore, comparative analyses, which involved separability analysis and extraction precision analysis, were conducted among PISI, biophysical composition index (BCI), and normalized difference built-up index (NDBI). Results indicate that PISI is more accurate and has better separability for ISA and soil as well as ISA and vegetation in the ISA extraction than the BCI and NDBI under different conditions. The accuracy of PISI in the four cities is 94.13%, 96.50%, 89.51%, and 93.46% respectively, while BCI and NDBI showed accuracy of 77.53%, 93.49%, 78.02%, and 84.03% and 58.25%, 57.53%, 77.77%, and 64.83%, respectively. In general, the proposed PISI is a convenient index to extract ISA with higher accuracy and better separability for ISA and soil as well as ISA and vegetation. Meanwhile, as PISI only uses blue and near-infrared bands, it can be used in a wider variety of remote sensing images.


2019 ◽  
Vol 12 (25) ◽  
pp. 44-55 ◽  
Author(s):  
Safaa Sabah Adhab

This research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration the lineaments because its plays an important role in the study area.


2022 ◽  
Vol 14 (2) ◽  
pp. 348
Author(s):  
Yashon O. Ouma ◽  
Lone Lottering ◽  
Ryutaro Tateishi

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.


Author(s):  
A. Montaldo ◽  
L. Fronda ◽  
I. Hedhli ◽  
G. Moser ◽  
S. B. Serpico ◽  
...  

Abstract. In this paper, a multiscale Markov framework is proposed in order to address the problem of the classification of multiresolution and multisensor remotely sensed data. The proposed framework makes use of a quadtree to model the interactions across different spatial resolutions and a Markov model with respect to a generic total order relation to deal with contextual information at each scale in order to favor applicability to very high resolution imagery. The methodological properties of the proposed hierarchical framework are investigated. Firstly, we prove the causality of the overall proposed model, a particularly advantageous property in terms of computational cost of the inference. Secondly, we prove the expression of the marginal posterior mode criterion for inference on the proposed framework. Within this framework, a specific algorithm is formulated by defining, within each layer of the quadtree, a Markov chain model with respect to a pixel scan that combines both a zig-zag trajectory and a Hilbert space-filling curve. Data collected by distinct sensors at the same spatial resolution are fused through gradient boosted regression trees. The developed algorithm was experimentally validated with two very high resolution datasets including multispectral, panchromatic and radar satellite images. The experimental results confirm the effectiveness of the proposed algorithm as compared to previous techniques based on alternate approaches to multiresolution fusion.


Author(s):  
E. E. Epuh ◽  
N. O. Jimoh ◽  
M. J. Orji ◽  
O. E. Daramola

With the increase in population of Ogun state, the necessity to provide water to the populace has become a disturbing problem. In this study, a systematic approach to delineate the groundwater potential zones of the state was carried out using Remote Sensing, Geographic Information Systems (GIS) and Hydrogeophysics as a tool. Vertical Electrical Sounding (VES) observations were also carried out in OGD Sparklight Estate to validate the results obtained from the integrated remote sensing and GIS observation and also determine the aquifer depth and possible pollution. The various thematic maps such as: soil map, land use/Land, geological map, rainfall map, lineaments map were obtained from enhanced satellite imagery and Slope map was generated from Shuttle Radar Topographic Mission elevation model (SRTM DEM). These maps were overlaid in terms of weighed overlay method using Spatial Analysis tool in Arc GIS 10.4. During weighed overlay analysis, different ranks were given to each individual parameter of each thematic map and weights were assigned according to their influence. The groundwater potential map obtained from the study area showed that 47% of the total study area (Ogun state) lie within the “very high” potential zone, 15% of the area falls within the “high”, 30% lies within the of “moderate” zone, 5% lies within the “low “potential zone while “2% “ lies within the very low potential zone. The very high potential areas lie within the sedimentary zone in the southern part of the study area with high alluvial deposits, while the “very low” prospect zone lies majorly within the basement complex zone in the northern part of the study area. The boreholes susceptible to salt water intrusion were identified and the best drilling point with respect to depth were also determined.


2017 ◽  
Vol 1 (2) ◽  
pp. 19-26
Author(s):  
Parveen Kumar Jha

 This research paper gives checklist of common birds of Chitwan National Park, which is a wild-life protected area in south-central Nepal. It covers tropical and sub-tropical vegetation. It is first protected area and includes 932 sq. km. Common birds observed are about 170 belonging to 48 Avian families during 2013-2014. Present investigator has very minutely observed birds in habitat conditions. Bird species were recognized by very high binocular. Birds were thoroughly studied from point of view of Taxonomy. Machans were also erected for observing birds.


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