Services Directory - IMG_VCGI_TREECANOPY2022_WM

IMG_VCGI_TREECANOPY2022_WM_v1 (Map Service)

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Current Version: 10.81

Service Description: This Coniferous and Deciduous dataset was derived from high-resolution remotely sensed data -- 2021/2022 NAIP and 2016 LiDAR. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and coniferous deciduous trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:2500 and all observable errors were corrected.

Map Name: Layers

Legend

All Layers and Tables

Layers:

LandLandcov_TreeCanopy2022.tif(0)

Description: This Coniferous and Deciduous dataset was derived from high-resolution remotely sensed data -- 2021/2022 NAIP and 2016 LiDAR. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and coniferous deciduous trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:2500 and all observable errors were corrected.

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]
Level ID: 4 [Start Tile, End Tile]
Level ID: 5 [Start Tile, End Tile]
Level ID: 6 [Start Tile, End Tile]
Level ID: 7 [Start Tile, End Tile]
Level ID: 8 [Start Tile, End Tile]
Level ID: 9 [Start Tile, End Tile]
Level ID: 10 [Start Tile, End Tile]
Level ID: 11 [Start Tile, End Tile]
Level ID: 12 [Start Tile, End Tile]
Level ID: 13 [Start Tile, End Tile]
Level ID: 14 [Start Tile, End Tile]
Level ID: 15 [Start Tile, End Tile]
Level ID: 16 [Start Tile, End Tile]
Level ID: 17 [Start Tile, End Tile]
Level ID: 18 [Start Tile, End Tile]
Level ID: 19 [Start Tile, End Tile]
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: 0.0
Max Scale: 0.0

Min LOD: 7
Max LOD: 20

Units: esriMeters

Supported Image Format Types: MIXED

Export Tiles Allowed: false
Max Export Tiles Count: 100000

Resampling: true

Document Info:

Title: VT Service - Raster Tile Layer - Tree Canopy 2022
Author: Services_VCGI
Comments:
Subject: Coniferous and Deciduous raster was developed as part of land cover mapping for the Updated High-Resolution Land Cover Mapping for Vermont.
Category:
Keywords: SkipBackup, nodeVCGI, vcgi open data, itemtypeWebService, isothemeLand, subthemeLandcov, land cover, landcover, trees, tree canopy, deciduous, coniferous, 2022, Vermont