ArcGIS REST Services Directory Login | Get Token
JSON

Layer: Total Forest Carbon (2018) (ID: 3)

Parent Layer: National Carbon Layers

Name: Total Forest Carbon (2018)

Display Field: ClassName

Type: Raster Layer

Geometry Type: null

Description: The Total Forest Carbon 2018 map was developed by Forest Service scientists using data from FIA plots measured between 2014-2018, in conjunction with remote sensing data. More info is available here - https://usfs.maps.arcgis.com/home/item.html?id=bd3c2c1ba3844ebabd8df6d1c4932387 . This image service was developed using data from over 213,000 national forest inventory plots measured during the period 2014-2018 from the USFS Forest Inventory and Analysis (FIA) program, in conjunction with other auxiliary information. Roughly 4,900 Landsat 8 OLI scenes, collected during the same time period, were processed to extract information about vegetation phenology. This information, along with climatic and topographic raster data, were used in an ecological ordination model of tree species. The model produced a feature space of ecological gradients that was then used to impute FIA plots to pixels. The plots imputed to each pixel were then used to assign values (tons per pixel) for total forest carbon. Carbon Pools can be found - https://usfs.maps.arcgis.com/home/item.html?id=4a604935bdce4a6eb77a967fab47ddff For more information about the methods used to produce this dataset please see the following references: • Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E. 2018. Harmonic regression of Landsat time series for modeling attributes from national forest inventory data. ISPRS Journal of Photogrammetry and Remote Sensing. 137: 29-46. • Wilson, Barry Tyler; Woodall, Christopher W.; Griffith, Douglas M. 2013. Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage. Carbon Balance and Management. 8:1. doi:10.1186/1750-0680-8-1 • Wilson, B. Tyler; Lister, Andrew J.; Riemann, Rachel I. 2012. A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data. Forest Ecology and Management. 271: 182-198. • Ohmann, Janet L.; Gregory, Matthew J. 2002. Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A. Canadian Journal of Forest Research. 32: 725-741 Spatial Extent: CONUSUnits: Short tons per pixel

Copyright Text: USDA Forest Service: Forest Inventory and Analysis (FIA); BIGMAP

Default Visibility: true

MaxRecordCount: 0

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: false

Supports Statistics: false

Has Labels: false

Can Modify Layer: false

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeNone

Type ID Field: null

Fields:
Supported Operations:   Query   Query Attachments   Query Analytic   Generate Renderer   Return Updates

  Iteminfo   Thumbnail   Metadata