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HP_WAHCAP/SolarRisk (ImageServer)

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Service Description: Areas of both high connectivity value and solar development risk developed for the Washington Habitat Connectivity Action Plan.To identify focal connectivity areas with a high threat of solar development we used The Solar Development Suitability Model for Columbia Plateau created by a mapping group for the Least-Conflict Solar Project managed by Washington State University Energy Program (https://www.energy.wsu.edu/RenewableEnergy/LeastConflictSolarSiting.aspx). The model was built using Environmental Evaluation Modeling System (EEMS) developed by the Conservation Biology Institute (CBI). EEMS is a flexible, data-driven framework that uses fuzzy logic to integrate various spatial data layers and assess complex environmental and planning questions. It allows for the combination of different types of data (e.g., ecological, infrastructure, land use) to produce a suitability map. The logic of The Solar Development Suitability Model aimed at depicting relative physical suitability for utility scale passive solar development. At a high level of this hierarchical model, high development suitability was defined by characteristics such as terrain (slope and aspect) and soil conditions, high proximity to existing road and transmission infrastructure, and to a lesser degree potential hazards (i.e., wildfire and earthquakes). The values of The Solar Development Suitability Model ranged from -1 (highly unsuitable) to 1 (highly suitable). We extracted only the positive values by setting all negative values to 0. We then multiplied this layer by the rescaled (0-1) connectivity value surface, representing areas with relatively high connectivity (portions of the original connectivity surface with values exceeding the 30th percentile). The resulting layer assigned higher values to areas of high connectivity threatened by solar development. We then used this final multiplication layer to compute a kernel density surface. Similarly to the residential development analyses, we applied a kernel cost-weighted distance of 79,200.

Name: HP_WAHCAP/SolarRisk

Description: Areas of both high connectivity value and solar development risk developed for the Washington Habitat Connectivity Action Plan.To identify focal connectivity areas with a high threat of solar development we used The Solar Development Suitability Model for Columbia Plateau created by a mapping group for the Least-Conflict Solar Project managed by Washington State University Energy Program (https://www.energy.wsu.edu/RenewableEnergy/LeastConflictSolarSiting.aspx). The model was built using Environmental Evaluation Modeling System (EEMS) developed by the Conservation Biology Institute (CBI). EEMS is a flexible, data-driven framework that uses fuzzy logic to integrate various spatial data layers and assess complex environmental and planning questions. It allows for the combination of different types of data (e.g., ecological, infrastructure, land use) to produce a suitability map. The logic of The Solar Development Suitability Model aimed at depicting relative physical suitability for utility scale passive solar development. At a high level of this hierarchical model, high development suitability was defined by characteristics such as terrain (slope and aspect) and soil conditions, high proximity to existing road and transmission infrastructure, and to a lesser degree potential hazards (i.e., wildfire and earthquakes). The values of The Solar Development Suitability Model ranged from -1 (highly unsuitable) to 1 (highly suitable). We extracted only the positive values by setting all negative values to 0. We then multiplied this layer by the rescaled (0-1) connectivity value surface, representing areas with relatively high connectivity (portions of the original connectivity surface with values exceeding the 30th percentile). The resulting layer assigned higher values to areas of high connectivity threatened by solar development. We then used this final multiplication layer to compute a kernel density surface. Similarly to the residential development analyses, we applied a kernel cost-weighted distance of 79,200.

Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 5280.0

Pixel Size Y: 5280.0

Band Count: 1

Pixel Type: F32

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

Mensuration Capabilities: Basic

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: This layer was developed for the 2025 Washington Habitat Connectivity Action Plan by the Washington Department of Fish and Wildlife (WDFW) and the Conservation Biology Institute (https://www.consbio.org/). WDFW modified the solar suitability layer that CBI created for the Least-Conflict Solar Siting project (https://www.energy.wsu.edu/RenewableEnergy/LeastConflictSolarSiting.aspx).

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: 0

Max Values: 0.5358530879020691

Mean Values: 0.010804678888509625

Standard Deviation Values: 0.04151707538181991

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

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Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Nearest

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: false

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