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The conception of an invasive species in popular culture is generally tied to living things more mobile than cheatgrass – think zebra mussels in the Missouri River, Asian carp in the Great Lakes, or boa constrictors in Florida’s Everglades.
The motorists who see highway signs that warn anglers to check boats for zebra mussels are unlikely to read a billboard that says “watch out for cheatgrass.”
But invasive grasses represent a real and serious fire risk in the nation’s drylands, particularly in western states. Cheatgrass spreads rapidly, greens up and dies out quickly, leaving the equivalent of kindling spread for miles amid scattered patches of oily, long-burning sagebrush.
Western states are in the throes of the fight against such invasive grasses, and the Western Governor’s Association recently created a working group to fine-tune its attack in areas where the invasive has yet to gain a foothold.
Remote sensing data from the U.S. Geological Survey’s Earth Resources Observation and Science (EROS) Center has offered help in recent years. The National Land Cover Database (NLCD) includes geospatial data products defining the extent of shrub, litter and bare ground in the west at 30-meter resolution, and research teams produce even timelier cheatgrass maps twice a year at 250-meter resolution for the past three years.
Now, thanks to a novel approach to combining data from USGS Landsat and European Space Agency (ESA) Sentinel-2 satellites, those twice-a-year maps will be more detailed, accurate, and useful for the land managers and research teams on the ground.
A new publication, authored by EROS contractor Neal Pastick and co-authored by EROS Scientist Bruce Wylie outlines the new mapping method. It leans on satellite data, on-the-ground measurements, and weekly estimations of Normalized Difference Vegetation Index (NDVI)—a measure of greenness that serves as an indicator of plant health—to produce geospatial maps at a higher resolution than previous efforts.
The maps run from 2016 through the present, stretching across parts of seven states, and are freely available to the public. New maps will be released at middle and end of the current growing season for the foreseeable future.
The research “fills a critical gap in our ability to effectively assess, manage, and monitor drylands by providing a framework that allows for an accurate and timely depiction of land surface phenology and exotic annual grass cover at spatial and temporal resolutions that are meaningful to local resource managers,” according to the publication’s abstract.
Importance of timely, high-resolution mapping
The weekly look is particularly important because vegetation health in drylands is tied more closely to ephemeral moisture than seasonal climate dynamics. The predictable greenness curves of midwestern cultivated croplands or southeastern deciduous forests don’t track with invasive grasses in dryland ecosystems. A sudden soak of rain can produce spikes in greenness that fade within weeks.
That’s why the weekly mapping project began, initially using 250-meter resolution greenness data derived from the MODIS sensors onboard NASA’s Terra and Aqua satellites. Those orbiters allowed researchers to characterize the rapid green-up with near daily readings, something not possible through Landsat (once every 8-16 days) or Sentinel (once every 5-10 days) alone. Combining that higher-resolution data solved that timeliness problem, Pastick said.
“You get observations every three days with Sentinel and Landsat together. With MODIS, it’s one or two days. So here, we get almost the same temporal resolution as we would with MODIS, but at a much finer (spatial) scale,” Pastick said.
Moving from 250- to 30-meter resolution improves the weekly maps considerably, as invasive grass cover can vary within those 250 meters. That’s important to land managers and researchers alike.
Applications for invasive grass maps
Stuart Hardegree, a plant physiologist at the Northwest Watershed Research Center U.S. Department of Agriculture’s Agricultural Research Service, studies invasive grasses from the perspective of elevation, slope, and aspect.
Soil type and climate patterns are often cited as factors in an area’s resistance and resilience to invasive weeds, Hardegree said, but there’s less understanding of the impact other factors can have. On the Boise front range in Idaho, for instance, patterns on the ground seem to tie more closely to elevation and “microclimate” – the climate of a smaller area that differs from that of the areas surrounding it.
“When you’re out in the field, the higher elevation you go, the more native plants hang in. Where you have lower elevation, lower precipitation and higher temperatures - that’s where cheatgrass dominates,” Hardegree said. “Also, if you’re on the north slope, you’re more likely to have native grasses hang in there, while cheatgrass will dominate on the south slope.”
Hardegree is working to parse those observations in greater detail, but finding the data necessary to do so across wide areas has been a challenge. Plugging EROS data into his models could help fill that gap as he moves forward on a multi-year project.
“What I’ve been looking for documentation of weediness as a function of slope, aspect, and elevation, so that when I do my modeling and map microclimatic scenarios over space, I can see whether those metrics are also correlated with weed distribution in areas that have burned enough that the vegetation that’s there now reflects resilience and resistance to weeds.”
Hardegree’s work illustrates just one potential use of the data. Illustrating the extent of cheatgrass alone can offer insight in efforts to manage the issues it causes.
The Center for Sustaining Agriculture and Natural Resources (CSANR) at Washington State University produces profiles of ranchers in the region to highlight potential management practices in the face of climate change. One such profile in the works documents the practices of a ranch family recovering from the impact of the Soda Fire, which burned nearly 280,000 of sagebrush land in 2015.
“The issue of managing cheatgrass, and whether grazing can be one more tool in the toolbox, is part of what some of these science sidebars in this profile are about,” said Sonia Hall of CSANR. “We wanted to provide that visual of cheatgrass and cheatgrass extent.”
The EROS cheatgrass maps, Hall and her co-author Tip Hudson learned, turned out to be the most up-to-date way to offer that visual. They’d initially looked at including a figure from a 2016 EROS publication, but Hall later learned the maps were updated twice a year and open to the public.
“It was significantly newer than what we’d planned on using,” she said.
Further uses of near real time invasive data
The marquee products borne of the cheatgrass mapping project are, of course, the maps themselves. But the NDVI data that will now accompany their release can help scientists study problems beyond invasive species.
The weekly NDVI composites, after all, are essentially greenness indicators for all the vegetation spread across the mapped area. Those offer potential value to a host of work: Phenology studies, for example, which its focus on seasonal life cycles, or drought monitoring projects, many of which have traditionally relied on coarse resolution satellite data from sensors like MODIS.
“There are a lot more uses for this NDVI data than just invasive grasses,” Pastick said.
Devendra Dahal, an EROS contractor and another co-author of the Pastick study, presented initial findings this month during the annual meeting of the Society for Rangeland Management in Denver, Colo. Dahal met with some current users of the 250-meter maps and heard positive feedback and excitement for the possibility of weekly NDVI data.
Cheatgrass maps for 2016-2018 for a smaller portion of the Western U.S. were released in early February, just prior to the publication of Pastick’s paper. Dahal hopes users take some time to check out the upgraded data and offer feedback.
“Everyone can access that right now,” Dahal said.
Data for 2019 and 2020 are expected to arrive in spring, coinciding with previous 250-meter near real time data release schedule.
Download the 2016-2018 data here.
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