Hazards/FloydSusceptibility_ImageService (ImageServer)

View In: ArcGIS JavaScript ArcGIS Online Map Viewer ArcGIS Earth

Service Description: We classified the landslide susceptibility results in a GIS (Geographic Information Systems) using standard deviations from a calculated probability that a landslide has occurred, is occurring, or will occur based upon a combination of landscape variables. The landslide susceptibility classes are: Landslide Susceptibility (pixel values: low 0.0 - 0.2 low-moderate 0.21 - 0.4 moderate 0.41 - 0.6 moderate-high 0.61 - 0.8 high 0.81 - 1.0 We developed an approach to landslide-susceptibility mapping combining machine-learning and geomorphic statistics (Crawford and others, 2021). The susceptibility model is based upon high-resolution airborne lidar-derived data sets from a 1.5-m regional digital elevation model and a detailed landslide inventory for Floyd County, Kentucky. We used a logistic regression model to establish a connection between specific slope variables and landslide occurrence. We evaluated slope angle, aspect, elevation, terrain roughness, curvature, and plan curvature to determine what influences landslide occurrence. Next, we modeled the probability of occurrence and used those values to create a landslide-susceptibility map. Our model and resulting map estimate the probability of an event (a landslide) determined by the slope variables. The probability and map classification are not a landslide prediction result from a scenario-based event (a rainfall event, for example), or a probability with a time component. This means the map classification will not predict how or when a landslide might occur, only the likelihood of a past or future occurrence. Data that occurs on less than a 3-degree slope were excluded because these areas are mostly flat. Although determining landslide susceptibility has inherent uncertainty, our map results, and distribution of higher probabilities (moderate, moderate-high, high) effectively reflect the geomorphic variables that are indicative of unstable ground conditions and potential landslide activity. The low-moderate and low susceptibility classes do not indicate that landslides have not or cannot occur in these areas.

Name: Hazards/FloydSusceptibility_ImageService

Description: We classified the landslide susceptibility results in a GIS (Geographic Information Systems) using standard deviations from a calculated probability that a landslide has occurred, is occurring, or will occur based upon a combination of landscape variables. The landslide susceptibility classes are: Landslide Susceptibility (pixel values: low 0.0 - 0.2 low-moderate 0.21 - 0.4 moderate 0.41 - 0.6 moderate-high 0.61 - 0.8 high 0.81 - 1.0 We developed an approach to landslide-susceptibility mapping combining machine-learning and geomorphic statistics (Crawford and others, 2021). The susceptibility model is based upon high-resolution airborne lidar-derived data sets from a 1.5-m regional digital elevation model and a detailed landslide inventory for Floyd County, Kentucky. We used a logistic regression model to establish a connection between specific slope variables and landslide occurrence. We evaluated slope angle, aspect, elevation, terrain roughness, curvature, and plan curvature to determine what influences landslide occurrence. Next, we modeled the probability of occurrence and used those values to create a landslide-susceptibility map. Our model and resulting map estimate the probability of an event (a landslide) determined by the slope variables. The probability and map classification are not a landslide prediction result from a scenario-based event (a rainfall event, for example), or a probability with a time component. This means the map classification will not predict how or when a landslide might occur, only the likelihood of a past or future occurrence. Data that occurs on less than a 3-degree slope were excluded because these areas are mostly flat. Although determining landslide susceptibility has inherent uncertainty, our map results, and distribution of higher probabilities (moderate, moderate-high, high) effectively reflect the geomorphic variables that are indicative of unstable ground conditions and potential landslide activity. The low-moderate and low susceptibility classes do not indicate that landslides have not or cannot occur in these areas.

Single Fused Map Cache: false

Extent:

Initial Extent:

Full Extent:

Pixel Size X: 10.0

Pixel Size Y: 10.0

Band Count: 1

Pixel Type: F32

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

Resampling: false

Copyright Text:

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: 0.0013674651272594929

Max Values: 0.9977895021438599

Mean Values: 0.3355649657880341

Standard Deviation Values: 0.199034360879271

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: 20000

Max Image Width: 20000

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: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources: Info 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