Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>WGS-Protocol Landslide Mapping shows the locations of landslides mapped using lidar and the Washington Geological Survey’s published landslide mapping protocol Bulletin 82 (Slaughter and others, 2017). The WGS-Protocol Landslide Mapping data supersede the </SPAN><SPAN><SPAN>Other Compiled Landslide Mapping</SPAN></SPAN><SPAN><SPAN> </SPAN></SPAN><SPAN><SPAN>dataset (see below).</SPAN></SPAN></P><P><SPAN><SPAN> As additional high</SPAN></SPAN><SPAN><SPAN>-</SPAN></SPAN><SPAN><SPAN>quality lidar is obtained, and as mass movements occur, the inventory will continue to be updated; because of these caveats, the inventory may not contain all the mass movements within an area where mapping appears to be complete. This dataset is not intended as a substitute for a detailed investigation of potential slope instability by a qualified practitioner. Site-specific analysis may give results that differ from those displayed on the map.</SPAN></SPAN></P><P /></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This is a point feature class used to define the approximate head scarp or initiation area of landslides using the methods described in our lidar-based protocol (Slaughter and others, 2017). Recent landslides visible in aerial/orthoimagery, from field reconnaissance, or from information from outside sources are defined with this feature class. This feature class is part of a larger landslide inventory dataset for Washington State.</SPAN></P></DIV></DIV></DIV>
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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>This is a polygon feature class used to delineate alluvial fan or debris flow fan deposits using the methods described in our lidar-based protocol (Slaughter and others, 2017). Fans visible in lidar (light detection and ranging) derivative datasets are delineated in this feature class, and no deposits inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class only includes information the analyst can determine remotely. This feature class is part of a larger landslide inventory dataset for Washington State.</SPAN></SPAN></P></DIV></DIV></DIV>
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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 0 0;"><SPAN>This is line feature class used to graphically represent the uppermost portion of a rock fall source area using the methods described in our lidar-based protocol (Slaughter and others, 2017). Only source areas visible in lidar derivative datasets and (or) aerial/orthoimagery derivative datasets are delineated with this feature class, and no rock fall scarps inferred from field reconnaissance, or other techniques are included. This feature class is part of a larger landslide inventory dataset for Washington State. Lines in this feature class are related to polygons in the ‘Rock Fall Deposits’ feature class by using the ROCKFALL_ID primary key field. </SPAN></P></DIV></DIV></DIV>
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Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:7 0 7 0;"><SPAN><SPAN>This is a polygon feature class used to delineate rock fall deposits using the methods described in </SPAN></SPAN><SPAN><SPAN>our lidar-based protocol (Slaughter and others, 2017)</SPAN></SPAN><SPAN>. Only rock fall deposits visible in lidar (light detection and ranging) derivative datasets and (or) aerial/orthoimagery are delineated with this feature class, and no rock fall deposits inferred from field reconnaissance or other techniques are included. This feature class only includes information the landslide analyst can determine remotely. This feature class is part of a larger landslide inventory dataset for Washington State. Polygons in this feature class are related with lines in the ‘Rock Fall Scarps’ feature class by using the ROCKFALL_ID primary key field.</SPAN></P></DIV>
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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This is a polyline feature class used to graphically represent the head scarp and internal scarps (if present) of a landslide using the methods described in the protocol. Only scarps visible in lidar (light detection and ranging) derivative datasets are delineated with this feature class, and no scarps inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class is part of a larger landslide inventory dataset for Washington State. Polylines in this feature class are related with polygons in the landslide_deposit and scarp_and_flank feature classes by using the LANDSLIDE_ID primary key field.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:0 0 0 0;"><SPAN>This is a polygon feature class used to delineate the head scarp and flanks of landslides using the methods described in our lidar-based protocol (Slaughter and others, 2017). Only scarps and flanks visible in lidar derivative datasets are delineated with this feature class, and no scarps or flanks inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class is part of a larger landslide inventory dataset for Washington State. Polygons in this feature class are related to polygons in the ‘Landslide Deposits’ feature class, and lines in the ‘Scarps’ feature class, by using the LANDSLIDE_ID primary key field.</SPAN></P></DIV>
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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:7 0 7 0;"><SPAN><SPAN>This is a polygon feature class used to delineate landslide deposits using the methods described in </SPAN></SPAN><SPAN><SPAN>our lidar-based protocol (Slaughter and others, 2017)</SPAN></SPAN><SPAN>. Only landslide deposits visible in lidar derivative datasets are delineated with this feature class, and no deposits inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class only includes information the landslide analyst can determine remotely. This feature class is part of a larger landslide inventory dataset for Washington State. Polygons in this feature class are related with polygons in the ‘Scarps and Flanks’ feature class, and lines in the ‘Scarps’ feature class, by using the LANDSLIDE_ID primary key field.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:0 0 0 0;"><SPAN>This is a polygon feature class used to rapidly delineate entire landslides (including the deposit, head scarp, and flank areas) using the methods described in our lidar-based protocol (Slaughter and others, 2017). Only landslides visible in lidar derivative datasets are delineated with this feature class, and no deposits inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class only includes minimal information the analyst can determine remotely. This feature class is part of a larger landslide inventory dataset for Washington State. The acronym SLIP refers to Streamlined Landslide Inventory Protocol.</SPAN></P></DIV>
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Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>This is a polygon feature class used to rapidly delineate fans using the methods described in </SPAN></SPAN><SPAN><SPAN>our lidar-based protocol (Slaughter and others, 2017)</SPAN></SPAN><SPAN>. Only fans visible in lidar derivative datasets are delineated with this feature class, and no deposits inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. This feature class only includes minimal information the analyst can determine remotely. This feature class is part of a larger landslide inventory dataset for Washington State. The acronym SLIP refers to Streamlined Landslide Inventory Protocol.</SPAN></P></DIV>
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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This is a raster intended to estimate areas susceptible to shallow landslides, and methods described in Burns and others (2012) were followed to generate the data.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>This is a raster intended to estimate areas susceptible to deep-seated landslides. To create this susceptibility dataset, a landslide inventory was first created by using the methods described in the lidar-based protocol (Slaughter and others, 2017). The constructed landslide inventory was then used, along with other necessary datasets, to create this deep-seated landslide susceptibility dataset by following the protocol from Special Paper 48 (Burns and Mickelson, 2016).</SPAN></SPAN></P><DIV><DIV><P><SPAN /></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>This feature class shows the extents of studies completed following </SPAN></SPAN><SPAN><SPAN>our lidar-based protocol (Slaughter and others, 2017)</SPAN></SPAN><SPAN><SPAN>. Only landslide deposits visible in lidar derivative datasets are delineated in this database, and no deposits inferred from aerial/orthoimagery, field reconnaissance, or other techniques are included. </SPAN></SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><P STYLE="margin:0 0 0 0;"><SPAN>Other Compiled Landslide Mapping shows landslides compiled from a variety of sources, spanning the past few decades. Landslides from various projects may or may not have used lidar for landslide identification. Landslides in this compilation are mapped at various scales and with varied purpose. Many of these compilation layers are not statewide in extent – the absence of a mapped landslide in a particular location does not suggest that no landslide exists or that there is no landslide risk.</SPAN></P><P /><DIV><P><SPAN /></P></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This feature class contains landslides compiled from a variety of sources, spanning the past few decades. The Landslide Compilation contains landslides from the following sources: (1) Landslides that are mapped within 1:24,000-scale geologic mapping (not statewide) and our statewide 1:100,000-scale geologic map compilation; (2) a miscellaneous compilation of pre-existing landslide data from several sources, including the Washington Geological Survey, the Department of Natural Resources’ Forest Practices Division, and other federal and private entities; (3) landslides mapped as part of Watershed Analysis efforts for the Forest Practices Board; (4) reconnaissance-scale mapping of landslides associated with significant landslide events; and (5) a study of near-shore landforms along the Salish Sea.</SPAN></P><P><SPAN>1:24,000-scale and 1:100,000-scale Landslides from Geologic Mappings how landslides that were extracted from 1:24,000- and 1:100,000-scale geologic maps. Landslide mapping was not the primary purpose of these projects, and the absence of a mapped landslide in a particular location does not suggest that no landslide exists or that there is no landslide risk. Also, due to the scale of the final mapping products, landslides with deposits too small to be identified in any included scale of geologic mapping (for example, debris flows, debris avalanches, rock topples, etc.) are not typically included. Only partial coverage exists for landslides mapped at 1:24,000 scale. 1:100,000-scale mapping covers the entire state.</SPAN></P><P><SPAN>Miscellaneous Landslide Mapping is compiled landslide data from many sources focused on landslide mapping. Each project has its own protocol and methods, so it is up to the user to determine how best to interpret the landslide data. To avoid the risk of misinterpretation, invalid results, and erroneous conclusions, users should consider original map scale, collection methodology, original mapping purpose, currency of data, and any other conditions specific to every data element and each dataset as a whole.</SPAN></P><P><SPAN>Watershed Analysis Landslide Mapping polygons were created to support forest practices rules in identification of unstable slopes in various watersheds throughout the state. Rule-identified landform mapping was conducted using aerial photographs, maps (including geology, soil, and topographic), field observations, and limited lidar. Landforms were identified and mapped using a Watershed Analysis or the Landslide Hazard Zonation Protocol. All rule-identified landforms are not shown; only areas identified as landslides in the original watershed analyses are included in this data.</SPAN></P><P><SPAN>Reconnaissance-Scale Landslide Mapping is compiled landslides mapped from surveys immediately following widespread rain or rain-on-snow events in Washington. Mapping techniques for these large-scale surveys vary between aerial surveys from small aircraft, aerial photography, or lidar identification, with minimal field verification.</SPAN></P><P><SPAN>The Salish Sea Landforms identifies landforms along 2,200 miles of Salish Sea shoreline that have characteristics of deep-seated landslides, but lack the thorough investigation necessary to classify these landforms as landslides. All landforms in this layer were identified using historic aerial imagery and 3- to 6-foot LiDAR digital elevation models (DEM). Based on interpretation of LiDAR derivatives (such as hill shades, contour lines, and slope gradient) and aerial imagery, observations of geomorphic features representative of a deep-seated landslide were delineated in a GIS. Due to the method of data collection and the certainty of the data, this dataset should not be confused with a landslide inventory, which typically undergoes a thorough, historic aerial imagery analysis, field validation, and peer review. </SPAN></P><P><SPAN>Landslides from various projects may or may not have used lidar for landslide identification. Landslides in this compilation are mapped at various scales and with varied purpose. Many of these compilation layers are not statewide in extent – the absence of a mapped landslide in a particular location does not suggest that no landslide exists or that there is no landslide risk.</SPAN></P><P><SPAN>To avoid the risk of misinterpretation, invalid results, and erroneous conclusions, users must consider original map scale, collection methodology, currency of data, and any other conditions specific to every data element and each dataset as a whole. This dataset is not intended as a substitute for a detailed investigation of potential slope instability by a qualified practitioner. Site-specific analysis may give results that differ from those displayed on the map.</SPAN></P><P><SPAN>In areas where the Landslide Compilation is overlapped by the lidar-based Landslide Inventory, the overlapping zones have been attributed as ‘superseded.’ These layers are not displayed on the portal but are available in the GIS download of the Landslide Compilation.</SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
GRADIENT_METHOD
(
type: esriFieldTypeString, alias: Gradient Method, length: 50
, Coded Values:
[Gradient degrees determined in the field: Gradient degrees determined in the field]
, [Gradient degrees determined from Lidar: Gradient degrees determined from Lidar]
, [Gradient degrees determined from a DEM (10m): Gradient degrees determined from a DEM (10m)]
, ...3 more...
)
FIELD_CHECK
(
type: esriFieldTypeString, alias: Field Check, length: 80
, Coded Values:
[Field checked by a landslide professional: Field checked by a landslide professional]
, [Field checked by a non-landslide professional: Field checked by a non-landslide professional]
, [Field checked from a plane, boat, or other location: Field checked from a plane, boat, or other location]
, ...2 more...
)
INFRASTRUCTURE_DAMAGE
(
type: esriFieldTypeString, alias: Infrastructure Damage, length: 90
, Coded Values:
[Landslide has caused structure damage : Landslide has caused structure damage]
, [Landslide has probably caused structure damage due to location adjacent to structure : Landslide has probably caused structure damage due to location adjacent to structure]
, [Landslide may have caused structure damage but evidence not conclusive: Landslide may have caused structure damage but evidence not conclusive]
, ...4 more...
)
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This polygon feature class contains map extents and associated citation attributes (where available) for landslide study areas in Washington State. Many of these studies were done over the extent of 1:24,000 or 1:100,000 scale quadrangles. Others were done over the extent of Watershed Administrative Units (WAUs). Areas that overlap studies performed using the new landslide inventory mapping protocol have been split at their intersection, and are superseded.</SPAN></P></DIV></DIV></DIV>
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