Service Description: This application was created to support the Mapping of Existing Vegetation on Tongass- Prince of Wales Island. Includes attributes for Dominance Type, Canopy Cover, Tree Size, QMD and TPA.

Service ItemId: 528c2a319caf4fd7abad17aed4a9dd11

Has Versioned Data: false

Max Record Count: 2000

Supported query Formats: JSON

Supports applyEdits with GlobalIds: True

Supports Shared Templates: True

All Layers and Tables

Layers:

• PrinceOfWales_ExistingVegetation_2019_UpdatedStructure (2)

Description:

The Prince of Wales Existing Vegetation mapping project encompasses over 4.2 million acres of Southeastern Alaska—2.3 million of which are terrestrial. This map was designed to be consistent with the standards established in the Existing Vegetation Classification and Technical Guide (Nelson et al. 2015), and to provide baseline information to support project planning and inform land management of the Prince of Wales and surrounding islands. The final map comprises seven distinct, integrated feature layers: 1) vegetation type; 2) tree canopy cover; 3) trees per acre (TPA) for trees ≥ 1’ tall; 4) trees per acre for trees ≥ 6” diameter at breast height (dbh);  5) quadratic mean diameter (QMD) for trees ≥ 2” dbh; 6) quadratic mean diameter for trees ≥ 9” dbh; and 7) thematic tree size. The dominance type map consists of 18 classes, including 15 vegetation classes and 3 other land cover types. Continuous tree canopy cover, TPA, QMD, and thematic tree size was developed for areas classified as forest on the final vegetation type map layer. Geospatial data, including remotely sensed imagery, topographic data, and climate information, were assembled to classify vegetation and produce the maps. A semi-automated image segmentation process was used to develop the modeling units (mapping polygons), which delineate homogeneous areas of land cover. Field plots containing thematic vegetation type and tree size information were used as reference for random forest prediction models. Important model drivers included 30 cm orthoimagery collected during the height of the 2019 growing season, in addition to Sentinel 2 and Landsat 8 satellite imagery, for vegetation type prediction.  Additionally, detailed tree inventory data were collected at precise field locations to develop forest metrics for Quality Level 1 (QL1) Light Detection and Ranging (LiDAR) data. LiDAR information was acquired across approximately 80% of the project’s land area. Continuous tree canopy cover and 2^nd order forest metrics (TPA and QMD) were modeled across the LiDAR coverage area, and subsequently, extrapolated to the full project extent using Interferometric Synthetic Aperture Radar (IfSAR) as the primary topographic data source. <o:p></o:p>

Copyright Text: USDA-USFS-R10-GTAC

Spatial Reference: 26931 (26931)

Initial Extent:

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Spatial Reference: 26931 (26931)

Full Extent:

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Spatial Reference: 26931 (26931)

Units: esriMeters

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Supported Operations:   Query   ConvertFormat   Get Estimates   Create Replica   Synchronize Replica   Unregister Replica