Yosoon Choi

Multi‐criteria evaluation and least‐cost path analysis for optimal haulage routing of dump trucks in large scale open‐pit mines

A new raster‐based GIS model that combines multi‐criteria evaluation and least‐cost path analysis was developed to determine the optimal haulage routes of dump trucks in large scale open‐pit mines. The model logic can consider multiple criteria simultaneously (i.e. speed, water body, ore body, curve, visibility, haul road maintenance) and can rate the adverse factor scores of truck movement using fuzzy membership functions. After establishing the weights of five factors by pairwise comparisons, the average adverse score grid can be generated by the weighted linear combination of factor and constraint scores. New software, called Dump Traveler, was implemented to improve the availability of the developed model. An application to the Roto South pit in the Pasir open‐pit coal mine, Indonesia, showed that the software can provide rational solutions to determine the optimal routes on truck haulage operations. Moreover, the layout of available haul roads can be evaluated to consider the trade‐off between road maintenance costs and the potential for traffic jams. Variations of weights for factors were found to be sensitive to the optimal haulage routes determined by least‐cost path analysis. The software provides both optimal routes on truck haulage operations and approximately estimated travel times along the routes, therefore it can support other truck dispatching software that mainly considers scheduling problems.

Tunneling Analyst: A 3D GIS extension for rock mass classification and fault zone analysis in tunneling

In this study, an extension called Tunneling Analyst (TA) has been developed in ArcScene 3D GIS software, part of the ArcGIS software package. It dramatically extends the functionalities of ArcScene because it allows: (1) estimation of the 3D distribution of rock mass rating (RMR) values using borehole and geophysical exploration data, (2) the modeling of 3D discontinuity planes such as faults from field-based structural measurements, and (3) analysis of 3D intersections and 3D buffer zones between proposed tunnel alignments and some discontinuities. Because TA can handle and visualize both 2D and 3D geological data in a single GIS environment, the tedious tasks required for data conversion between various software packages can be reduced significantly. The application to the Daecheong tunneling project in Korea shows that TA could present a rational solution to evaluating the rock mass classes along a proposed tunnel alignment and can also provide specific 3D spatial query tools to support the tunnel design work. This paper describes the concept and details of the development and implementation of TA.

A new algorithm for grid-based hydrologic analysis by incorporating stormwater infrastructure

We developed a new algorithm, the Adaptive Stormwater Infrastructure (ASI) algorithm, to incorporate ancillary data sets related to stormwater infrastructure into the grid-based hydrologic analysis. The algorithm simultaneously considers the effects of the surface stormwater collector network (e.g., diversions, roadside ditches, and canals) and underground stormwater conveyance systems (e.g., waterway tunnels, collector pipes, and culverts). The surface drainage flows controlled by the surface runoff collector network are superimposed onto the flow directions derived from a DEM. After examining the connections between inlets and outfalls in the underground stormwater conveyance system, the flow accumulation and delineation of watersheds are calculated based on recursive computations. Application of the algorithm to the Sangdong tailings dam in Korea revealed superior performance to that of a conventional D8 single-flow algorithm in terms of providing reasonable hydrologic information on watersheds with stormwater infrastructure.

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data.

Analysis of photovoltaic potential at abandoned mine promotion districts in Korea

The present study analyzed the photovoltaic (PV) potentials at seven abandoned mine promotion districts in Korea: Taebaek, Samcheok, Jeongseon, Yeongwol, Mungyeong, Hwasun, and Boryeong. A PV system with a capacity of 99 kW was considered at each abandoned mine promotion district. The estimated electric power productions and economic effects of PV systems were analyzed using RETScreen software developed by Natural Resources Canada (NRC). The results showed that the Boryeong district has the highest PV potential, with estimated electric power production of about 83.43 MWh/year, which means a present net value of 69.2 million KRW and a payback period of about 13 years.

A Rapid, Accurate, and Efficient Method to Map Heavy Metal-Contaminated Soils of Abandoned Mine Sites Using Converted Portable XRF Data and GIS

The use of portable X-ray fluorescence (PXRF) and inductively coupled plasma atomic emission spectrometry (ICP-AES) increases the rapidity and accuracy of soil contamination mapping, respectively. In practice, it is often necessary to repeat the soil contamination assessment and mapping procedure several times during soil management within a limited budget. In this study, we have developed a rapid, inexpensive, and accurate soil contamination mapping method using a PXRF data and geostatistical spatial interpolation. To obtain a large quantity of high quality data for interpolation, in situ PXRF data analyzed at 40 points were transformed to converted PXRF data using the correlation between PXRF and ICP-AES data. The method was applied to an abandoned mine site in Korea to generate a soil contamination map for copper and was validated for investigation speed and prediction accuracy. As a result, regions that required soil remediation were identified. Our method significantly shortened the time required for mapping compared to the conventional mapping method and provided copper concentration estimates with high accuracy similar to those measured by ICP-AES. Therefore, our method is an effective way of mapping soil contamination if we consistently construct a database based on the correlation between PXRF and ICP-AES data.

Calculating Time-Specific Flux of Runoff Using DEM Considering Storm Sewer Collection Systems

AbstractA new technique is proposed for calculating time-specific accumulative flux of surface runoff from a digital elevation model (DEM). The method incorporates ancillary datasets required to determine the depth of effective rainfall and a priori information on surface and underground storm sewer collection systems, permitting grid-based hydrologic analysis using a DEM. The diffusion wave equation is used to analyze temporal changes in surface runoff variables such as flow depth and velocity. Therefore, time-specific accumulative flux of surface runoff for each DEM cell, and for inlets and outfalls of the storm sewer collection systems, can be calculated and used to simulate the propagation of flood waves around storm sewers. The technique was applied to the Sangdong tailings dam in Korea that has both surface drainage and storm sewers. The proposed technique provides better time-specific hydrologic information on watersheds that contain both surface and underground storm sewer collection systems, whic...

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH), high content with a low z-score (HL), low content with a high z-score (LH), and low content with a low z-score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Development of Cultural Inheritance Information System using LBS Technologies for Tourists

The object of the study outlined in this chapter is to propose a prototype of cultural inheritance information system that provides tourists with more interactive and dynamic information using Location Based Service (LBS) technology. Using Personal Digital Assistants (PDA) and Global Positioning System (GPS), tourists can acquire cultural information when they approach a place of cultural heritage. A GIS database of Deoksugung Palace, one of the most famous areas of cultural heritage in Seoul, South Korea, was constructed and dynamic functions connecting location information with cultural content in the GIS database were implemented. As a result, it is expected that the dynamic system will contribute to tourist industry by providing location-related cultural information to tourists.

An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest

In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further.