Services Directory Login

Hawaii_tree_canopy_WTL1 (Map Service)


View In:    ArcGIS JavaScript   ArcGIS.com   WMTS  

Current Version: 10.81

Service Description:

The USDA Forest Service (USFS) builds multiple versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass CONUS, Coastal Alaska, Hawaii, U.S. Virgin Islands andPuerto Rico. There are three versions of data within the 2016 TCC Product Suite, which include:

  • The initial model outputs referred to as the Analytical data;

  • A masked version of the initial output referred to as Cartographic data;

  • And a modified version built for the National Land Cover Database and referred to as NLCD data, which includes a canopy cover change dataset derived from subtraction of datasets for the nominal years of 2011 and 2016.

The Analytical data are the initial model outputs generated in the production workflow. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the nominal years of 2011 and 2016 are available.

The Cartographic products mask the initial model outputs to improve the visual appearance of the datasets. These data are best suited for users who prioritize visual appearance of the data for cartographic and illustrative purposes. Datasets for the nominal years of 2011 and 2016 are available.

The NLCD data are the result of further processing of the masked data. The goal was to generate three coordinated components. The components are (1) a dataset for the nominal year of 2011, (2) a dataset for the nominal year of 2016, and (3) a dataset that captures the change in canopy cover between the two nominal years of 2011 and 2016. For the NLCD data, the three components meet the criterion of “2011 TCC + change in TCC = 2016 TCC”. These NLCD data are best suited for users who require a coordinated three-component data stack where each pixel’s values meet the criterion of “2011 TCC + change in TCC = 2016 TCC”. Datasets for the nominal years of 2011 and 2016 are available, as well as a dataset that captures the change (loss or gain) in canopy cover between those two nominal years of 2011 and 2016, in areas where change was identified.

These tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms, as listed below:

Analytical

Cartographic

NLCD

The Hawaii TCC 2016 NLCD dataset is comprised of a single layer. The pixel values range from 0 to 98 percent. The background is represented by the value 255. The dataset has data gaps due to consistent clouds/shadows in the Landsat images used for modeling. These data gaps are represented by the value 127.



Map Name: Map

Legend

All Layers and Tables

Layers: Tables: Description:

The USDA Forest Service (USFS) builds multiple versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass CONUS, Coastal Alaska, Hawaii, U.S. Virgin Islands andPuerto Rico. There are three versions of data within the 2016 TCC Product Suite, which include:

  • The initial model outputs referred to as the Analytical data;

  • A masked version of the initial output referred to as Cartographic data;

  • And a modified version built for the National Land Cover Database and referred to as NLCD data, which includes a canopy cover change dataset derived from subtraction of datasets for the nominal years of 2011 and 2016.

The Analytical data are the initial model outputs generated in the production workflow. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the nominal years of 2011 and 2016 are available.

The Cartographic products mask the initial model outputs to improve the visual appearance of the datasets. These data are best suited for users who prioritize visual appearance of the data for cartographic and illustrative purposes. Datasets for the nominal years of 2011 and 2016 are available.

The NLCD data are the result of further processing of the masked data. The goal was to generate three coordinated components. The components are (1) a dataset for the nominal year of 2011, (2) a dataset for the nominal year of 2016, and (3) a dataset that captures the change in canopy cover between the two nominal years of 2011 and 2016. For the NLCD data, the three components meet the criterion of “2011 TCC + change in TCC = 2016 TCC”. These NLCD data are best suited for users who require a coordinated three-component data stack where each pixel’s values meet the criterion of “2011 TCC + change in TCC = 2016 TCC”. Datasets for the nominal years of 2011 and 2016 are available, as well as a dataset that captures the change (loss or gain) in canopy cover between those two nominal years of 2011 and 2016, in areas where change was identified.

These tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms, as listed below:

Analytical

Cartographic

NLCD

The Hawaii TCC 2016 NLCD dataset is comprised of a single layer. The pixel values range from 0 to 98 percent. The background is represented by the value 255. The dataset has data gaps due to consistent clouds/shadows in the Landsat images used for modeling. These data gaps are represented by the value 127.



Copyright Text: Funding for this project was provided by the U.S. Forest Service (USFS). RedCastle Resources, Inc. produced the dataset under contract to the USFS Geospatial Technology and Applications Center.

Spatial Reference:
102100

Single Fused Map Cache: true

Capabilities: Map,TilesOnly,Tilemap

Tile Info:
Initial Extent:
Full Extent:
Min Scale: 4622324.434309
Max Scale: 72223.81928599995

Min LOD: 6
Max LOD: 12

Units: esriMeters

Supported Image Format Types: Mixed

Export Tiles Allowed: false
Max Export Tiles Count: 100000

Document Info: