REMOTE SENSING TECHNIQUES OF GEOSPATIAL GEOTECHNICAL SITE CHARACTERIZATION APPLIED TO COMPETENCE STUDIES OF MINE TAILINGS IMPOUNDMENTS AND SLOPE STABILITY INVESTIGATIONS WILHELM MAX-OTTO GREUER A DISSERTATION Submitted in partial fulfillment of the requirements For the degree of DOCTOR of PHILOSOPHY (Mining Engineering) MICHIGAN TECHNOLOGICAL UNIVERSITY 2006 Copyright © Wilhelm Max-Otto Greuer 2006 UMI Number: 3209901 Copyright 2006 by Greuer, Wilhelm Max-Otto All rights reserved. INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted.
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ProQuest Information and Learning Company 300 North Zeeb Road P. Box 1346 Ann Arbor, MI 48106-1346 This dissertation, ‘Remote Sensing Techniques of Geospatial Geotechnical Site Characterization Applied to Competence Studies of Mine Tailings Impoundments and Slope Stability Analysis’, is hereby approved in partial fulfillment of the requirements for the degree of DOCTOR of PHILOSOPHY in the field of Mining Engineering. DEPARTMENT or PROGRAM: Mining Engineering Signatures: Dissertation Advisor & `“., Fellow, ASCE Dr. Ralph z TT oe _ Dr.
Rose Department Chair ey,ViePF Dr. Pennington Date Vey S , CCOflc _ b2 TABLE OF CONTENTS ABSTRACCTT. c- có 9 HH HH HH 7081000386008 180080049161000000000181641800800010000001111000000000504 7 «S555 5651Sese2 CHAPTER I: INTRODUCTION .1 SOCIAL IMPACTS & COSTS OF LANDSLIDES.2 THE CAUSE OF LANDSLIDES.-- cành HH1 Hài Hà Hà Hi tk HH0 10 1.3 TRADITIONAL RISK MITIGATION & SITE CHARACTERIZATION.4 SITECHARACTERIZATION USING REMOTE SENSING. Hà HH HH HH Tà T11 TT 114111481 111 01111.
17 CHAPTER II: SITE CHARACTERIZATION OF GROUND PROPERTIES; A REMOTE SENSING APPROACH. co nh HH nHY n9 g1 0104100010 000000040040800100004000014010010101160 19 2.1 REQUIRED INPUT PARAMETERS FOR SLOPE STABILITY ANALYSIS.2 REMOTE SENSING APPROACH FOR SLOPE ENGINEERING. 20 HH HH Hà tinh 20 2.4 DETERMINATION OF DIELECTRIC PERMITTIVŨY. che 23 Hà tiệt 29 2.5 PENETRATION DEPTH OF WAVE SIGNAL,.6 SOIL POROSITY & MOISTURE CONTENÏT.
36 CHAPTER II: SHEAR STRENGTH PARAMETERS THROUGH REMOTE SENSING.1 SHEAR STRENGTH OF SOIL. cà Ăn S919 Hà in 01101111 trg 38 CHAPTER IV: GEOSPATIAL TOPOGRAPHIC DATA.1 DIGITIZED FIELD SURVEY DA TA. Hàn Hà n0 HH1 1111210 11 tr.2 EXTRACTING SLOPE ANGLES. nha Hà Hà Hà Hà Hà th HH H1 tt tre 50 CHAPTER V: ALTERNATE SITE CHARACTERIZATION METHODS 54 5.1 GEOBOTANICAL INDICATORS & SOIL IDENTIFICATION.2 SOIL CLASSIFICATION THROUGH SPECTRAL SIGNATURES.
se 59 CHAPTER VI: PORE WATER PRESSURES & THE PHREATIC SUREACE.1 GROUNDWATER AND SLOPE FAILDRE.-- tt Hé HH 012 này 67 6.2 GROUND EMISSIVITY & THE PHREATIC SURFACE.3: CAPILLARITY & THE PHREATIC SURFACE.4: DYNAMIC PORE PRESSURES. - LH H non HH Hà tà Hà Hà Ha Hà Tà HH0 11111121114 77 CHAPTER VII: EXTENDING SLOPE STABILITY ANALYSIS TO GIS MAPPING.1: INFINITE SLOPE ANALYSIS. con Ha Hà tà no Hà HH HH0 01014111116 90 1Ÿ «SH n1 161 vr6 CHAPTER VIII: CASE STUDY.1: CASE STUDY SITE SELECTION. ¿5 cà SẺ 22122222 tt th gà, 95 nhe-ít 98 Ăn .2: GEOTECHNICAL DATA FOR THE SITE.3: REMOTE SENSING IMAGERY FOR SLOPE ANALVYSIS.4: CROSS VALIDATION OF CALCULATED PARAMETERS TO FIELD DATA.
cu HH HH HH2 HH0 H00 1 001 111tr.6: GENERATION OF GEOSPATIAL INPUT ĐATA.cc chau ey 114 8.7: STABILITY ANALYSIS THROUGH THE PLANAR SLIDING MODEL.- HH Hà 2 Hà Hà Hà nh ni 111 r0 tr. 130 CHAPTER IX: DISCUSSION. co cuc HH nền Y4 0n 08000041400000000001610000040800009000008 137 9.1: ANALYSIS OF TAILINGS DAM FAILURE.3: NARROWING THE GAP BETWEEN ENGINEERING AND SCIENCE. 141 CHAPTER X: CONCLUSIONS & RECOMMENDATIONS.1: ADVANTAGES OF REMOTE SENSING APPROACH.2: PROBLEMS WITH REMOTE SENSING APPROACH.3: AUTOMATED LANDSLIDE HAZARD WARNING SYSTEM.4: POTENTIAL USERS & BENEFICIARIES OF THESE TECHNIQUES.
153 APPENDIX A: FRESNEL INVERSION PROOE. 158 APPENDIX B: CONE PENETROMETER TEST RESULTS FOR SHEAR STRENGTH. 162 APPENDIX C: WELL DATA. cs srescesor s ors sc rens arsen s ersone 184 APPENDIX D: PATCH MAP OF Fs VALUES OF DOWNSTREAM TAILINGS IMPOUNDING STRUCTURE, INFINITE SLOPE METHOD 185 APPENDIX E: REMOTE SENSING TECHNIQUES OF ASSESSING FUGITIVE PARTICULATE EMISSION POTENTIAL AND THE EFFECTIVENESS OF PARTICULATE SUPPRESSION .cssssssssoosssossossnesssonsncsorensoesatesssessssessescesusnesseoreneesesesonensensansnserseesensensentessssenees 186 APPENDIX F: MINE TAILINGS STRENGTH AND BEARING CAPACITY DISCRIMINATION WITH MULTISPECTRAL IMAGERY.eeeSeseeeseisee 4 99099885699 99000 6849489908084 04060008090409004005070800000989146000060940899088409 240 LIST OF TABLES & FIGURES FIGURE 1.1: AERIAL IMAGERY OF STUDY SITE.1: THE ELECTROMAGNETIC WAVE SPECTRUM.1: PROPORTIONALITY CONSTANT K; RELATING SHEAR STRENGTH TO THE SHEAR MODULUS.ecce<sesesssssx ti V08 408490004.1: SOIL COHESION REGRESSED FROM MOHR ENVELOPE.1: DEM DATA SOURCE EXAMPLE; AERIAL PHOTO 48 FIGURE 4.2: DEM DATA SOURCE EXAMPLE; USGS 7.5' TOPOGRAPHIC MAP OF PART OF THE ISHPEMING QUADRANGLE.3: DEM PRODUCED WITH DOQQ PHOTO AND USGS 7.4: DEM 10? ELEVATION CONTOURS.6: COMPUTER-CALCULATED SLOPE ANGLES "¬".1: TEXTURAL TRIANGLE OF SOIL CLASSES.2: AVIRIS IMAGE FOR SPECTRAL GEOLOGIC MAPPING “ toes 62 FIGURE 5.3: SPECTRAL SIGNATURE OF AVIRIS PIXEL VERSUS NASA JPL CATALOGUED SPECTRAL SIGNA TURE.4: GEOLOGIC MAP GENERATED BY SPECTRAL MATCHING.5: SPECTRAL ANGLE ILLUSTRATED FIGURE 6.
DEPTH FOR INCREASING MOISTURE CONDITIONS.2: EMISSIVITY DEPTH VS.3: WATER CONTENT VS. MATRIC POTENTIAL FOR VARIOUS SOILS .1: Y,,’ AND B VALUES OF PRINCIPAL SOIL CLASSES.4: SLOPE FAILURE DUE TO HIGH SEEPAGE RATES.2: Ry; PARAMETER FOR GP MODEL.osc on n1 11191 115016551 0560855054 TABLE 6.10: GROUNDWATER POTENTIAL GTP.o cGc cóc S900 3 0 THỌ 005600306095010710011051 851 s0 95095 0558580858 815055 88 FIGURE 6.5: GEOMETRIC CHARACTERISTICS OF SLICES.6: WATER PRESSURE DISSIPATION VECTOR DIAGRAM. co non HH ngang nen FIGURE 7.1: PLANAR SLIDING FAILURE MODEL.1: TAILINGS BERM CROSS SECTION.2: TAILINGS BASIN DRAINAGE CONTINGENT TO DAM FAILURE 98 TABLE 8.1: AVAILABLE GROUND-TRUTH DATA VALUES .2: CALCULATED DATA VALUES g4 ssssssssssssses 104 FIGURE 8.3: NAPP/DOQQ IMAGE OF TAILINGS BASIN AND DATA COLLECTION LOCATIONS.4: COMPUTED VERSUS ACTUAL VALUES FORP sscsssssssssseseesvsunenssncuensensesconens 109 FIGURE 8.5: CALCULATED VERSUS ACTUAL GROUND COHESION .6: CALCULATED VERSUS ACTUAL ANGLES OF INTERNAL FRICTION .7: COMPUTED VERSUS ACTUAL DEPTHS OF THE GROUNDWATER TABLE .3: GWT DATA FROM WELLS THROUGHOUT ONTONAGON COUNTY, MICHIGAN.8: TAILINGS DENSITY COMPUTED FROM IMAGE .9: COHESION COMPUTED FROM *.GRD FILES FOR P & H.10: INTERNAL FRICTION ANGLE, IN DEGREES, COMPUTED FROM “NÑORMSTRESS***,GRD”, “SHEAR***,GRD”, “MEANNORMAL.GRD” AND “MEANSHEAR.11: COMPUTED GWT DEPTH&S. veesees ssessesessssssessesaseessasese LOO FIGURE 8.12: MEAN DOWNSTREAM TAILINGS BERM F; VALUES FOR INCREASING DEPTHS; PLANAR SLIDING MODEL,.csccssscsssssenavene seeeee mm.13: GIS OUTPUT OF SAFETY INDICES THROUGHOUT THE DOWNSTREAM TAILINGS DAM STRUCTURE; PLANAR SLIDING MODEL.14: COMPUTATIONAL SEQUENCE OF PRINCIPAL PARAMETERS.4: COMPUTED PHREATIC SURFACE DEPTHS.
135 ABSTRACT: The research presented in this dissertation suggests methods of deriving critical engineering properties of soils from appropriate high altitude spectral data, or imagery. Soil interaction with ambient or applied electromagnetic radiation results in spatially varying degrees of reflection and absorption of electromagnetic radiation. Soil properties govern the band-specific interaction of the soil with the applied electromagnetic radiation, visually resulting in a soil’s colour and brightness. The visual appearance, or cumulative interaction of the soil with each applied band of electromagnetic radiation, is recorded by cameras mounted on a remote sensing platform.
From the resulting imagery, representing the soil’s reflection/absorption intensity, key dielectric soil properties are calculated. Dielectric properties govern the soil’s reflection and absorption intensities. In turn, dielectric properties are governed by the soil’s structure and composition and are indicative of the soil’s principal geotechnical properties. Dielectric properties of soil are the tie connection between the engineering properties of soil and geospatial data provided as imagery.
This provides a fast, simple, inexpensive, and comprehensive geotechnical site assessment, performed by a single user in a GIS system, with soil spectral data as the principal input. Included with the image-extracted soil properties are principal slope engineering parameters. Using GIS and the prescribed series of computations, image-extracted geospatial data sets representing these key properties are applied to an area-wide modification of a common slope stability analysis method, resulting in a map illustrating the risk of slope failures throughout the area encompassed by imagery. This method is the skeleton of a possible automated satellite-based forecasting and warning system against landslides.
In addition to the presented slope stability investigation, ground moisture surveys are also applied to competence investigations involving ground bearing capacity and fugitive dust emissions.1 SOCIAL IMPACTS & COSTS OF LANDSLIDES Landslides, unlike many hazards, are events for which various techniques exist for their detection and control. In addition, the driving mechanisms of a landslide are generally well understood. Despite this, neither is a standard quantitative method for determining the factors causing landslides, nor a system to analyze slopes on a regional basis, in place. The major problem in estimating a slope’s stability is that testing and monitoring of the ground’s physical parameters are time and labour intensive.
Current regional landslide hazard mitigation studies are mostly qualitative, and lack vital engineering information. Also, the majority of slope stability studies where engineering analysis are performed are highly localized, for slopes which have already been identified as worthy of further analysis. Current engineering procedures for determining risk require field sampling and laboratory testing of the engineering properties of the earth materials, and the time and resources involved in implementing monitoring systems for slopes are in most cases cost-prohibitive. Remote sensing imagery is being used for landslide hazard studies, but mostly on a qualitative basis.
Recently, techniques have been developed to calculate the engineering properties of soils with remote sensing images, which can be used for a more reliable quantitative approach for slope failure studies. These techniques, when applied, can lead to area-wide satellite monitoring of natural hillsides, cuts, and embankments, and for more localized analysis be used to assist in field testing or in- situ monitoring of the engineering parameters of the soil which drive slope failure. Traditional techniques for landslide hazard analysis and slope monitoring are used extensively throughout the world. However, implementing current techniques still requires material testing, which is labour-intensive and time consuming.
This leads to problems for any areas that have any level of development, since a landslide, which can easily be averted, does have severe costs attached. The most obvious is property destruction and possibly severe injury or loss of life, such as a property where a dwelling or place of business exists upon, or adjacent to, a slope. While most individual landslides cause few, if any, injuries or fatalities, the total combined losses worldwide account for one fourth of all fatalities due to natural hazards (Hansen, 1984). An exceptional example is the Vaiont Dam in the Italian Tyrol, where in 1963 a landslide rapidly displaced 312 million cubic yards of water from a reservoir, breaching what at the time was the world’s second highest dam and resulting in a flash flood which killed about 3000 people downstream from the slide (Kiersch, 1964).
Similarly, very large landslides occurring in shallower waters along sea sides and lakesides are known to generate tsunamis. This is especially common in more remote Pacific coastal areas of British Columbia and Alaska, an example being the 1958 Lituya Bay event in Alaska, where a landslide suddenly displaced 40 million cubic yards of water, generating a wave which broke on the shoreline with a height of 1720 feet, the highest wave ever measured (Pararas-Carayannis, 1999). Much of the steep shoreline along these areas is adjacent to shallower fjords, which are somewhat contained by larger islands which ring the coast. When a landslide deposits a large amount of material into one of these fjords, the kinetic energy of the sliding earth mass is not entirely absorbed by the shallow water.
Therefore, as this energy is transferred into the water displaced by the earth material, a large wave emerges, which is then channeled down through the fjord, sometimes leading to rapid flooding of any surrounding shoreline settlements. Such an event occurred in Dyea, Alaska, in 2002 (Associated Press, 24 July 2002).