TerrAdapt:Cascadia Documentation
TerrAdapt:Cascadia
  • QUICK START GUIDE
  • HOW TO USE TERRADAPT:CASCADIA
    • Public License and Citation
    • Appropriate Uses and Key Limitations
    • TerrAdapt:Cascadia Map Portal
    • TerrAdapt:Cascadia Dashboard
  • DATA INPUTS
    • Data Inputs Overview
    • Remote Sensing Data
    • Climate
    • Energy and Transportation Infrastructure
    • Topography, Hydrology, & Soils
  • METHODS AND VALIDATION
    • Methods Overview
    • Landcover
      • Taxonomy
      • Training Data
      • Covariates
      • Model Development
      • Model Validation
    • Forest Structure
      • Training Data
      • Covariates
      • Model Development
      • Model Validation
    • Rangeland Fractional Cover
      • Training Data
      • Covariates
      • Model Development
      • Model Validation
    • Change Detection and Ecological Disturbance Modeling
      • Taxonomy
      • Covariates
      • Training Data
      • Model Development
    • Human Footprint
    • Habitat
      • Species Distribution Modeling
      • Ecosystem-based Models
      • Core Habitat
      • Habitat Centrality
    • Connectivity
      • Mapping Connectivity Networks
      • Corridors
      • Corridor Centrality
      • Mapping Barriers
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  1. METHODS AND VALIDATION

Rangeland Fractional Cover

Overview

Rangeland fractional cover refers to the percentage of a pixel that is covered in a particular vegetation type found in the arid rangelands of western North America. These fractional rangeland vegetation types vary widely as a function of succession after disturbances like wildfire, and often have profound influences on habitat quality for rangeland-associated species. TerrAdapt:Cascadia currently models fractional cover of 4 rangeland vegetation types, including % sagebrush cover, % shrub cover, % perennial grass cover, and % invasive annual grass cover.

In the following sections, we describe the training data and covariates we used to predict rangeland fractional cover, our approach to developing the models, and model validation.

PreviousModel ValidationNextTraining Data

Last updated 1 year ago

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