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A powerful data extraction tool that intuitively streamlines and simplifies the exploration of more than 100 datasets within NASA’s Earth Observing System Data and Information System (EOSDIS) now has expanded to include its first two datasets from the U.S. Geological Survey (USGS).

A visualization of data from the NASA AppEEARS data extraction tool
AppEEARS time series graphs of eMODIS Smoothed NDVI (top) and SSEBop Evapotranspiration (bottom) for a point extraction at a grassland site in California (center). The two datasets were queried simultaneously and the request completed in 16 seconds.(Public domain.)

In what’s being called a “win-win situation” for both agencies, the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), developed by NASA’s Land Processes Distributed Active Archive Center (LP DAAC), went live with the two USGS datasets on Oct. 12, 2018.

For the first time, researchers wanting to use AppEEARS to sample data for various points on the planet—or larger areas, for that matter—will have access to these important datasets developed at the USGS Earth Resources Observation and Science (EROS) Center. Those wanting to know how the country’s vegetation is doing in fairly quick fashion can access the USGS’ smoothed weekly eMODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index (NDVI). Or if they’re interested in water consumption, they can get the MODIS Operational Simplified Surface Energy Balance (SSEBop) Evapotranspiration (ET) product that’s run globally for the Famine Early Warning Systems Network (FEWS NET).

“It’s a good collaboration story,” Tom Maiersperger, the AppEEARS principal investigator at EROS, said of the partnership with USGS. “These have been very important datasets for USGS EROS, and they are land relevant, which is our focus, too.”

Reaching the larger scientific community

Scientists at USGS EROS had been talking for some time about ways to develop a tool that would broaden access to datasets they were using for scientific studies but weren’t reaching the larger science community outside the Center. The expedited MODIS NDVI product, or eMODIS, was one of those datasets, EROS Scientist Jess Brown said. To better characterize such things as vegetation health, and the start and end of growing seasons across time, EROS staff has cleaned up and smoothed weekly raw data used for NDVI. That eliminates a lot of the atmospheric effects, making it a much better dataset for, say, monitoring drought, Brown said.

A proposal in 2017 to Landsat Remote Sensing (LRS) brought in some dollars to explore the possibility of making such a tool to enable the use of smoothed eMODIS NDVI outside the Center. But the cost was high. As Brown and others at EROS discussed their options, the conversation turned to AppEEARS.

“This is when it’s good that we talk with each other out here, and ideas get thrown around,” Brown said. “(AppEEARS was) getting going, releasing new datasets. And as we had communications with the AppEEARS team, we could see that this was something that would be good for us. I mean, it really does represent a nice collaboration across the building, I think.”

Like Brown, EROS Scientist Gabriel Senay saw an opportunity with AppEEARS for his MODIS global SSEBop ET project. Senay likes the fact that the extraction tool is easily accessible for users and allows them to quickly analyze the data, leading to more exploration and what he calls the generation of additional hypotheses.

“This tool will help us examine the behavior of the model results over time in the far corners of the world, not only for users but for ourselves,” Senay said. “And we can compare it to other similar products or ancillary data, such as elevation, climate, and land cover.”

Ensuring data interoperability

The challenge for AppEEARS with adding the two USGS datasets to more than 100 others from numerous EOSDIS DAACs—as well as NASA’s National Snow and Ice Data Center (NSIDC) DAAC, and the Socioeconomic Data and Applications Center (SEDAC)—is ensuring data interoperability, Maiersperger said.

For the USGS, allowing for interoperability with its datasets meant spending time and money up front to prepare its datasets in a way that made them easy to integrate with the other data already in AppEEARS. The USGS scientists also had to find a platform to house the datasets, and that’s where collaboration at the Center rose to the occasion again. Working with the Landsat and Sentinel Archive and Access (LSAA) team at EROS, Brown and Senay found an archive platform that would accommodate the back-end reprocessing of the low-resolution data used for smoothed eMODIS NDVI and the MODIS SSEBop ET and make them operational within AppEEARS.

With LSAA “providing the storage and some of the back-end infrastructure … it really is kind of a three-way partnership” at the Center, Maiersperger said.

A simple way to to access and prepare data

What does all that mean for users? For one, AppEEARS upholds the promise of a simple, efficient way to access and prepare data by enabling those users to download only the data they need from multiple datasets—in some cases, reducing what needs to be downloaded by up to 99.99 percent.

With its growing number of datasets, AppEEARS also offers the ability to consider multiple variables in the sampling of points or areas through a time series—from environmental variables derived from data collected by MODIS aboard NASA’s Terra and Aqua Earth-observing satellites, to socioeconomic variables from SEDAC’s Gridded Population of the World (GPW) Version 4 collection.

In Brown’s case, anyone interested in seeing how the country’s vegetation is doing quickly and regularly, without doing all the work themselves, could tap into the smoothed eMODIS NDVI now in AppEEARS. She knows, for example, that the wildlife community in the Western U.S. is interested in the eMODIS dataset, especially for those people who follow animals like deer and elk that are tied to foraging on rangelands.

“That community has really adopted MODIS NDVI,” Brown said. “As they hear about eMODIS and the smoothed NDVI, I think (AppEEARS) will be a good resource tool for them.”

Maiersperger said it was always the LP DAAC’s vision to build a framework and capability that wasn’t just specific to one dataset or a collection of similar datasets from a certain sensor or mission. It’s been nice to expand beyond niche applications and capabilities with a growing number of datasets, he added, and to do so in an integrated way.

“We’ve got everything under the same umbrella, and with sort of the same view, even if it’s across very different kinds of datasets,” Maiersperger said. “And people, our users, seem to be really jazzed about this. It really has been tremendously popular, and that popularity just seems to keep growing.”

Brown believes AppEEARS could be a good fit for other datasets at EROS as well. “Certainly, there’s not one tool out there that does everything for everybody. But AppEEARS seems to do a lot,” Brown said. Because it does, she sees more datasets being added from the DAACs, USGS, and elsewhere as only benefitting users going forward.

“AppEEARS does a lot,” Brown said. “Especially once it has more of a sort of time component to it, both with Gabriel’s data and my data, and a lot of MODIS datasets that are in there. These things that are repeated, that move and change through time … I think AppEEARS has a really strong ability to look at all of those and to put that data out for people in a very valuable way.”

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