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Wildlife_Movement_Resistance (Map Service)


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Current Version: 10.81

Service Description:
The Source Layer was combined with the Southern California Council of Governments (SCAG) 2008 Land Use layer to produce the resistance layer for species movement in Omniscape. This regional land use map aggregates local municipal land use maps from the numerous local planning agencies within the study area. The specificity of each of the 100 land use types in the resulting dataset, and the precise polygon delineations, provides a detailed estimate of land use intensity and boundaries suitable for converting to the relatively high 10’ pixel resolution of this study. Many of the 100 land use types provided were relatively duplicative because they represented different local naming and classification conventions for the same general land use. I reviewed the descriptions of each type and reclassified them into 15 general types based on assumed land use intensity and potential resistance to species movement (see Table 3-1). Refining resistance values considering road traffic volumes, more detailed land use for the City of Los Angeles, building footprints, and other mapped barriers is a planned next step for application. 

The approach presented here is somewhat of a hybrid between purely landcover and land use based approaches. First, I consider remotely sensed surface cover for differentiating vegetated vs. non-vegetated pixels using the 2016 LA County Urban Forest Canopy Assessment dataset and CALVEG. I assigned vegetated pixels, regardless of the underlying SCAG land use type they fall within, with relatively low resistance scores based on their source values, but reversed (i.e. source scores of 10 receive a resistance score of 1, 9 = 2, 8 = 3, etc.). Adjusting vegetated pixel resistance based on underlying land use context may be appropriate in this more urbanized area and should be explored as a next step in application. Next, I assigned resistance values to non-vegetated pixels based on the underlying SCAG land use type. Values of 23 to 300 were given for non-vegetated pixels, which reflects similar values to McRae et al (2016). Land uses, such as commercial and high rise residential, were assumed to produce higher “edge effects”, such as light, noise, traffic, or litter, or other land use impacts that may reduce native species movement and were given the highest resistance values. Non-vegetated pixels within land uses such as low density residential and open space were given the lowest resistance values since they were assumed to produce less edge effects. Campus, office, and industrial land uses were given moderate resistance values. The ocean was given a “no data” value because this study is intended to assess terrestrial permeability only (including small water bodies).

Data source: 2006 10-foot Digital Elevation Model (DEM) – LARIAC – Public Domain


Map Name: Layers

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All Layers and Tables

Layers: Description:
The Source Layer was combined with the Southern California Council of Governments (SCAG) 2008 Land Use layer to produce the resistance layer for species movement in Omniscape. This regional land use map aggregates local municipal land use maps from the numerous local planning agencies within the study area. The specificity of each of the 100 land use types in the resulting dataset, and the precise polygon delineations, provides a detailed estimate of land use intensity and boundaries suitable for converting to the relatively high 10’ pixel resolution of this study. Many of the 100 land use types provided were relatively duplicative because they represented different local naming and classification conventions for the same general land use. I reviewed the descriptions of each type and reclassified them into 15 general types based on assumed land use intensity and potential resistance to species movement (see Table 3-1). Refining resistance values considering road traffic volumes, more detailed land use for the City of Los Angeles, building footprints, and other mapped barriers is a planned next step for application. 

The approach presented here is somewhat of a hybrid between purely landcover and land use based approaches. First, I consider remotely sensed surface cover for differentiating vegetated vs. non-vegetated pixels using the 2016 LA County Urban Forest Canopy Assessment dataset and CALVEG. I assigned vegetated pixels, regardless of the underlying SCAG land use type they fall within, with relatively low resistance scores based on their source values, but reversed (i.e. source scores of 10 receive a resistance score of 1, 9 = 2, 8 = 3, etc.). Adjusting vegetated pixel resistance based on underlying land use context may be appropriate in this more urbanized area and should be explored as a next step in application. Next, I assigned resistance values to non-vegetated pixels based on the underlying SCAG land use type. Values of 23 to 300 were given for non-vegetated pixels, which reflects similar values to McRae et al (2016). Land uses, such as commercial and high rise residential, were assumed to produce higher “edge effects”, such as light, noise, traffic, or litter, or other land use impacts that may reduce native species movement and were given the highest resistance values. Non-vegetated pixels within land uses such as low density residential and open space were given the lowest resistance values since they were assumed to produce less edge effects. Campus, office, and industrial land uses were given moderate resistance values. The ocean was given a “no data” value because this study is intended to assess terrestrial permeability only (including small water bodies).

Data source: 2006 10-foot Digital Elevation Model (DEM) – LARIAC – Public Domain


Copyright Text: Los Angeles Region Imagery Acquisition Consortium (LARIAC), Southern California Association of Governments (SCAG), Isaac Brown (UCLA Doctoral Dissertation)

Spatial Reference:
102100

Single Fused Map Cache: true

Capabilities: Map,TilesOnly,Tilemap

Tile Info:
Initial Extent:
Full Extent:
Min Scale: 0.0
Max Scale: 0.0

Min LOD: 11
Max LOD: 14

Units: esriMeters

Supported Image Format Types: MIXED

Export Tiles Allowed: false
Max Export Tiles Count: 100000

Resampling: true

Document Info: