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Service Description: Direct Download (Raster Data Gateway)
Objective: Identify locations where vegetation composition and successional stage are departed from the natural range of variation.
Data: Vegetation departure within a TCA landscape ecosystem describes the degree to which the observed proportion (percent, 0-100%) of successional classes (i.e., A through E) derived from Landfire Succession Classes (SClass) dataset, is departed from the proportions one would expect based on the reference condition contained in the Landfire Biophysical Settings (BpS) dataset at each cell location. Departure is calculated as:
Departure = 100 – Similarity
where Similarity = ∑ (min(Ai,Bi)) over all classes i,…n
Departure is determined for each BPS within an LTA, and then weighted average for departure is calculated for the LTA based on the areal extent of the BPS. After being added to the assessment in 2022, the update timeline of the input source data from LANDFIRE did not align with the timing of TCA assessment in 2023, so data from 2022 was reused. The 2024 TCA Assessment used updated source data to create new vegetation departure indicator data.
Units: Percent
Format: Raster data are continuous
Resolution: 30m
Source: Landfire Succession Class and Biophysical Setting, methods from Swaty et al. 2022
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_VegetationDeparture
Description: Direct Download (Raster Data Gateway)
Objective: Identify locations where vegetation composition and successional stage are departed from the natural range of variation.
Data: Vegetation departure within a TCA landscape ecosystem describes the degree to which the observed proportion (percent, 0-100%) of successional classes (i.e., A through E) derived from Landfire Succession Classes (SClass) dataset, is departed from the proportions one would expect based on the reference condition contained in the Landfire Biophysical Settings (BpS) dataset at each cell location. Departure is calculated as:
Departure = 100 – Similarity
where Similarity = ∑ (min(Ai,Bi)) over all classes i,…n
Departure is determined for each BPS within an LTA, and then weighted average for departure is calculated for the LTA based on the areal extent of the BPS. After being added to the assessment in 2022, the update timeline of the input source data from LANDFIRE did not align with the timing of TCA assessment in 2023, so data from 2022 was reused. The 2024 TCA Assessment used updated source data to create new vegetation departure indicator data.
Units: Percent
Format: Raster data are continuous
Resolution: 30m
Source: Landfire Succession Class and Biophysical Setting, methods from Swaty et al. 2022
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
Single Fused Map Cache: false
Extent:
XMin: -1.41402966464E7
YMin: 3167658.6758999974
XMax: -7623396.646400001
YMax: 6690228.675899997
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Initial Extent:
XMin: -1.41402966464E7
YMin: 3167658.6758999974
XMax: -7623396.646400001
YMax: 6690228.675899997
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Full Extent:
XMin: -1.41402966464E7
YMin: 3167658.6758999974
XMax: -7623396.646400001
YMax: 6690228.675899997
Spatial Reference: 102100
(3857)
LatestVCSWkid(0)
Time Info:
Start Time Field: beginyear
End Time Field: endyear
Time Extent:
[2022/01/01 00:00:00 UTC, 2024/01/01 00:00:00 UTC]
Time Reference:
N/A
Pixel Size X: 30.0
Pixel Size Y: 30.0
Band Count: 1
Pixel Type: U8
RasterFunction Infos: {"rasterFunctionInfos": [
{
"help": "",
"name": "None",
"description": "Make a Raster or Raster Dataset into a Function Raster Dataset."
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{
"help": "",
"name": "Vegetation Departure",
"description": "A raster function template."
}
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Mensuration Capabilities: Basic
Inspection Capabilities:
Has Histograms: true
Has Colormap: false
Has Multi Dimensions : true
Rendering Rule:
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Max Scale: 0
Copyright Text: Methods from Swaty, R.; Blankenship, K.; Hall, K.R.; Smith, J.; Dettenmaier, M.; Hagen, S. Assessing Ecosystem Condition: Use and Customization of the Vegetation Departure Metric. Land 2022, 11,28 https://www.mdpi.com/2073-445X/11/1/28; Data from http://www.landfire.gov (S-class and BPS settings, accessed Feb. 6, 2024)
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Standard Deviation Values: 19.853363393673945
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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:
Name: Raster Dataset
Description: Supports all ArcGIS Raster Datasets
Help:
Has Raster Attribute Table: false
Edit Fields Info: N/A
Ownership Based AccessControl For Rasters: N/A
Child Resources:
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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
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Project