Services Directory - Forest

Forest_ras (Map Service)

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Current Version: 10.81

Service Description:

This raster data was created through a combination of field sampling, remote sensing, and classification.

Classification was achieved using vegetation characteristics including canopy height, slope, atmospherically resistant vegetation index (ARVI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), canopy xanthophyll or photochemical reflectance index (PRI), soil-adjusted vegetation index (SVI), and normalized difference burn index (NDBI).

The final raster has four values reflecting four categories based on the tree ratio:

Category 4 = 70 – 100% dead; Category 3 = 40 – 70% dead, Category 2 = 10 – 40% dead, and Category 1 = 0 – 10% dead.

Map Name: Map

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Layers:

Forest assessment(0)

Tables:

Description:

This raster data was created through a combination of field sampling, remote sensing, and classification.

The final raster has four values reflecting four categories based on the tree ratio:

Category 4 = 70 – 100% dead; Category 3 = 40 – 70% dead, Category 2 = 10 – 40% dead, and Category 1 = 0 – 10% dead.

Copyright Text:

Spatial Reference:
102100

Single Fused Map Cache: true

Capabilities: Map,TilesOnly,Tilemap

Tile Info:

Height: 256
Width: 256
DPI: 96
Levels of Detail: (# Levels: 24)

Level ID: 0 [Start Tile, End Tile]
Level ID: 1 [Start Tile, End Tile]
Level ID: 2 [Start Tile, End Tile]
Level ID: 3 [Start Tile, End Tile]
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Level ID: 10 [Start Tile, End Tile]
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Level ID: 20 [Start Tile, End Tile]
Level ID: 21 [Start Tile, End Tile]
Level ID: 22 [Start Tile, End Tile]
Level ID: 23 [Start Tile, End Tile]

Format: Mixed
Compression Quality: 75
Origin:
Spatial Reference:
102100

Initial Extent:

Full Extent:

Min Scale: 1155581.108577
Max Scale: 36111.909643

Min LOD: 9
Max LOD: 14

Units: esriMeters

Supported Image Format Types: Mixed

Export Tiles Allowed: false
Max Export Tiles Count: 100000

Document Info:

Title: Forest_ras
Author: cprescot_UWyo
Comments:
Subject: Tree ratio classification raster.
Category:
Keywords: