1. Characterizing Slope Stability of Colluvial Soils in Ohio
Using LiDAR Data
A Ph.D. Dissertation Proposal
Matthew Waugh
Department of Geology
Kent State University
Advisor: Dr. Abdul Shakoor

2. Statement of Problem
Slope instability in colluvial soils has been a recurring problem along roadways
throughout the state of Ohio (Figures 1a, 1b, 1c). Colluvial soils are those soils formed from the
weathering or deterioration of the underlying bedrock, and the weathered soil material
accumulates at a rate comparable to the rate of weathering. For this reason, the composition of a
colluvial soil is dependent upon the composition of the underlying bedrock, and the thickness of
a colluvial soil layer is a reflection of bedrock durability, i.e. its resistance to weathering, the
type of weathering process, and slope angle. Shale-derived and claystone/mudstone-derived
colluvial soils are encountered frequently in nature, since shales and claystones/mudstones are
relatively low-durability rocks that weather at much higher rates than more durable rocks, such
as sandstones and limestones. Claystones have the lowest average slake durability values and
shales have the highest slake durability values, with mudstone durabilities falling in the
intermediate ranges (Dick, 1992). The mineral composition of colluvial soils dictates the values
of the shear strength parameters of cohesion and friction angle, which are critical considerations
when analyzing the stability of slopes upon which colluvial soils have accumulated.
Skempton (1964) first proposed that the shear strength values of normally-consolidated
clays approach the drained residual strength of the soil due to the possible pre-existing presence
of shear planes in a slope. The drained residual strength state represents a total loss of the
cohesion component and a significant decrease in the frictional component which could be as
much as one-half of the peak value. The decrease in post-peak drained shear strength is caused
entirely by the reorientation of platy clay minerals parallel to the direction of shearing
(Skempton, 1985). Therefore, the fraction of clay minerals present within the soil dictates the
behavior of the soil with respect to drop in shear strength values. For clay fractions below 20%,

3. the shear strength of the soil is controlled by the sand and silt size particles. Soils with platy clay
minerals and clay fractions of 20-25% or higher have been shown to experience the effects of
clay mineral realignment, which reduces the shearing resistance. Furthermore, for soils with
clay-size fractions of 50% or more, the clay mineralogy becomes very significant, since the
residual shear strength is owed entirely to the internal friction of the clay particles, which is
reliant upon their character (Skempton, 1985).
Numerous investigators have conducted research that supports Skempton’s conclusions
with regards to reduced post-peak shear strength values in slopes with varying clay content and
fraction. Table 1 summarizes some of the recent research that has been conducted on colluvial
soils. The difference in peak and residual cohesion and friction angle values is outlined in the
table, and the values fully support Skempton’s research. With the exception of the research
conducted by Haneberg etal (2009), the cohesion component of the calculated shear strength is
negligible. It is important to note that laboratory investigations were not conducted in
Haneberg’s study, and the values for cohesion and friction angle were assumed, and therefore
quite different from the other tabulated research. In each study, the residual friction angle was
found to be significantly lower than the peak friction angle, or natural angle of repose for
colluvial soils, which Campbell (1975) has established to be approximately 34 degrees.
Laboratory investigations conducted by Kaya etal (2007) and Maurenbrecher etal (1975) found
that the friction angle experienced a post-peak drop of approximately 50%, again concurring
with Skempton’s work.
The plasticity index (PI) for a majority of these investigations ranges from 30 to 45, and
this value represents the difference between the liquid limit (LL) and the plastic limit (PL). The
plasticity index is an indicator of the amount of clay content present in the colluvial soil, as well

4. as potential problems associated with low shear strength of the soil. The clay fractions for the
colluvial soils listed in Table 1 fall entirely in the range of 25% or higher, and as Skempton
concluded, this would indicate that each of these soils is susceptible to clay particle reorientation
and the associated reduction in shear strength.
Table 1. Summary of recent research findings of colluvial soil geotechnical parameters from
various study areas.
Recent research has been done on the slope stability of colluvial soils along roadways in
Ohio, especially in areas that have prominent beds of mudrocks (Wu et al., 1981 and Wu, 1977
and Shakoor and Smithmyer, 2005). These studies did not differentiate between slope stability
problems in shale-derived colluvial soils versus claystone/mudstone-derived colluvial soils.
Rotational and translational landslides and flows are the common mechanisms of slope failure in
this region of the state (Admassu, 2010). Figure 1 shows examples of typical slope movements
that occur in shale-derived and claystone/mudstone-derived colluvial soils.
Study area
Liquid
Limit
(%)
Plastic
Limit
(%)
Clay-size
fraction
(%)
Clay
Mineralogy
Estimated
peak c
(kPa)
Estimated
residual c
(kPa)
Estimated
peak φ°
Estimated
residual φ°
Reference
Irbid-Amman Hwy, Jordan 58 27 49 - - 0 34 25 Al-Homoud et al. (1997)
Seattle, Washington - - - - 4 - 33.6 - Godt et al. (2008)
McMechen, West Virginia 0 0 27 18 Gray et al. (1977)
Cincinnati, Ohio - - 62 illite - 0 34 22 Haneberg (1991)
San Francisco, California - - - - - 19 34 30 Haneberg et al. (2009)
island of Oahu, Hawaii 86 39 59 amorphous* 21 0.5 21 12 Kaya et al. (2007)
Northern Apennines, Italy 55 21 42
smectite &
vermiculite
0.1 0 30 22 Meisina et al. (2007)
Natal, South Africa 57 24 52 illite & mica 14 0 24 11 Maurenbrecher et al. (1975)
I-77 southeastern Ohio 31 26 32
kaolinite &
illite
7.7 2.7 34 28.1 Shakoor et al. (2005)
*contains alumina-silicates, iron and aluminum oxides, and silica

5. (a)
(b)
(c)
Figure 1. Typical slope movement that occurs in colluvial soils in Ohio: (a) Shallow
translational slide in colluvial soil along I-77 (from Shakoor and Smithmyer, 2005); (b)
Rotational slide along SR-666 showing head scarp (left) and toe bulge (right) (Waugh); (c)
mudflow within a shale-derived colluvial soil (from Admassu, 2010).

6. The shales and claystones/mudstones found along roadcuts throughout Ohio weather by
different processes. Claystones and mudstones deteriorate into a finer, soil-like material and
accumulate directly on the slope, with little or no initial movement downslope. Shales ravel into
smaller pieces and gravity carries the pieces downslope where they settle near the toe, or some of
the weathered material stays on the slope as a thin layer of colluvial soil. For this reason,
colluvial soils that develop atop claystones/mudstones, especially along highway cuts, are thicker
than colluvial soil layers atop shales. Additionally, roadcut slopes in claystones/mudstones are
cut at gentler angles (20º to 45º) than slopes cut in shales (45º to 60º), further increasing the
likelihood of claystone/mudstone-derived colluvial soil accumulating on the slope face instead of
at the toe, where shale-derived colluvial soils build up.
Claystones and mudstones have a relatively low durability compared to shales, and
claystone/mudstone-derived colluvial soil has higher clay content. Furthermore, the presence of
clay in the colluvial soil decreases the relative permeability, which results in higher pore
pressures present within the slope. Additionally, erosion by gulleying is prominent in
claystone/mudstone-derived colluvial soils, while gulleying is not prominent within the slope
face of shale-derived colluvial soils (Figures 2a, 2b).
(a)

7. (b)
Figure 2. Typical slope erosion that occurs in colluvial soils in Ohio: a) claystone/mudstone-
derived colluvial soil with gulleying erosion; b) shale-derived colluvial soil showing raveling
(from Admassu, 2010).
Table 2 compares roadcut slopes in shales versus claystones/mudstones that are found
along Ohio roadways, indicating that different types of slope failure may be related to shale-
derived and claystone/mudstone-derived soils. Rotational slides typically occur in thicker layers
of soil, while translational slides generally occur in relatively thinner layers of soil. Therefore,
shale-derived colluvial soils would typically undergo translational failure, while
claystone/mudstone-derived colluvial soils usually exhibit rotational failure. Flows are also
common, especially in claystone-derived colluvial soils (Figure 1c).

8. Table 2. Comparison of slopes comprised of shale-derived and claystone/mudstone-derived
colluvial soils
Figure 3 displays the prominent features of both translational and rotational slides
described by Cruden and Varnes (1996). Mapping of these features in the field is a very
laborious and time consuming undertaking. The application of Light Detection And Ranging
(LiDAR) imagery (Appendix A) has greatly increased the efficiency with which researchers can
identify and map landslides in the field. LiDAR imagery can eliminate vegetation and tree cover
from the equation, and produce high-quality, high-resolution digital elevation models (DEMs).
These DEMs can be used to quickly identify landslides of all natures, including small-scale
rotational and translational slides as displayed in Figure 3, to more complex, multiple-episode
slides, as pictured in Figure 4.
1. Steeper roadcut slopes (45º - 60º) 1. Gentler roadcut slopes (20º - 45º)
2. Higher durability bedrock 2. Lower durability bedrock
3. Weathering process is raveling
3. Weathering process is deterioration into
soil-like material
4. Material tends to accumulate at toe area
(typically a thin cover of colluvial soil)
4. Material tends to accumulate on slope face
(typically a thick cover of colluvial soil)
5. Soil is silty in nature 5. Soil is clayey in nature
6. Failure typically translational in nature 6. Failure typically rotational in nature
7. Lower pore pressure within the slope
(relatively higher permeability)
7. Higher pore pressure within the slope
(relatively lower permeability)
8. Gulley erosion not prominent in slope 8. Gulley erosion prominent in slope
Shale Slopes Claystone/Mudstone Slopes

9. (a) (c)
(b) (d)
Figure 3. Slope movement in a rotational slide (a) and (b) versus a translational slide (c) and (d)
Figure 4. Block diagram of idealized complex earth slide-earth flow (from Varnes, 1978)
An example of a LiDAR-generated DEM, overlain with shaded-relief and contour line
map layers, is shown in Figure 5. The bold line running through the center of the figures

10. represents SR-666 in Muskingum County, Ohio. Through the use of shading and contour lines,
the features associated with a rotational landslide can be seen in the imagery. The rotational
slide encroaching upon the road near mile marker 4 (red dot) is pictured in Figure 1b.
(a) (b)
Figure 5. LiDAR-derived DEM with shaded relief and contouring to identify steepened contours
(head scarp), hummocky topography (zone of sliding), and zone of accumulation (toe bulge). (a)
DEM showing mile marker 4.0 along SR-666 in Muskingum County, Ohio; (b) DEM with
polygons indicating failure areas.
Differences in the slope stability of shale-derived versus claystone/mudstone-derived
colluvial soils have not been investigated in detail, nor are there any studies pertaining to the
application of LiDAR imagery in evaluating these differences. Hence, there is a need to fill this
gap in slope stability-related research.
I plan to utilize LiDAR in two aspects of my research:
1. During the site selection process, I will evaluate slope geometry and modes of
slope failures present at approximately 25 study sites selected through a
combination of the ODOT GHMS database and field observations of those sites.

11. 2. During the data analysis phase, I will utilize the LiDAR imagery to evaluate its
efficiency in characterizing the nature of the colluvial soils, as well as the modes
of failure within the soil slopes.
I will incorporate LiDAR data and GIS techniques to identify the landslide features
displayed in Figure 3 and Figure 4, and additionally to identify slope geometries that may be
consistent with steeper slopes in shale-derived colluvial soils and gentler slopes in
claystone/mudstone-derived colluvial soils.
Research Hypothesis
The hypothesis of the proposed research is that the character of shale-derived and
claystone/mudstone-derived colluvial soils may be a significant indicator of the types of
instabilities that occur within colluvial soil slopes, and LiDAR imagery may be an effective tool
in evaluating the differences in roadcut slopes composed of these two types of colluvial soils.
Objectives
Objectives of this research are as follows:
1. To investigate the differences in the character of colluvial soils developing over shale
bedrock vs. claystone/mudstone bedrock.
2. To investigate the differences in the modes of slope failure in shale-derived colluvial soil
and claystone/mudstone-derived colluvial soil.
3. To evaluate the usefulness of LiDAR imagery, in association with GIS software, in
distinguishing between the characteristics of shale-derived and claystone/mudstone-

12. derived colluvial soils and the corresponding modes of slope failure affecting these two
types of colluvial soil.
Methodology
The research proposed herein will proceed in three phases: (1) field investigations; (2)
laboratory investigations; and (3) data analysis and interpretation.
1. Field investigations
The field investigation phase of my proposed research will include site selection,
identification of the types of slope movement, establishing stratigraphic cross-sections,
determination of slope geometry, and soil and rock sampling.
• Site selection – approximately 12 specific sites along Ohio road cuts will be used for this
study. Approximately half of these sites will have shale as the predominant bedrock underlying
the colluvial soil, and the other half will have claystone and mudstone as the bedrock underlying
the colluvial soil. Sites that have thin, alternating bedrock sequences within the slope will not be
considered for this research. Four specific areas within Ohio will be targeted for site selection:
o State Road 666 in Muskingum County (current research site of ODOT funded
LiDAR project, with OSU as the principle investigator). This state road runs
north/south along the Muskingum River, connecting Zanesville in the south to
Dresden in the north. Along certain sections of this 15-mile road, the natural
slope geometry is quite steep on the upslope, and the downslope is being undercut
by the river. I will attempt to obtain stratigraphic columns or borehole data from
this site. At least 3 of the suitable sites are expected to come from this road cut.

13. o Cincinnati area, especially colluvial soil overlying the Kope formation (mostly
claystones and mudstones). Approximately 3 suitable sites are expected to be
selected from this area.
o Interstate 77 through the southern part of Ohio. I-77 has numerous road cuts in
the southern part of Ohio with thick layers claystones and mudstones-derived
colluvial soils. I expect to select 3 sites in this area.
o State Road 7 in the southeastern part of Ohio. SR 7 along the Ohio River has
numerous road cuts containing relatively thick units of both shale and
claystone/mudstone-derived colluvial soil. I anticipate selecting a minimum of 3
suitable sites along this stretch of highway containing shale-derived and
claystone/mudstone-derived colluvial soils.
In addition to these four areas, I will explore other areas within Ohio for selection of
suitable sites. I will utilize the ODOT Geological Hazard Management System (GHMS)
database to identify landslide study sites that meet the following criteria: 1) site is south of the
glacial margin; 2) site has a preliminary hazard rating of 3 or higher (scale of 1 to 16); 3) site is a
natural slope or a cut slope, not an embankment; and 4) the slope material is classified as either
colluvium or weathered rock. The ODOT GHMS database, located at
http://130.101.12.31/ghmsserver/, is equipped with a GIS application that enables the user to
both identify areas of high landslide concentration and to filter landslide sites by attribute,
location, feature buffer or point buffer. Once a subset of landslide sites is identified, the user can
gather detailed information on each landslide by utilizing the GHMS’s Data Management
application. This information can include, but is not limited to, the preliminary hazard rating, site
location data, basic slope characteristics, maintenance information, landslide characteristics,

14. detailed slope information, and hydrological information. I will prepare a list of 125 to 150
preliminary sites that meet the previously noted criteria, and I will travel to each site to
photograph the landslide features and record field notes. Upon completion of the field work, I
will narrow the list to approximately 20 to 25 landslide study sites with assistance from my
advisor.
During the final phase of site selection, I will obtain the LiDAR LAS data files provided
by the Ohio Statewide Imagery Program (OSIP), for each potential study site. The websites that
host this imagery can be found at http://gis3.oit.ohio.gov/geodata or http://lidar.cr.usgs.gov/. The
Ohio state-funded website contains LiDAR data with resolution that is accurate within plus or
minus 1 foot in most terrain. Subsequent field-survey checks have yielded results of two to
three-tenths of a foot vertical accuracy. I will evaluate the LiDAR data from each source in
terms of resolution for each study site in order to obtain the highest resolution data currently
available. I will also note the dates of the flights from which the LiDAR imagery was obtained,
and I will utilize those LiDAR datasets that were flown during leaf-off seasons, as recommended
by Burns, Coe, Kaya and Ma (2010). I will be using LiDAR imagery provided by ODOT for the
State Route 666 site, as I am currently part of a Kent State University team that is contributing to
an ODOT-funded research grant that was awarded to Ohio State on the use of LiDAR imagery to
create a computer model for the detection of landslides. Based on an examination of digital
elevation models (DEMs) produced from LiDAR data for these sites, I will select approximately
12 sites that best meet the objectives of this proposed research.
• Identification of the types of slope movement
o For each of the selected sites, I will investigate the types of slope movements
affecting the colluvial soil. Colluvial soils can be affected by two basic types of

15. slope movement: rotational and translational slides (see Figure 3). I will
investigate which sites have a greater frequency of rotational slides or
translational slides and whether these modes of failure are related to the type of
colluvial soil. The observations will be documented as field notes and pictorial
record.
• Establishing the stratigraphic cross-section
o For each selected site, I will develop a stratigraphic cross-section based on the
available information, field observations, and any drilling records (if available
from Ohio Department of Transportation, Ohio Department of Natural Resources,
etc.)
• Slope geometry
o I will measure the length, height, slope angle and slope aspect (dip) for each of
the selected sites. The slope angle is directly related to bedrock geology. ODOT
constructs steeper slopes in shale bedrock than in claystones/mudstones. Multiple
locations across the slope will be used for these measurements and average values
of these parameters will be used. Information about slope geometry will be
related to the nature of colluvial soil (e.g., particle size distribution) and the soil
thickness. I expect to find thicker cover of colluvial soil over gentler slopes
consisting of claystones and mudstones, and thinner cover of colluvial soil over
steeper slopes consisting of shale bedrock. Additionally, slope aspect can
influence the amount of moisture available and thereby the nature of weathering
(raveling of shale, deterioration of claystones/mudstones).

16. • Sampling
o I plan to collect a minimum of three samples of colluvial soil, each weighing 25
pounds (~10kg). Every effort will be made to insure that the collected samples
are representative of the lateral and vertical variability of the conditions within
each site. Additionally, sufficient samples (minimum of 3 per site) of the
underlying bedrock will be collected for lab preparation and tests. These samples
will be based upon the stratigraphic cross-sections for each site, locating the
weaker, more weatherable rock layers.
o To preserve the natural water content and prevent further disintegration, the soil
and bedrock samples will be wrapped in plastic bags and stored in 5-gallon
buckets, covered with lids. These and all additional guidelines set forth by ASTM
standards D5079 (rock) and D4220 (soil) for the preservation and transportation
of rock and soil will be followed.
2. Laboratory investigations
I will conduct the following laboratory tests on collected samples of colluvial soils and
the corresponding bedrock, according to ASTM test specifications:
• Laboratory tests on colluvial soil
o Natural water content (ASTM D2216) – This test will provide information about
the void ratio/porosity of the soils, as well as the type of clay minerals present
within the soils. I expect a higher presence of clay minerals in the colluvial soils
that have weathered from claystones and mud stones relative to the shale-derived
soils.

17. o Atterberg Limits – The Atterberg limits (ASTM D4318) test will include the
determination of liquid limit, plastic limit and plasticity index of the colluvial soil
samples collected. The Atterberg limits represent levels of water content where
the soil behavior changes. The liquid limit (LL) represents the water content
above which soils will behave as a viscous liquid. The plastic limit (PL) indicates
the water content below which a soil will behave as a brittle material. The
plasticity index, PI, represents the range of water content in which the soil will
behave plastically (i.e., not as a brittle material or viscous liquid). The higher the
plasticity index, the higher the clay content of the soil (Holtz and Kovacs, 1981).
The plasticity index is also an indicator of potential problems with low shear
strength (Deere and Gamble, 1971). I expect the plasticity index to be higher for
claystone/mudstone-derived colluvial soil than shale-derived colluvial soil, and
therefore be more susceptible to slope instability.
o Grain Size Distribution (ASTM D422) – A sieve analysis for material coarser
than #200 sieve and hydrometer analysis for material passing #200 sieve will be
performed to classify the colluvial soils in terms of the Unified Soil Classification
System (USCS). In place of hydrometer analysis, I may possibly use the particle
sizer in Dr. Ortiz’s lab, which is a very rapid method of determining GSD of the
finer material. I expect the particle sizes to be finer for the claystone/mudstone-
derived soil than the shale-derived soil.
o Direct Shear test (ASTM D3080) – This test will be performed to determine the
shear strength parameters of the colluvial soils to determine the values of
cohesion and friction angle. Claystone/mudstone soils are expected to be more

18. cohesive in nature than shale-derived soils. To simulate shear along soil-soil
contacts as well as soil-bedrock contacts, two types of direct shear test will be
conducted, with soil being placed in both halves of the apparatus for one test, and
rock and soil being placed in opposite halves for the second test. The strength
parameters will be used to perform stability analysis for selected, well-developed
translational and rotational slides that have failure planes entirely within the soil,
and also failure planes that occur along the soil and bedrock interface.
• Laboratory tests on bedrock
o Slake durability test (ASTM D4644) will indicate the resistance of the shales and
claystones/mudstones to weathering from drying and wetting cycles. Although
durability of shales and claystones/mudstones is at the lower end of the spectrum
compared to other rocks, I do expect the durability of the claystones and
mudstones to be slightly lower compared to the durability of shales (Dick, 1992).
o X-ray diffraction analysis (XRD) – the bedrock samples will be disintegrated to a
soil-like material by subjecting them to multiple cycles of wetting and drying until
enough fine-grained material is available for XRD analysis. The purpose of the
XRD analysis is to investigate how clay mineralogy of the original bedrock
influences the character of the weathered material, i.e. the colluvial soil,
especially the elasticity characteristics. The determination of the Plasticity Index
will be an important procedure in this evaluation.
3. Data analysis and interpretation
I will perform the following data analysis and provide interpretation of the results:

19. o All field and laboratory data including slope geometry measurements,
stratigraphic information, types of slope failure, and laboratory test results will be
presented in the form of graphs, figures, tables, cross-sections and photographs.
o Shale-derived and claystone/mudstone-derived colluvial soils will be
characterized:
In terms of their mode of formation, i.e. either raveling or deterioration
In terms of their thickness above the underlying bedrock
In terms of their engineering properties, including:
• natural water content
• Atterberg limits
• grain size distribution
• shear strength parameters
• hydrologic conditions
• erosional features
These differences will be tabulated and interpreted in light of slope geometry,
bedrock type, and the bedrock engineering properties. I will determine the
average values of these variables and perform ANOVA tests to determine if a
significant difference exists for these two colluvial soil types.
o Stability analysis for well-developed rotational and translational landslides
observed in the field, using the following techniques:
Infinite slope analysis method for translational landslides (Duncan, 1996)
STABL4 software analysis for rotational landslides

20. Significance of Research
The research proposed herein will be a novel approach to investigating the differences in
the character of shale-derived versus claystone/mudstone-derived colluvial soils with respect to
slope stability considerations.
The use of LiDAR imagery in distinguishing the differences between these two types of
colluvial soil will also make a new and important contribution.
To the best of my knowledge, the type of research proposed herein has not been
conducted previously in the state of Ohio.
Acknowledgements
I would like to thank Mr. Kirk Beach of the Ohio Department of Transportation for
granting permission to utilize the Geological Hazard Management System database.
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25. Research Schedule
My research will begin in the summer of 2012 with the compilation of LiDAR imagery
and historical data (borehole logs, geologic maps, stratigraphic information) required for the
proper selection of suitable sites. Site selection is scheduled to be complete by late summer. I
will begin my field work during the fall of 2012. By the end of the fall semester of 2012, my
field work will be complete and I expect to begin my laboratory investigations on collected
colluvial soil and bedrock samples. I expect to begin writing my dissertation during the winter
of 2012. In the spring of 2013, I will perform any follow up visits to the study sites, if necessary.
I plan to finish my dissertation during the fall semester of 2013, with anticipated graduation in
December of 2013.

26. Appendix A
Light Detection And Ranging (LiDAR) has also been referred to as laser altimetry,
airborne laser scanning, airborne laser swath mapping. LiDAR data is obtained by an airplane
equipped with a LiDAR scanner flying above the study area, bouncing laser beams off of the
earth’s surface and collecting the reflected beams, thus providing a high-resolution
representation of the topography. The resolution of the LiDAR imagery is a result of the flight
altitude of the airplane. Low resolution LiDAR imagery is captured from altitudes of 2000 or
more meters (6600+ feet), while standard resolution LiDAR imagery requires flight altitudes of
about 1400 meters (~4600 feet), and high resolution LiDAR imagery must be taken at altitudes
of 900 meters or less (<3000 feet).
The LiDAR data collected by the scanner (mounted to the airplane) consists of a massive
number of individual points of elevation. Typical point spacing is 1.0 meter (~3.3 feet) for high
resolution LiDAR data, 1.4 meters (~4.6 feet) for standard resolution LiDAR data, and 1.8
meters (~6 feet) for low resolution LiDAR data. This point data can then be imported into GIS
software to develop a digital elevation model of the earth’s surface, whose boundary is defined
by the LiDAR scanner’s swath or scope. The higher the resolution of the LiDAR point data, the
more accurate the representation of the earth’s surface and topography. The GIS-created DEM
derived from the LiDAR point data converts the point file into a shape file through interpolation.
The shape file can then be used to create additional helpful GIS layers, such as contour lines,
hillslope maps, shaded relief maps, and statistical analysis maps. A multi-layer analysis in GIS
using different combinations of map layers can reveal areas of geologic interest, including slope
movements and landslide features. For example, rotational landslides exhibit features in the
DEM and accompanying map layers that are discernible to the trained eye, such as a steepened

27. head scarp, hummocky topography, and a well-defined toe bulge. Figure 5 illustrates how these
landslide features appear in a LiDAR-based DEM.
Figure 5. LiDAR-derived DEM with shaded relief and contouring to identify steepened contours
(head scarp), hummocky topography (zone of sliding), and zone of accumulation (toe bulge)
LiDAR-based mapping and assessment of landslides has become a very useful tool for
geologists worldwide within the past 10 to 12 years. In recent years, LiDAR incorporated
research with respect to landslides has been conducted by:
• Roering and others (2005) and Drazba and others (2006) in Oregon
• Schulz (2006) and Troost and others (2006) in the state of Washington
• Falls and others (2004) in northern California
• Glenn and others (2005) in Idaho
• Wooten and others (2007) in North Carolina
• Delano and Braun (2007) in Pennsylvania
• Haneberg and others in southern California (2009) and Papua New Guinea (2005)
• Van Den Eeckhaut and others (2006) in Belgium
• Ventura and others (2010) in southern Italy