USFS Analytical 2016 Tree Canopy Cover Coastal AK (Image Service)
dataset
posted on 2024-10-01, 13:04authored byU.S. Forest Service
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 and Puerto 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 USFS Tree Canopy Cover Datasets USFS Enterprise Data Warehouse Cartographic USFS Tree Canopy Cover Datasets NLCD Multi-Resolution Land Characteristics (MRLC) Consortium USFS Enterprise Data Warehouse The Coastal Alaska TCC 2016 NLCD dataset is comprised of a single layer. The pixel values range from 0 to 91 percent. The background is represented by the value 255. Data gaps (which are explained in more detail below) are represented by the value 127.The NLCD data include three components: 2011 NLCD TCC, 2016 NLCD TCC, and 2011-to-2016 change in TCC. For nearly all pixels, the values meet the criterion of 2011 TCC + change in TCC = 2016 TCC. However, there are some pixels with no TCC values because of a lack of imagery in persistently cloudy areas. These data gaps were given a value 127. In summary, if a data gap was present in the original 2011 or 2016 data, that data gap was carried through to all three components of the NLCD data. Recall that the three NLCD components (2011 NLCD TCC, 2016 NLCD TCC, and change between the two nominal years) are intended to coordinate and line up. The USFS's GTAC also makes available the original 2011 and 2016 TCC datasets (prior to development of any integrated data stack for NLCD) that are output as part of the production workflows. If a user would like the original datasets for the nominal years of 2011 and 2016 (prior to integrating into a common data stack for NLCD), they should visit https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/and download the FS-Cartographic version of the 2011 and/or 2016 datasets for their cartographic applications.
This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: