Rangeland Brush Estimation Tool (RaBET): An Operational Remote Sensing-Based Application for Quantifying Woody Cover on Western Rangelands

Much of the western United States is covered by rangelands used for grazing and wildlife. Woody plant cover is increasing in areas historically covered by grasslands and can cause numerous problems, including losses in wildlife habitat, forage for grazing, and overall losses in soil health. Land man...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-11, Vol.15 (21), p.5102
Main Authors: Holifield Collins, Chandra, Skirvin, Susan, Kautz, Mark, Winston, Zachary, Curley, Dustin, Corrales, Andrew, Bishop, Andrew, Bishop, Nadine, Norton, Cynthia, Ponce-Campos, Guillermo, Armendariz, Gerardo, Metz, Loretta, Heilman, Philip, van Leeuwen, Willem
Format: Article
Language:English
Subjects:
Agriculture
Arizona
Canopies
Ecosystems
Environmentalists
Government agencies
Grasses
Grasslands
Grazing
Land management
Landsat
Landsat satellites
Machine learning
Managers
Natural resources
Phenology
Photography
Range ecology
Rangelands
Remote sensing
Texas
Time series
Vegetation
vegetation maps
Wildlife
Wildlife conservation
Wildlife habitats
Wildlife management
woody cover
Woody plants
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Much of the western United States is covered by rangelands used for grazing and wildlife. Woody plant cover is increasing in areas historically covered by grasslands and can cause numerous problems, including losses in wildlife habitat, forage for grazing, and overall losses in soil health. Land managers and conservationists are working to control these increases in woody plants, but need tools to help determine target areas to focus efforts and resources where they are most needed. In this work, we present RaBET (Rangeland Brush Estimation Tool), which uses transparent, well-understood methodologies with remotely sensed data to map woody canopy cover across large areas of rangelands. We demonstrate that our process produced more accurate results than two currently available tools based on advanced machine learning techniques. We compare two methods of map validation: traditional field methods of plant canopy measurements; and aircraft-based photography, which decreases the amount of time and resources needed. RaBET is a remote sensing-based application for obtaining repeatable, accurate measures of woody cover to aid land managers and conservationists in the control of woody plants on rangelands.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15215102