Landslide Analysis using Multi-Temporal LiDAR Data

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Landslides (a.k.a. landslips, slumps, or slope failures), shown in Figures 1 and 2, are the movement of rock, debris, or earth down a slope. Landslides occur on every continent, with some regions experiencing more landslides due to specific geologic and hydrologic conditions.

Landslides occurring in the vicinity of gas pipelines can strain and even damage pipelines or cause environmental problems if material migrates into streams, wetlands, or other environmentally-sensitive areas. These integrity and environmental impacts are serious operational issues that can be costly and difficult to remediate. For companies like The Williams Companies, Inc. (Williams), accurately mapping, evaluating, and monitoring landslides near pipeline infrastructure is, therefore, essential for maintaining pipeline and environmental integrity. This is especially true for pipelines located in regions that are highly prone to landslide occurrence.

Williams owns and operates hundreds of miles of pipeline traversing West Virginia, Ohio, and Pennsylvania, which is some of the most highly-susceptible landslide terrain in the conterminous United States, according to the United States Geological Survey (USGS). Landslides in this area are abundant, fluctuate often, and are problematic to track. Williams continually strives to maintain current and accurate systematic information on the type, abundance, distribution, and severity of landslides in this area to keep their assets reliable for customers and safe for the public.

Improved Methodology for Gathering Landslide Information
Historically, Williams has relied on routine aerial and field patrols to obtain systematic landslide information in this region. These methods, however, have limitations. With the expanding and changing West Virginia pipeline network, it has become increasingly difficult for Williams to continually delineate, catalogue, evaluate, and monitor landslides using only these approaches. The recent advent of affordable aerial light detection and ranging (LiDAR) acquisition and high-resolution digital elevation modeling (DEM) has made it readily possible to obtain accurate regional landslide information at a frequency that can match the fast-paced world of pipeline operations. In fact, Williams, in conjunction with Michael Baker International, has successfully utilized LiDAR over the past few years to assess and monitor northern West Virginia landslides, which has ultimately led to improved safety, environmental performance, and asset integrity. This successful methodology includes:
Collecting and constraining LiDAR;
Creating DEMs, topographic contours, and developing hillshades and heat maps;
Using hillshades and heat maps to delineate and analyze landslides along the pipelines; and,
Prioritizing delineated landslides for field assessments and remediation.

LiDAR Collection and Constraining
A fixed-wing aircraft was used to collect airborne LiDAR in 2013, 2015, and 2016 for a 2,200-foot corridor surrounding Williams’ Ohio River Valley gathering pipelines. Due to the evolving nature of Williams’ pipeline system, the successive LiDAR datasets did not entirely overlap; i.e., additional LiDAR was obtained as the years progressed to capture new pipelines installed or acquired over the years. To maintain consistency over the years, similar collection parameters (Table 1) were used during the yearly LiDAR acquisition.

The LiDAR data was constrained to multiple high-accuracy transformation control points (3 cm accuracy or better), which were installed on the ground surface at pre-determined locations across the project area prior to the LiDAR acquisition. Before filtering and classifying the LiDAR for analysis, the data was geometrically corrected against the ground control points to account for potential geocoded LiDAR data errors due to global navigation satellite system (GNSS) errors, inertial measurement unit (IMU) anomalies, or other associated calibration issues. During this process, the ground control was intersected with the triangulated irregular network (TIN) model of the calibrated LiDAR point cloud. Elevation values were checked against one another and the differences were calculated/adjusted to develop useable LiDAR datasets. After the constraining processes were complete, a control point statistical evaluation report (Table 2) was generated each year to evaluate and verify LiDAR accuracy and consistency.

Developing Hillshades and Heat Mapping
After the LiDAR data was collected and constrained, bare-earth DEMs were created (Figure 3) from final classified and hydro-enforced ground points using natural neighbor interpolation methods within Esri, TerraScan, and Global Mapper software. Since the input LiDAR is highly dense and accurate, natural neighbor interpolation methods retained the most detailed and accurate surface characteristics in the output raster. The bare-earth raster DEMs were then used to create topographic contours in Esri ArcGIS (Figure 4). Finished contour lines were smoothed and splined for aesthetic purposes, then subjected to a quality assurance check to investigate for potential production cartographic and topologic errors (e.g., self-intersecting loops, sharp angles in lines, intersecting or crossing contours, etc.).

Hillshade mapping was created using Esri ArcGIS for the entire 2,200-foot wide pipeline corridor (Figure 5). Hillshading is a technique used to visualize terrain as shaded relief illuminated with a hypothetical light source. The illumination light value for each raster cell was determined based on slope, aspect, and orientation to the light source.

Esri ArcGIS was also used to model elevation changes for areas where the 2013, 2015, and 2016 LiDAR datasets overlapped. By comparing pixel elevations of the bare-earth rasters over the different years, heat mapping (Figure 6) was generated to show locations of earth movement from year to year. Varying shades of red and blue were used to depict ground elevation losses and gains, respectively. Darker shades of red and blue corresponded to larger elevation differences measured between the LiDAR datasets.

Landslide Delineation and Analysis
Williams was able to systematically search its West Virginia Pipeline corridors to detect and delineate possible landslides by interchangeably viewing the hillshade and heat mapping at various scales using Esri ArcMap software. The hillshade mapping was used to delineate new landslides in areas where 2013/2015/2016 LiDAR data did not overlap. In areas where 2013/2015/2016 LiDAR data did overlap, the elevation change heat mapping was used to quickly detect new landslides and evaluate existing landslides for new horizontal/vertical movement. Topographic contours were also occasionally draped over the mapping to accentuate the slope geomorphology. The aerial limits of the delineated landslides were digitized and the landslides were labeled for tracking purposes.

After initial delineation, landslides thought to present greater pipeline integrity and environmental impact risks were field-evaluated, and the risk assessment was further refined based on observed landslide severity, surveyed pipe location, stream proximity, etc. The landslides with the highest fieldevaluated risk values were then selected for remediation. The LiDAR contours were also used to further analyze the landslides and develop detailed remedial design plans, which eliminated additional field ground survey costs.

Future Work
Williams plans to obtain aerial LiDAR for its primary gas gathering pipelines in northern West Virginia on a recurring basis to continue to monitor the fluctuating regional landslide conditions, as an important component of its overall program to maintain safe operating conditions. Efforts are also underway to create an interactive spatial landslide susceptibility model in Esri ArcGIS by statistically linking delineated landslide locations to different LiDAR derivatives, such as hydrologic flow direction and accumulation, surface data (e.g., slope, aspect, curvature, etc.), and historical mapped data (e.g., mapped coal seam outcrops, bedrock dips, soil types, ancient landslide locations, etc.). The goal is to generate probabilistic heat mapping that shows the likelihood of a landslide occurring at any given location within the region (Figure 7). This susceptibility model could be used to avoid installing new pipelines in high-risk landslide areas. Landslides could also potentially be prevented by installing mitigation measures (e.g., drains) in targeted high-probability landslide areas.

Landslides occurring in the vicinity of gas pipelines can damage pipelines and impact environmentally-sensitive areas. For pipeline operators, accurately mapping, evaluating, and tracking landslides near pipeline infrastructure is a necessary component of an overall program to maintain safe operating conditions. This is especially true for Williams’ Ohio River Valley pipeline system located in the landslide-prone hills of northern West Virginia. The multi-temporal LiDAR collection and analysis methodology outlined in this article has proven to be highly effective for assessing and monitoring landslides, and particularly useful for focusing reconnaissance and remedial field efforts. Williams’ efforts over the past few years have resulted in fewer impacts to pipelines and the environment, which has also translated into reduced operating expenses and improved reliability.

Dr. Srini Dharmapuri, CP, PMP, GISP is currently with Michael Baker Jr., Inc. in Pittsburgh as LiDAR Scientist. Srini is Baker’s resident LiDAR Scientist, responsible for management and oversight of all LiDAR processing activities involving extraction, algorithm development, quality assurance, and product delivery. Dr. Dharmapuri has Master’s of Science (Physics), Master’s of Technology (Remote Sensing), and Doctorate (Satellite Photogrammetry). Dr. Dharmapuri has over 29 years of extensive, wide-ranging experience within the Geospatial industry; most notably with LiDAR, Photogrammetry, and GIS. He has worked in both the private and public sectors, as well as internationally. In addition to his educational achievements, Dr. Dharmapuri is also an ASPRS Certified Photogrammetrist and licensed Photogrammetric Surveyor in South Carolina and Virginia, as well as a Certified GIS Professional and Project Management Professional. Dr. Dharmapuri is actively involved with ASPRS and currently serves as Chair–Mobile Mapping Standards Committee.

Brian Halchak is a Geotechnical Engineer for The Williams Companies, Inc. who has been with the company since 2014. He has degrees in Civil Engineering and Geomatics Engineering and is currently pursuing a Master’s Degree in Geotechnical Engineering. Mr. Halchak has experience in many facets of geotechnical and civil engineering, and geomatics. This includes preparing landslide remediation designs, Geospatial Information System data processing/analysis, geodesy, and GNSS measurement and processing. Over the past few years Brian has been involved in many operating areas within Williams. He has performed work in Louisiana, Texas, Pennsylvania, and West Virginia functioning in multiple different roles.

Jonathan F. Bell, P.E. has over 11 years of diversified geotechnical engineering experience. During this period, Mr. Bell focused on Marcellus/Utica shale gas-related geotechnical designs for well pads, impoundments, meter stations, processing plants, flare pads, and pipelines; landslide investigation, analysis, and remediation was also an intricate aspect of this geotechnical design work. Over the past two years, Jonathan extensively researched and evaluated pipeline stress and strain related to contiguous ground movement (e.g., landslides, earthquakes, longwall mining, sinkholes, etc.), which has led to Mr. Bell’s involvement with LiDAR analysis, landslide mapping and monitoring, and landslide prediction efforts.

A 4.023Mb PDF of this article as it appeared in the magazine complete with images is available by clicking HERE