Landslide mapping and susceptibility modeling in Wrangell Island, Alaska

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What does this data set describe?

Title:
Landslide mapping and susceptibility modeling in Wrangell Island, Alaska
Abstract:
Landslide mapping and susceptibility modeling in Wrangell Island, Alaska, Report of Investigation 2026-2, provides a regional assessment of landslide hazards on Wrangell Island, Alaska, following the fatal 2023 Zimovia Highway landslide, which underscored the safety and financial risks that slope failures pose to people and infrastructure. To support the City and Borough of Wrangell resilience to landslide hazards, the Alaska Division of Geological and Geophysical Surveys (DGGS) expanded an existing landslide inventory and modeled shallow landslide susceptibility and potential debris flow inundation. DGGS integrated previously mapped Tongass National Forest landslides with newly identified slope failures; more than 90 percent of all inventoried features are classified as debris flows. Shallow landslide susceptibility was evaluated using frequency ratio analysis that compared inventoried landslides with terrain factors influencing slope failure. The highest susceptibility is associated with slopes steeper than 31 degrees, southwest- to west-facing aspects, proximity to drainages, and colluvial soils. Model performance was strong, with an area-under-curve value of 0.88. DGGS also modeled the initiation and downslope movement of channelized debris flows and their inundation extents for relatively common events occurring every few years to decades, as well as rare events with recurrence intervals of roughly 1,000 years. Collectively, these analyses provide a regional framework for understanding landslide hazards on Wrangell Island and can inform future land-use planning, development, and scientific investigations. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website http://doi.org/10.14509/32057.
Supplemental_Information:
DGGS completed this landslide hazard assessment for the City and Borough of Wrangell by developing a landslide inventory and database, a map of modeled shallow landslide susceptibility, and a map of modeled channelized debris flow initiation and runout. Together these products provide a regional assessment of slope failure hazards that can support community planning, emergency preparedness, and the identification of areas where more detailed investigations may be warranted. The maps identify areas that are relatively more susceptible to slope failure but do not predict the timing, probability, or recurrence intervals of future landslides. Site‑specific geologic and geotechnical investigations should be completed prior to development in potentially hazard prone areas. The results presented herein are for informational purposes only and are not suitable for legal, engineering, or surveying uses. DGGS is not a regulatory agency; therefore, this report and maps are non‑regulatory. 
wrangell_landslide_susceptibility_db:    Landslide inventory geodatabase and accompanying data dictionary, includes raster data file depicting slopes susceptible to shallow landslides.
  1. How might this data set be cited?
    Nicolazzo, J.A., 2026, Landslide mapping and susceptibility modeling in Wrangell Island, Alaska: Report of Investigation RI 2026-2, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 27 p., 3 sheets, scale 1:25,000
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -132.395763
    East_Bounding_Coordinate: -131.920505
    North_Bounding_Coordinate: 56.489379
    South_Bounding_Coordinate: 56.116687
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2026
    Currentness_Reference:
    publication date
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a vector data set.
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 8
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -135
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000.000000
      False_Northing: 0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest .00000001
      Ordinates (y-coordinates) are specified to the nearest .00000001
      Planar coordinates are specified in Meters
      The horizontal datum used is NAD83 (2011).
      The ellipsoid used is GRS 80.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257222101.
  7. How does the data set describe geographic features?
    ri2026-2_wrangell_landslide_susceptibility_db.gdb, ri2026-2_wrangell_landslide_susceptibility_db_data_dictionary.xlsx
    Landslide inventory geodatabase and accompanying data dictionary, includes raster data file depicting slopes susceptible to shallow landslides. (Source: DGGS)
    landslide_points
    Points match polygons (Source: this report, DGGS staff) File Geodatabase Feature Class
    deposit_polygons
    Polygons tracing deposit extents, or the scar extents of a paleolandslide (Source: this report, DGGS staff) File Geodatabase Feature Class
    flank_polygons
    Polygons tracing landslide flanks (Source: this report, DGGS staff) File Geodatabase Feature Class
    scarp_polylines
    Polylines tracing scarps (Source: this report, DGGS staff) File Geodatabase Feature Class
    transport
    Polylines representing the transport path for a debris flow (Source: this report, DGGS staff) File Geodatabase Feature Class
    watershed
    Polygons representing the watershed contributing to each potential debris flow (Source: this report, DGGS staff) File Geodatabase Feature Class
    inundation_typical
    Polygons representing debris flow inundation/deposition extents modeled for a "typical" event (Source: this report, DGGS staff) File Geodatabase Feature Class
    inundation_extreme
    Polygons representing debris flow inundation/deposition extents, modeled for an "extreme" event (Source: this report, DGGS staff) File Geodatabase Feature Class
    shallow_susceptibility
    Raster image depicting slopes susceptible to shallow landslides; pixel values indicate risk classification: 1 = very low/none, 2 = low, 3 = moderate, 4 = high, 5 = very high (Source: this report, DGGS staff) File Geodatabase Raster Dataset

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
  2. Who also contributed to the data set?
    This work was funded by the Federal Emergency Management Agency (FEMA) Cooperative Technical Partnership (CTP) Program grant number EMS-2024-CA-05006. We thank Katreen Wikstrom Jones and our other reviewers for their expertise and thoughtful comments that helped improve the quality of this product.
  3. To whom should users address questions about the data?
    Alaska Division of Geological & Geophysical Surveys
    GIS Manager
    3354 College Rd
    Fairbanks, AK
    USA

    907-451-5020 (voice)
    dggsgis@alaska.gov
    Hours_of_Service: 8 am to 4:30 pm, Monday through Friday, except State holidays

Why was the data set created?

The purpose of this report is to assess landslide hazards on Wrangell Island by expanding the landslide inventory, modeling shallow landslide susceptibility, and estimating debris-flow inundation extents. The work supports community resilience by identifying terrain conditions associated with high susceptibility and by providing regional hazard information to guide land-use planning and future investigations.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 2025 (process 1 of 3)
    Geodatabase deployment - DGGS compiled geologic and surficial soils information by incorporating 1:63,360-scale geologic maps of the Petersburg B-1 and B-2 quadrangles, a 1:150,000-scale regional compilation, a 1:7,200-scale surficial soils map of the Wrangell area, USDA STATGO2 soils data, and U.S. Fish & Wildlife Service wetlands data. DGGS incorporated the U.S. Forest Service Tongass National Forest landslide inventory, excluding snow avalanches, and used it to calibrate identification of additional slope failures. DGGS integrated slope failures identified by others and compared two lidar datasets collected in July and November 2023. Following published landslide mapping protocols, DGGS used ArcGIS Pro to create feature classes for deposit polygons, flank polygons, scarp polylines, and landslide initiation points. DGGS interpreted hillshade and slope rasters derived from lidar-based digital terrain models, supplemented by aerial imagery from Maxar, Esri Wayback, and Google Earth, to identify additional slope failures throughout the project period. DGGS mapped landslide components where visible, inferred initiation points where necessary, and included scarp polylines for unstable bedrock areas. These steps produced the landslide inventory geodatabase used in subsequent susceptibility modeling and debris-flow analysis.
    Date: 2025 (process 2 of 3)
    Shallow-landslide susceptibility model - DGGS modeled shallow-landslide susceptibility by compiling terrain and environmental variables and evaluating their relationships to inventoried landslides using frequency ratio methods. DGGS derived slope angle, slope aspect, curvature, and topographic wetness index rasters from lidar-based digital terrain models and calculated distances to drainages and roads. DGGS incorporated geologic mapping to represent material conditions. DGGS binned each conditioning factor, computed frequency ratio values for each bin, and combined the results to produce a susceptibility surface. DGGS evaluated model performance using area-under-curve analysis.
    Date: 2025 (process 3 of 3)
    Channelized debris flow inundation model - DGGS modeled channelized debris flow initiation, transport, and inundation using the Laharz-based workflow described by Burns and others (2022). DGGS applied the modified Laharz tools to simulate debris flow initiation from shallow landslides or channel-adjacent erosion, routed modeled flows downslope through drainage channels, and allowed modeled volumes to expand during transport. DGGS delineated watershed susceptibility classes by evaluating initiation and transport potential for each watershed. DGGS generated inundation and deposition extents for multiple modeled event severities to produce debris-flow susceptibility and inundation mapping.
  3. What similar or related data should the user be aware of?
    Hubbard, T.D., Daanen, R.P., and Stevens, D.S.P., 2025, Debris flow hazard evaluations for multi-hazard risk mapping in Sitka, Alaska: Report of Investigation RI 2024-2, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 14 p., 6 sheets, scale 1:20,000
    Nicolazzo, J.A., and Larsen, M.C., 2025, Alaska landslide inventory database: Digital Data Series DDS 23, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 14 p
    Nicolazzo, J.A., Wikstrom Jones, K.M., Salisbury, J.B., and Horen, K.C., 2024, Post-landslide elevation changes detected from multi-temporal lidar surveys of the November 2023 Wrangell, Alaska, landslides: Preliminary Interpretive Report PIR 2024-2, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 22 p
    Zechmann, J.M., Wikstrom Jones, K.M., and Wolken, G.J., 2023, Lidar-derived elevation data for Wrangell Island, Southeast Alaska, collected July 2023: Raw Data File RDF 2023-28 v. 1.1, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 14 p
    Zechmann, J.M., Wikstrom Jones, K.M., and Wolken, G.J., 2024, Lidar-derived elevation data for Wrangell Island, Southeast Alaska, collected November 28-29, 2023: Raw Data File RDF 2024-1, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 9 p

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Mapping for this project is desktop-based and relies on available datasets without field verification, and lidar provides only a snapshot of landscape conditions at the time of acquisition, so map accuracy may decline as new landslides occur, technology improves, or mapping techniques evolve. Some slope failures were likely missed or misinterpreted due to lidar limits, imagery quality, vegetation cover, and the absence of field checks. The shallow-landslide susceptibility model uses post-failure lidar, meaning mapped initiation points may not represent pre-failure conditions, and the frequency ratio method identifies associations rather than causation, assumes conditioning factors are independent, and produces relative likelihood values rather than absolute probabilities. Channelized debris flow modeling is based on estimated growth factors and volumes, so actual flow behavior may differ, and infrastructure, topographic changes, and mitigation measures can alter flow paths. Material differences, such as woody debris, can affect flow behavior and runout, and lidar analysis cannot always distinguish natural elevation changes from man-made structures. For additional discussion of these limitations, see the accompanying report.
  2. How accurate are the geographic locations?
    Horizontal accuracy is controlled primarily by the quality of the lidar point cloud and the georeferencing of source datasets. Lidar provides a consistent regional framework, but its snapshot nature means mapped feature positions may not fully represent pre-failure conditions or areas affected by vegetation, shadowing, or limited point density. Desktop interpretation of lidar and imagery introduces additional uncertainty, and some mapped features may be offset or generalized relative to their actual ground locations. For more detail on horizontal accuracy and related limitations, see the accompanying report.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    The dataset is broadly complete where lidar coverage, imagery, and terrain derivatives adequately capture landscape conditions at the time of acquisition, providing a consistent regional basis for desktop mapping and susceptibility modeling. However, completeness is limited by vegetation cover, imagery quality, lidar resolution, and the absence of field verification, which may result in some slope failures being missed or misinterpreted. Susceptibility relationships derived from frequency ratio analysis reflect statistical associations rather than causation, leaving some interactions among terrain factors unresolved. Debris-flow modeling relies on estimated parameters and does not fully represent real-world variability, infrastructure effects, or material differences, and lidar may not distinguish natural elevation changes from man-made structures. For more detail on data quality and completeness, see the accompanying report.
  5. How consistent are the relationships among the observations, including topology?
    The relationships among the observations are generally consistent at a regional scale, but they are constrained by data quality, lidar interpretations, statistical assumptions, and modeling uncertainties. We used frequency ratio analysis to quantify statistical relationships between landslide occurrence and terrain attributes. Some observed relationships may be incomplete, may not represent pre-failure conditions, or may vary as new data, improved techniques, or additional landslides occur. For additional discussion of these limitations and tests used to determine data quality, see the accompanying report.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints:
This report, map, and/or dataset is available directly from the State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys (see contact information below).
Use_Constraints:
Any hard copies or published datasets utilizing these datasets shall clearly indicate their source. If the user has modified the data in any way, the user is obligated to describe the types of modifications the user has made. The user specifically agrees not to misrepresent these datasets, nor to imply that changes made by the user were approved by the State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys. The State of Alaska makes no express or implied warranties (including warranties for merchantability and fitness) with respect to the character, functions, or capabilities of the electronic data or products or their appropriateness for any user's purposes. In no event will the State of Alaska be liable for any incidental, indirect, special, consequential, or other damages suffered by the user or any other person or entity whether from the use of the electronic services or products or any failure thereof or otherwise. In no event will the State of Alaska's liability to the Requestor or anyone else exceed the fee paid for the electronic service or product.
  1. Who distributes the data set? (Distributor 1 of 1)
    State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys
    3354 College Road
    Fairbanks, AK
    USA

    907-451-5020 (voice)
    907-451-5050 (FAX)
    dggspubs@alaska.gov
    Hours_of_Service: 8 am to 4:30 pm, Monday through Friday, except State holidays
    Contact_Instructions:
    Please view our website (http://www.dggs.alaska.gov) for the latest information on available data. Please contact us using the e-mail address provided above when possible.
  2. What's the catalog number I need to order this data set? RI 2026-2
  3. What legal disclaimers am I supposed to read?
    The State of Alaska makes no express or implied warranties (including warranties of merchantability and fitness) with respect to the character, function, or capabilities of the electronic services or products or their appropriateness for any user's purposes. In no event will the State of Alaska be liable for any incidental, indirect, special, consequential, or other damages suffered by the user or any other person or entity, whether from the use of the electronic services or products, any failure thereof, or otherwise, and in no event will the State of Alaska's liability to the requestor or anyone else exceed the fee paid for the electronic service or product.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 23-Sep-2026
Metadata author:
Simone Montayne
3354 College Road
Fairbanks, AK
USA

907-451-5020 (voice)
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
Metadata extensions used:
Generated by mp version 2.9.50 on Wed Sep 23 16:53:12 2026