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Ecosystems/USFS_EDW_TCA_Drought (ImageServer)

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Service Description:

Direct Download (Raster Data Gateway)

Objective: Characterize current moisture deficit and surplus relative to the long-term average.

Data: The indicator represents areas of moisture deficit as a z-score. A z-score is a statistical method for assessing how different a value (i.e., most recent 3 years) is from the mean (historical average). The source climate data is from PRISM. Mean moisture values were derived from historical data on precipitation and Thornthwaite potential evapotranspiration, from 1900 to t-minus 4 (t = current TCA Assessment year). The greater the negative z-value, the larger the departure from average conditions, indicating larger moisture deficits.

These data highlight regions of moisture deficit as a z-score calculated from the reference time period and current conditions. There is a lag between the assessment year and the most recent drought data, for example, the 2024 TCA Assessment used 2021-2023 to represent current conditions and 1900-2020 for the reference time period. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding landscape (LTA).

Data Format: Raster data are continuous

Units: Mean difference in z-score

Spatial Resolution: 4000m (4km)

Source data: PRISM; z-score calculations provided by the USFS Office of Sustainability and Climate based on the methods found here: https://www.fs.usda.gov/research/treesearch/43361

Additional Resources:

Details on Method Changes and Source Data Versions

Overview of the Terrestrial Condition Assessment: TCA Hubsite or Landfire Office Hour Presentation

Explore the results of the most recent assessment: TCA Interactive Data Viewer

Learn more about the TCA KPI: Dashboard link when available



Name: Ecosystems/USFS_EDW_TCA_Drought

Description:

Direct Download (Raster Data Gateway)

Objective: Characterize current moisture deficit and surplus relative to the long-term average.

Data: The indicator represents areas of moisture deficit as a z-score. A z-score is a statistical method for assessing how different a value (i.e., most recent 3 years) is from the mean (historical average). The source climate data is from PRISM. Mean moisture values were derived from historical data on precipitation and Thornthwaite potential evapotranspiration, from 1900 to t-minus 4 (t = current TCA Assessment year). The greater the negative z-value, the larger the departure from average conditions, indicating larger moisture deficits.

These data highlight regions of moisture deficit as a z-score calculated from the reference time period and current conditions. There is a lag between the assessment year and the most recent drought data, for example, the 2024 TCA Assessment used 2021-2023 to represent current conditions and 1900-2020 for the reference time period. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding landscape (LTA).

Data Format: Raster data are continuous

Units: Mean difference in z-score

Spatial Resolution: 4000m (4km)

Source data: PRISM; z-score calculations provided by the USFS Office of Sustainability and Climate based on the methods found here: https://www.fs.usda.gov/research/treesearch/43361

Additional Resources:

Details on Method Changes and Source Data Versions

Overview of the Terrestrial Condition Assessment: TCA Hubsite or Landfire Office Hour Presentation

Explore the results of the most recent assessment: TCA Interactive Data Viewer

Learn more about the TCA KPI: TCA Dashboard

*if you have trouble viewing the Dashboard, please submit a Tableau Viewer Access Request



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Time Info: Pixel Size X: 4000.0

Pixel Size Y: 4000.0

Band Count: 1

Pixel Type: F32

RasterFunction Infos: {"rasterFunctionInfos": [ { "help": "", "name": "None", "description": "Make a Raster or Raster Dataset into a Function Raster Dataset." }, { "help": "", "name": "Drought", "description": "A raster function template." } ]}

Mensuration Capabilities: Basic

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : true

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: USDA - GEO; USDA - USFS – GO

Service Data Type: esriImageServiceDataTypeScientific

Min Values: -3.9039897918701172

Max Values: 5.3067703247070312

Mean Values: 1.0253613377932191

Standard Deviation Values: 1.3080319133456524

Object ID Field: objectid

Fields: Default Mosaic Method: ByAttribute

Allowed Mosaic Methods: ByAttribute,NorthWest,Center,LockRaster,Nadir,Viewpoint,Seamline,None

SortField: StdTime

SortValue: 0

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: 1000

Max Image Height: 100000

Max Image Width: 100000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: N/A

Ownership Based AccessControl For Rasters: N/A

Child Resources:   Info   Histograms   Statistics   Key Properties   Legend   Raster Function Infos   Multidimensional Info   Slices

Supported Operations:   Export Image   Query   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query GPS Info   Find Images   Image to Map   Map to Image   Measure from Image   Image to Map Multiray   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project