Remote Sensing in Investigation of Engineered Underground Structures

Kane, William F.; Peters, Douglas C.; Speirer, R.A.

doi:10.1061/(asce)0733-9410(1996)122:8(674)

Cited by 16 publications

(5 citation statements)

References 3 publications

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“…To predict ground control problems in underground structures [16], lineament is strongly related to discontinuities such as joints, faults, and folds. For these reasons, lineament was used for structural analysis, analysis of the relationship with geology, and assessment of groundwater productivity.…”

Section: Datamentioning

confidence: 99%

Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping

Lee

2015

Sustainability

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Abstract:For the sustainable use of groundwater, this study analyzed groundwater productivity-potential using a decision-tree approach in a geographic information system (GIS) in Boryeong and Pohang cities, Korea. The model was based on the relationship between groundwater-productivity data, including specific capacity (SPC), and its related hydrogeological factors. SPC data which is measured and calculated for groundwater productivity and data about related factors, including topography, lineament, geology, forest and soil data, were collected and input into a spatial database. A decision-tree model was applied and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The resulting groundwater-productivity-potential (GPP) maps were validated using area-under-the-curve (AUC) analysis with the well data that had not been used for training the model. In the Boryeong city, the CHAID and QUEST algorithms had accuracies of 83.31% and 79.47%, and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 86.18% and 80.00%. As another validation, the GPP maps were validated by comparing the actual SPC data. As the result, in the Boryeong city, the CHAID and QUEST algorithms had accuracies of 96.55% and 94.92% and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 87.88% and 87.50%. These results indicate that decision-tree models can be useful for development of groundwater resources. OPEN ACCESSSustainability 2015, 7 13417

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Section: Datamentioning

confidence: 99%

Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping

Lee

2015

Sustainability

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“…Proper decision-making will ensure the reasonable structural integrity and safety of tunnels. In fact, structural health monitoring based on automation and smart techniques is becoming indispensable for the accurate prediction of tunnel safety and stability [68][69][70][71][72]. In addition, the monitoring system must be sufficient to provide all the required information regarding the health status of the tunnel.…”

Section: Discussionmentioning

confidence: 99%

Seepage Actions and Their Consequences on the Support Scheme of Deep-Buried Tunnels Constructed in Soft Rock Strata

Frenelus,

Peng,

Zhang

2024

Infrastructures

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The stability of deep soft rock tunnels under seepage conditions is of particular concern. Aiming at thoroughly discussing seepage actions and their consequences on the support schemes of such structures, the host rocks of the Weilai Tunnel situated in the Guangxi province of China are used as the research subject. Emphasis is placed on adequately examining the seepage conditions, stresses, displacements and plastic zone radii along the surrounding rocks of such tunnels, taking into consideration the Mogi–Coulomb strength criterion and the elastic-plastic theory. Explicitly, this article proposes analytical solutions for stresses, displacements and plastic radii around deep tunnels in soft rocks under seepage conditions by considering the aforesaid criterion and nonlinear elastoplastic approaches. Subsequently, based on the strain-softening model, the coupled actions of seepage and softening on the rocks surrounding the tunnel are studied. In order to investigate the effects of relevant influencing factors on tunnel stability, parametric studies are thoroughly examined. According to the results, it is revealed that the support scheme of deep soft rock tunnels must be of the highest resistance possible to better decrease the plastic zone and the tangential stress along the host rocks. Moreover, throughout the surrounding rocks, the dissemination of pore water pressure is strongly affected by the uneven permeability coefficient under anisotropic seepage states. The combined effects of softening and seepage are very dangerous for the surrounding rocks of deep-buried tunnels. It is also shown that the seepage pressure substantially affects the plastic radii and tunnel displacements. Under high seepage pressure, the surface displacements of the tunnel are excessive, easily exceeding 400 mm. To better guarantee the reasonable longevity of such tunnels, the long-term monitoring of their support structures with reliable remote sensors is strongly recommended.

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“…In an image, a fault is defined as a straight or slightly curved surface feature of natural origin, interpreted directly from the imagery (O' Leary et al 1976;Koike et al 1998). Fault and intersections of lineaments reflect rock structures through which water can percolate and travel up to several kilometers within (Kane et al 1996). In this study, fault zones were detected through interpretation of IRS P6 LISS III imagery and hill-shade maps from a DEM and mapping methodology adopted as drainage density (Fig.…”

Section: Geological Factorsmentioning

confidence: 99%

Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process

Jothibasu

Anbazhagan

2016

Model. Earth Syst. Environ.

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In the present study, an effort has been made to investigate the analytical hierarchy process has been applied to delineate groundwater potential based on integrated geographic information system (GIS) and remote sensing (RS) techniques in Ponnaiyar River basin, Tamil Nadu, India. At first, the climatic factor, topographic factors, water related factors, geological factors, hydrogeological factors and other ecological factors such as land use/land cover and soil depth were derived from the spatial geo-database. Secondly, the 74 groundwater data with high potential yield values of C40 m 3 /h were collected and mapped in GIS. Out these, 44 (60 %) cases were randomly selected for models training, and the remaining 31 (40 %) cases were used for the validation purposes. Then, the assigned weights of thematic layers based on expert knowledge were normalized by eigenvector technique of AHP. To prepare the groundwater potential index, the weighted linear combination (WLC) method was applied in GIS. Finally, the receiver operating characteristic (ROC) curve was drawn for groundwater potential map, and the area under curve (AUC) was computed. Results indicated that the rainfall and slope percent factors have taken the highest and lowest weights, respectively. Validation of results showed that the AHP method (AUC = 76.90 %) performed fairly good predication accuracy. Results of this study could be helpful for better management of groundwater resources in the study area and give planners and decision makers an opportunity to prepare appropriate groundwater investment plans for sustainable environment.

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Remote Sensing in Investigation of Engineered Underground Structures

Cited by 16 publications

References 3 publications

Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping

Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping

Seepage Actions and Their Consequences on the Support Scheme of Deep-Buried Tunnels Constructed in Soft Rock Strata

Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process

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