Landslide mapping and susceptibility modeling near Cordova, Alaska

Nicolazzo, J.A.2026Landslide mapping and susceptibility modeling near Cordova, AlaskadataReport of InvestigationRI 2026-7Fairbanks, Alaska, United StatesAlaska Division of Geological & Geophysical Surveys15 p., 3 sheets, scale 1:25,000https://doi.org/10.14509/32148Landslide mapping and susceptibility modeling near Cordova, Alaska, Report of Investigation 2026-7, presents a geodatabase of landslide hazard data for approximately 245 km2 (94 mi2) surrounding the City of Cordova, Alaska, where slope failures pose significant risks to people and infrastructure. The Alaska Division of Geological & Geophysical Surveys (DGGS) developed the data as part of the Federal Emergency Management Agency (FEMA) Cooperating Technical Partners Program to improve understanding of these hazards and support community resilience. The geodatabase contains a landslide inventory, a shallow landslide susceptibility model, and a channelized debris flow susceptibility and inundation model. All analyses relied exclusively on remote sensing and existing datasets, without field verification. The landslide inventory combines previously mapped landslides with additional slope failures identified through interpretation of high-resolution light detection and ranging (lidar) data and aerial imagery. It includes deposit polygons, flank polygons, and scarp polylines, and records 85 deposits: 33 rockfalls, 28 landslides, and 24 debris flows. Shallow landslide susceptibility was modeled from calculated factors of safety derived from slope angle, surficial soils mapping, and estimated soil engineering properties. Because detailed soil data are limited, the resulting susceptibility classes are a conservative estimate. Channelized debris flow hazards were modeled with a lidar-based approach that classifies debris flow initiation, transport, and watershed susceptibility and delineates inundation areas for both typical (common) and extreme (rare) events. Together, these products provide a regional assessment of landslide hazards that can inform land-use planning, infrastructure management, emergency preparedness, and future site-specific investigations. The data were developed for use at the published map scale of 1:25,000. They are not suitable for site-specific, regulatory, engineering, or legal purposes, and they do not predict the timing, probability, or recurrence of future landslides. These data and accompanying discussion are available from the DGGS website at https://doi.org/10.14509/32148.The purpose of this geodatabase is to give communities, planners, and emergency managers a consistent, openly available baseline for identifying where slope failures are most likely to threaten people and infrastructure. By helping prioritize areas for detailed investigation before development or disaster occurs, the data support safer land-use decisions, reduce potential losses, and strengthen the resilience of Alaska communities, which face growing landslide hazards from severe storms and retreating glaciers. The data are intended for regional, community-scale use at the published map scale of 1:25,000 and are not suitable for site-specific, regulatory, engineering, or legal purposes.This geodatabase contains a lidar-based landslide inventory and modeled shallow landslide susceptibility and channelized debris flow susceptibility and inundation data for approximately 245 km2 surrounding Cordova, Alaska. >cordova_landslide_hazards: Landslide inventory and modeled shallow landslide susceptibility and channelized debris flow susceptibility and inundation data for approximately 245 km2 surrounding Cordova, Alaska.2026publication dateCompleteNone planned-145.895834-145.43575660.70682860.446419ISO 19115 Topic CategorygeoscientificInformationAlaska Division of Geological & Geophysical SurveysAlluvialAlluviumBasinsCoastalColluviumCommunity ResilienceDatabaseDebris AvalancheDebris FlowDebris Flow DepositsDGGSEmergency PreparednessEngineeringEngineering GeologyEnvironmentalFanFracturingGelifluctionGeodatabaseGeologicGeologic CommunicationsGeologic HazardsGeological ProcessGeologyGeomorphologyGeospatial DataGeotechnicalGISGroundwaterHazard AssessmentHazard MappingHazard MitigationHazardsImage InterpretationInfrastructure RiskInterpretationLAHARZLandslideLandslide DepositsLandslide InventoryLandslide SusceptibilityLiquefactionMass-MovementMethodsModelingRockfallShearSlidesSlopeSlope AnalysisSlope ApronSlope DepositsSlope FailureSlope InstabilitySlumpSoil PropertiesSoilsSolifluctionSurfaceSurficialTalusTopographyTransportationAlaska Division of Geological & Geophysical SurveysCity of CordovaCopper River HighwayCordovaEyak LakeHeney PeakHeney RangeHumpback CreekKelly MountainMount EcclesMount EyakMount Robert KornMount ShielsNicolet CreekOhman FallsOrca InletPower CreekPrince William Sound Mining DistrictScout LakeTripod HillThis 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).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.Alaska Division of Geological & Geophysical SurveysMetadata Managermailing and physical

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FairbanksAK99709-3707USA(907)451-5020(907)451-5050dggspubs@alaska.gov8 am to 4:30 pm, Monday through Friday, except State holidaysPlease view our website (https://www.dggs.alaska.gov) for the latest information on available data. Please contact us using the e-mail address provided above when possible.DGGS collected and processed the lidar data and conducted the landslide susceptibility mapping for this project with funds from the Federal Emergency Management Agency (FEMA) Cooperating Technical Partners (CTP) Program, grant number CTP EMS-2021-CA-00014-01. We thank our reviewers, Dennis Staley (U.S. Geological Survey) and Nealey Sims (DGGS), for their thoughtful comments and suggestions, which improved the quality of this product. We also thank Bretwood Higman for sharing his unpublished landslide mapping of the Cordova area, which we incorporated into our inventory.Nicolazzo, J.A.Larsen, M.C.2025Alaska Landslide Inventory DatabaseDigital Data SeriesDDS 23Fairbanks, Alaska, United StatesAlaska Division of Geological & Geophysical Surveys14 phttps://doi.org/10.14509/31697Zechmann, J.M.Wikstrom Jones, K.M.Wolken, G.J.2024Lidar-derived elevation data for Cordova, Southcentral Alaska, collected August 18-19, 2023, and September 19 and 22, 2023Raw Data FileRDF 2024-6Fairbanks, Alaska, United StatesAlaska Division of Geological & Geophysical Surveys11 phttps://doi.org/10.14509/31159Attribute values in this geodatabase were derived through desktop interpretation of lidar-derived hillshade and slope rasters and aerial imagery, and through modeling, without field verification. Landslide inventory attributes, such as feature type, are interpretive. Many features could not be confidently assigned to a specific movement type and are classified as undifferentiated, and some slope failures were likely missed or misinterpreted because of limitations in the lidar data, available imagery, and vegetation cover. Lidar-based analysis cannot always distinguish natural elevation changes, such as landslide scour and deposition, from man-made structures. The inventory is a snapshot of conditions at the time of data collection and may become less accurate as new landslides occur. Shallow landslide susceptibility classes were calculated per soil unit using factor of safety (FOS) values. The values are strongly influenced by the accuracy and resolution of the input data, including soil unit extents, estimated material properties, depth to failure, depth to groundwater, and slope angle. Material properties were estimated from generalized soils data and published values, and they are conservative. Calculations were made per cell without regard for adjacent cells, so some localized overestimation of susceptibility is still possible despite resampling to 3-meter resolution and applying focal statistics. Debris flow initiation, transport, watershed susceptibility, and inundation attributes are based on estimated growth factors and volumes, so actual debris flow behavior may differ from the modeled results. The models do not account for differences in material composition, such as woody debris, or for the effects of buildings, bridges, culverts, topographic change, and mitigation measures on flow paths. No quantitative accuracy assessment was performed. The attributes are intended for regional- or community-scale use at the published map scale of 1:25,000 and are not suitable for site-specific, regulatory, engineering, or legal purposes.The landslide inventory follows the mapping protocols of Burns and Madin (2009) and Slaughter and others (2017) and uses the same database feature layers, attributes, and data dictionary as Nicolazzo and Larsen (2025a). Landslide is used generically for all slope failure types, including landslides, debris flows, and rockfall. The inventory contains three feature classes: deposit polygons, flank polygons, and scarp polylines. Not all slope instabilities have all three feature types. Channelized debris flows generally lack a well-defined source area and do not originate at a scarp, so their deposit polygons have no associated scarps or flanks. Rockfall deposits might have an associated scarp polyline but no flank polygon. Erosional deposits such as colluvium and talus were not classified as landslides, although scarp polylines were mapped for some of them. Each mapped landslide may represent a single occurrence or multiple events. For additional information on data sources, methods, and processing, see the accompanying report.This publication is not exhaustive. Limitations in the lidar data, imagery, and vegetation cover, together with the lack of field verification, mean that some slope failures were likely missed or misinterpreted, and many features are classified as undifferentiated. The inventory is a snapshot of conditions at the time of data collection and does not include later landslides. Erosional deposits such as colluvium and talus were not classified as landslides. The susceptibility models cover the full study area but exclude deep-seated bedrock failures, seismically triggered ground failures, and slopes of 55 degrees and greater for debris flow initiation. Debris flow inundation was modeled for typical and extreme scenarios only.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.Landslide inventory mapping - Landslide deposits, flanks, and scarps were identified following the mapping protocols of Burns and Madin (2009), Slaughter and others (2017), and the data dictionary of Nicolazzo and Larsen (2025a). Hillshade and slope rasters derived from the lidar DTM (Zechmann and others, 2024) were interpreted and supplemented with aerial imagery. Deposit polygons, flank polygons, and scarp polylines were then digitized in ArcGIS Pro.2025Factor of safety calculation - Existing surficial soils mapping was refined using aerial imagery and the DTM. Because there was no field or laboratory testing, soil engineering properties were estimated from published values. Factor of safety (FOS) calculation was then calculated for each soil unit across the full range of possible slope angles. After calibration, the soils mapping was revised to account for vegetation and to distinguish stable from active landslide deposits.2025Shallow landslide susceptibility classification - Following Burns and others (2012), each soil unit was classified as high, moderate, or low to no susceptibility based on FOS thresholds, and the results were mosaicked into a single raster. The raster was then smoothed with Focal Statistics to remove small man-made features. Finally, buffers were applied around all mapped scarps (high susceptibility) and around areas of moderate or high susceptibility (moderate susceptibility).2025Debris flow susceptibility modeling - Following Burns and others (2022), debris flow initiation, channel transport, and watershed susceptibility were scored using a Laharz-based method and custom ArcGIS tools. The concavity threshold used to delineate drainage channels was adjusted by comparing modeled channels with lidar and aerial imagery.2025Debris flow inundation modeling - Typical and extreme debris flow scenarios were modeled, with inputs selected by comparison with observed debris flow deposits. The inundation rasters were then smoothed and converted to polygons, and the polygon edges were manually edited to remove unrealistic spikes and areas misclassified because of DTM interpolation.2025vector0.0010.001decimal degreesNAD83 (2011)GRS 806378137298.257222101cordova_landslide_hazardsLandslide inventory and modeled shallow landslide susceptibility and channelized debris flow susceptibility and inundation data for approximately 245 km2 surrounding Cordova, Alaska.this report, DGGS staffcordova_landslide_hazardsdeposit_polygonsPolygons tracing deposit extents, or the scar extents of a paleolandslidethis report, DGGS staffFile Geodatabase Feature Classflank_polygonsPolygons tracing landslide flanksthis report, DGGS staffFile Geodatabase Feature Classinundation_extremePolygons representing debris flow inundation/deposition extents, modeled for an "extreme" eventthis report, DGGS staffFile Geodatabase Feature Classinundation_typicalPolygons representing debris flow inundation/deposition extents modeled for a "typical" eventthis report, DGGS staffFile Geodatabase Feature Classscarp_polylinesPolylines tracing scarpsthis report, DGGS staffFile Geodatabase Feature Classshallow_susceptibilityRaster image depicting slopes susceptible to shallow landslides; pixel values indicate risk classification: 1 = very low/none, 2 = low, 3 = moderate, 4 = high, 5 = very highthis report, DGGS staffFile Geodatabase Raster DatasettransportPolylines representing the transport path for a debris flowthis report, DGGS staffFile Geodatabase Feature ClasswatershedPolygons representing the watershed contributing to each potential debris flowthis report, DGGS staffFile Geodatabase Feature ClassAlaska Division of Geological & Geophysical SurveysMetadata Managermailing and physical

3354 College Road

FairbanksAK99709-3707USA(907)451-5020(907)451-5050dggspubs@alaska.gov8 am to 4:30 pm, Monday through Friday, except State holidaysFGDC Content Standard for Digital Geospatial MetadataFGDC-STD-001-1998If the user has modified the data in any way they are obligated to describe the types of modifications they have performed in the supporting metadata file. User specifically agrees not to imply that changes they made were approved by the Alaska Department of Natural Resources or Division of Geological & Geophysical Surveys.https://dggs.alaska.gov/metadata/dggs.extdggs metadata extensions