Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software
Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.
Citation Information
Publication Year | 2017 |
---|---|
Title | Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software |
DOI | 10.1016/j.jag.2017.03.009 |
Authors | Amanda M. West, Paul H. Evangelista, Catherine S. Jarnevich, Sunil Kumar, Aaron Swallow, Matthew Luizza, Steve Chignell |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | International Journal of Applied Earth Observation and Geoinformation |
Index ID | 70190024 |
Record Source | USGS Publications Warehouse |
USGS Organization | Fort Collins Science Center |
Related Content
Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014
Related Content
- Data
Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014
This data bundle contains some of the inputs, all of the processing instructions and all outputs from two VisTrails/SAHM workflow. These models specifically include field data of locations with >40% cover of cheatgrass (presence) and - Connect