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stage/SLIDO_Statewide_LSS (ImageServer)

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Service Description: Many parts of Oregon are highly susceptible to landslides which pose significant threats to people and infrastructure particularly in the portions of the state with moderate to steep slopes. As population growth expands and development onto landslide susceptible terrain occurs, greater losses are likely to result. Most of Oregons landslide damage has been associated with severe winter storms where landslide losses exceed $100 million in direct damage (such as the February 1996 eventsee FEMA, 1996). However, landslides are a chronic hazard in Oregon and annual average maintenance and repair costs for landslides in Oregon are over $10 million (Wang and others, 2002). Landslides induced by earthquake shaking are likely in many parts of Oregon, and losses associated with sliding in moderate-to-large earthquakes are likely to be significant. Volcanic induced and/or associated landslide hazards are also potential threats to parts of Oregon. In order to reduce risk from landslides, information about the hazard must be readily available. In 2007, research at the Oregon Department of Geology and Mineral Industries (DOGAMI) was performed to choose the best remote sensing dataset (i.e. aerial photos, photogrammetric elevation data, lidar elevation data, etc.) to use as a primary tool to begin systematic mapping of landslides in Oregon. The use of lidar topographic data was deemed necessary for the understanding and mapping the landslide hazard in Oregon. The second conclusion of this study was to systematically compile all previously mapped landslides from geologic and hazard maps. This database (Statewide Landslide Information Database of Oregon, SLIDO) would then serve as a starting place for all future landslide studies (Burns, 2007). The data in this raster depicts landslide susceptibility at a 10-meter resolution, across the state of Oregon. This dataset was created using elevation data, first from the Oregon Lidar Consortium (OLC), or from USGS NED where OLC data was not present. This elevation data was converted into slopes, and a multi-pronged analysis process used these slopes, geology and mapped existing landslides to create this 10-meter raster. There are 4 classes of landslide susceptibility: Low, Moderate, High and Very High.

Name: stage/SLIDO_Statewide_LSS

Description: Many parts of Oregon are highly susceptible to landslides which pose significant threats to people and infrastructure particularly in the portions of the state with moderate to steep slopes. As population growth expands and development onto landslide susceptible terrain occurs, greater losses are likely to result. Most of Oregons landslide damage has been associated with severe winter storms where landslide losses exceed $100 million in direct damage (such as the February 1996 eventsee FEMA, 1996). However, landslides are a chronic hazard in Oregon and annual average maintenance and repair costs for landslides in Oregon are over $10 million (Wang and others, 2002). Landslides induced by earthquake shaking are likely in many parts of Oregon, and losses associated with sliding in moderate-to-large earthquakes are likely to be significant. Volcanic induced and/or associated landslide hazards are also potential threats to parts of Oregon. In order to reduce risk from landslides, information about the hazard must be readily available. In 2007, research at the Oregon Department of Geology and Mineral Industries (DOGAMI) was performed to choose the best remote sensing dataset (i.e. aerial photos, photogrammetric elevation data, lidar elevation data, etc.) to use as a primary tool to begin systematic mapping of landslides in Oregon. The use of lidar topographic data was deemed necessary for the understanding and mapping the landslide hazard in Oregon. The second conclusion of this study was to systematically compile all previously mapped landslides from geologic and hazard maps. This database (Statewide Landslide Information Database of Oregon, SLIDO) would then serve as a starting place for all future landslide studies (Burns, 2007). The data in this raster depicts landslide susceptibility at a 10-meter resolution, across the state of Oregon. This dataset was created using elevation data, first from the Oregon Lidar Consortium (OLC), or from USGS NED where OLC data was not present. This elevation data was converted into slopes, and a multi-pronged analysis process used these slopes, geology and mapped existing landslides to create this 10-meter raster. There are 4 classes of landslide susceptibility: Low, Moderate, High and Very High.

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 9.999999999959998

Pixel Size Y: 9.999999999960007

Band Count: 1

Pixel Type: U16

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "", "help": "" }]}

Mensuration Capabilities: Basic

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: Partially funded by the Federal Emergency Management Agency (FEMA) Hazard Mitigation Grant Program (HMGP)

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: 0

Max Values: 4

Mean Values: 1.6431018005942868

Standard Deviation Values: 1.143784074160697

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: true

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Raster Attribute Table   Histograms   Statistics   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project