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VEGETATION MAPPING FOR LANDFIRE National Implementation.

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Presentation on theme: "VEGETATION MAPPING FOR LANDFIRE National Implementation."— Presentation transcript:

1 VEGETATION MAPPING FOR LANDFIRE National Implementation

2  Existing vegetation type data layers  % Canopy Cover (separate for tree, shrub, and herbaceous data layers; binned)  Vegetation height (separate for tree, shrub, and herbaceous data layers; binned) Vegetation Dataset Deliverables

3 LANDFIRE Vegetation Mapping Data Requirements at EDC n LANDSAT ETM+ data (mosaics of three image dates; from MRLC) n Digital elevation model data (and derivatives; from 30m Elevation Derivatives for National Applications (EDNA)) n Preliminary classification products (from MRLC/NLCD) n Percent forest canopy cover data (from MRLC/NLCD) n High-quality field data (Map Attribute Table plot data from FIA, SCA, GAP, others) n Biophysical gradients (select list) and Biophysical settings data Major Requirements

4 Step 1. QA/QC of Field Data by Mappers n Isolate 2% of sample plots for traditional accuracy assessment using 3x3 k, 2% block design (do not use for map generation) n Identification of questionable plots – Identify 1990’s-2000’s NDVI difference values likely to represent plots of change – Identify plots very close to roads – Identify plots that do not match NLCD life forms n Visually assess questionable plots on imagery n If still questionable, flag plots in data base and do not use for map development

5 Example of Overlay of Points onto Imagery for QA/QC

6 Zone 16 Plot QA/QC Results n Started with 7293 plots n 956 had no EVT information n 135 plots withheld for accuracy assessment n 6202 plots used for life form modeling n 1474 plots excluded for vegetation type mapping (about from EROS analysis) n 4728 plots used for vegetation type mapping (65% points used for analysis)

7 Step 2. Vegetation Type Mapping; Part 1 n Extract digital values from spatial data layers using field plots that passed QA/QC inspection process n Generate life-form data mask (tree, shrub, herbaceous) using decision tree (Life-form field included in LFRDB) n Inspect cross-validation values/error matrices of mask n Develop additional data layers as needed (e.g., wetlands, other vegetation groupings)

8 Step 2. Vegetation Type Mapping; Part 2 n Run decision tree models separately for forest, shrub, and herbaceous life forms using all appropriate data (imagery, DEM and derivatives, BpG, BpS, wetlands) n Generate and inspect life-form specific cross-validation error matrices as well as spatial outputs (QA) n Assess impact of rare classes (decide to drop or keep) n Apply water, urban, agriculture masks (from NLCD) to vegetation type data layers n Merge life-form specific cover types into a single vegetation type data layer

9 Biophysical Gradient Data Used for Vegetation Type Mapping n Soil Depth n Degree Days n Daily Precipitation n Relative Humidity n Shortwave Radiation Flux Density n Maximum Temperature n Minimum Temperature n Nighttime Average Temp n Incoming Shortwave Radiation n Maximum Projected LAI – Forest and Grass Models n Potential Evapotranspiration – Forest and Grass Models n Soil Water Fraction – Forest and Grass Models n Growing Season Water Stress – Forest and Grass Models n Actual Evapotranspiration – Forest and Grass Models n Soil Water Potential – Grass Model

10 Summer ETM+ Image Mosaic Lifeform Mask Created Using Imagery and DEM Comparison Between Imagery and Lifeform Mask

11 LANDFIRE Forest Class Cross-Validation Error Matrix Reference Data Classified As

12 Key Cross Validation Numbers; Utah Highlands n 3-Lifeform Classification: 92% n 6-Lifeform Classification: 89% n Forest Classes: 78% n Shrub Classes: 78% n Herbaceous Classes: 65%

13 Vegetation Type Map; Utah Highlands

14 Step 3a. Canopy Cover; Trees n Create training set of forest canopy cover using high res orthophoto or satellite imagery (NLCD) n Establish relationship between Landsat and training data using regression tree n Apply relationship to generate spatial per-pixel estimates for all pixels n Evaluate error (R) values n Recode tree canopy continuous cover data to cover classes as defined by the Vegetation Working Group n Ensure consistency with EVT; correct when needed n Apply land cover masks: water, urban, agriculture

15 Utah Highlands Binned Forest Canopy Corr. Coef. = 88% (From NLCD) Avg. Error = 9.0%

16 n Extract digital values from spatial layers using field plots that have shrub or herbaceous canopy values n Stratify to life form n Generate life-form specific error values (R) n If R is acceptable, apply regression tree model n Recode shrub/herbaceous canopy continuous cover data to cover classes as defined by the Vegetation Working Group n Ensure consistency with EVT; correct when needed n Apply land cover masks: water, urban, agriculture Step 3b. Canopy Cover; Shrubs/Herbaceous

17 Utah Highlands Binned Shrub Canopy Corr. Coef. = 70% Avg. Error = 11%

18 Utah Highlands Binned Herbaceous Canopy Corr. Coef. = 62% Avg. Error = 12%

19 Utah Highlands Canopy Cover Composited Using Three Lifeform Dataset

20 Step 4. Canopy Height n Assign life-form specific height classes to plots in modified MAT as defined by the Vegetation Working Group n Extract digital values from the spatial data layers, including life-form specific cover types n Run decision tree model separately for the three life forms n Generate life-form specific cross-validation error matrices for height classes n Generate life-form specific height class spatial data using decision tree n Check for errors in the three life form-specific height maps n Mask each height map with water, urban, and agriculture masks

21 Step 4. Canopy Height Height Classes (LANDFIRE Vegetation Working Group) Forest 0-5 Meters 5-10 Meters Meters Meters > 50 Meters Shrub Meters Meters Meters > 3.0 Meters Herbaceous Meters Meters > 1.0 Meters

22 Utah Highlands Structure Stages Tree: Height > 10m, Canopy > 40% Tree: Height > 10m, Canopy <= 40% Tree: Height 40% Tree: Height <= 10m, Canopy <= 40% Shrub: Height > 1m, Canopy > 40% Shrub: Height > 1m, Canopy <= 40% Shrub: Height 40% Shrub: Height <= 1m, Canopy <= 40% Herbaceous: Height > 0.2m, Canopy > 40% Herbaceous: Height > 0.2m, Canopy <= 40% Herbaceous: Height 40% Herbaceous: Height <= 0.2m, Canopy <= 40% Barren land Water Permanent snow and ice Agriculture Residential and commercial lands Utah Existing Structural Stages

23 Utah Highlands Canopy Structure Stage

24 Questions, Comments? For Further Information Visit: Thank You!


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