Weeding the West: Monitoring Invasives using NASA Earth Observations

Category: Identifying Invasive Species Extent & Critical Species Habitat
Project Team: Southwest U.S. Ecological Forecasting
Team Location: NASA Langley Research Center – Hampton, Virginia

A multispectral classification using Bands 2-7 and Band 9 for two Landsat dates. Classes in red highlight grassland areas susceptible to cheatgrass. Image Credit: Southwest U.S. Ecological Forecasting Team

A multispectral classification using Bands 2-7 and Band 9 for two Landsat dates. Classes in red highlight grassland areas susceptible to cheatgrass. Image Credit: Southwest U.S. Ecological Forecasting Team

Authors:
Ryan Avery
Katherine Landesman
Jordan Vaa
Timmera Whaley
Dakoyta Greenman

Mentors/Advisors:
Dr. Kenton Ross (NASA Langley Research Center)

Past/Other Contributors:
Emily Gotschalk (Center Lead)
Tyler Rhodes (Center Lead)

Abstract:

The southwestern United States spans six states, more than 55 national parks, and a wide range of ecosystems, historical landmarks, and culturally significant landscapes. Of these parks, Bandelier National Monument in New Mexico (NM), Big Bend National Park (Texas), Glen Canyon National Recreation Area (Arizona, Utah), and Valles Caldera National Preserve (NM) are threatened by three particularly problematic invasive plant species: cheatgrass (Bromus tectorum), ravenna grass (Saccharum ravennae), and giant reed (Arundo donax). Currently, park management uses field observations to monitor these species, which requires a significant investment in time, effort, and money by the National Park Service (NPS). The NPS is interested in mapping and predicting the presence of invasive species by using NASA’s Earth observations. To this end, the Southwest U.S. Ecological Forecasting team created classified species distribution maps using Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI) data for the years 2000, 2008, and 2016. This project also used vegetation and topographic indices, as well as field data to predict invasive species presence using a Species Distribution Model (SDM) for each national park area and generated likelihood maps of species presence/absence.

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