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NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRSDate not supplied

Growing Beyond Earth: Student Citizen Science Contributing to Space Crop Production

Fairchild Tropical Botanic Garden and NASA have been partnering since 2015 to conduct a citizen science education program for middle and high school students called Growing Beyond Earth (GBE). Growing Beyond Earth is a multi-classroom science project designed to advance NASA’s research on growing plants in space. GBE was implemented locally and scaled nationally under two NASA Grants. Now serving more than 250 schools and over 10,000 middle and high school students nationwide, GBE successfully improved STEM education. It also contributed student-generated data to NASA, improving NASA research on the ground and on ISS, with two student-selected crops grown in space. GBE is unique in its focus on real scientific research, enabling student “citizen scientists” to contribute data toward NASA mission planning. Each classroom receives a Fairchild-designed plant habitat analogous to the plant growing equipment aboard the International Space Station (ISS). Fairchild and NASA scientists train teachers to conduct in-classroom GBE experiments, and students then share experimental data online with NASA. As NASA looks toward a long-term human presence beyond Earth’s orbit, there are specific science, technology, engineering, and math challenges related to food production in space. During this presentation, learn how GBE is addressing those challenges by expanding the diversity and quality of edible plants that can be grown aboard spacecraft. We will share the significant scientific and educational results that have come out of this partnership and explain how we quickly pivoted to allow students to continue to contribute during the COVID-era. Finally, we will explain how on Earth, GBE is also advancing technologies for growing plants in urban, indoor, and other resource-limited settings through the GBE Maker challenge for High School, University, and Professional communities of Makers across the country to develop the next generation of space crop production technologies. These programs are supported by NASA.

Growing Beyond Earth↗

NASA NTRS2020

Identifying Hurricane Impacts on Barbuda Using Citizen Science Ground Observations, Drone Photography and Satellite Imagery

Barbuda is a low-lying leeward island in the West Indies. In September 2017 Hurricane Irma battered the island with 185 mph winds. Damage to housing and infrastructure was so extensive that all 1800 residents of the island were immediately evacuated post hurricane to the neighboring island of Antigua. Our research is focused on documenting and analyzing the landscape scale changes that took place on the island as a result of the hurricane using a nested methodology. Ground level observations were recorded using a beta version of the Global Learning and Observation to Benefit the Environment (GLOBE) Observer Land Cover tool. Aerial photographs provide medium scale landscape resolution. Satellite images were processed to provide NDVI values. We describe how nested data at several spatial scales enable detailed description of Hurricane Irma’s impact across the landscape of this 62 sq. mile island. Here we are connecting observations at different spatial scales, using citizen science observations, aerial drone photography and satellite imagery to document and analyze hurricane impacts on the island of Barbuda, eastern Caribbean.

Barbuda↗

NASA NTRS2020

Spitzer Follow-up of Extremely Cold Brown Dwarfs Discovered by the Backyard Worlds: Planet 9 Citizen Science Project

We present Spitzer follow-up imaging of 95 candidate extremely cold brown dwarfs discovered by the Backyard Worlds: Planet 9 citizen science project, which uses visually perceived motion in multi epoch Wide-field Infrared Survey Explorer(WISE)images to identify previously unrecognized substellar neighbors to the Sun. We measure Spitzer[3.6]–[4.5]color to photo type our brown dwarf candidates, with an emphasis on pinpointing the coldest and closest Y dwarfs within our sample. The combination of WISE and Spitzer astrometry provides quantitative confirmation of the transverse motion of 75 of our discoveries. Nine of our motion-confirmed objects have best-fit linear motions larger than 1′′yr−1; our fastest-moving discovery is WISEA J155349.96+693355.2(μ≈215 yr−1),a possible T-type sub dwarf. We also report a newly discovered wide-separation(∼400 au)T8 comoving companion to the white dwarf LSPM J0055+5948(the fourth such system to be found), plus a candidate late T companion to the white dwarf LSR J0002+6357 at 55 projected separation(∼8700 au if associated). Among our motion-confirmed targets, five have Spitzer colors most consistent with spectral type Y. Four of these five have exceptionally red Spitzer colors suggesting types of Y1 or later, adding considerably to the small sample of known objects in this especially valuable low-temperature regime. Our Y dwarf candidates begin bridging the gap between the bulk of the Y dwarf population and the coldest known brown dwarf.

Y dwarfs↗

NASA NTRS2023

Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1, and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors, such as cloud cover, precipitation, and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season, such as in the monsoon dominated South Asia or the Pacific Northwestern region of the USA. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of their volume change with a statistical significant uncertainty that is less than the expected volume in South Asia. In North America, this statistically significant uncertainty in volume estimation was found to be around 50% in lakes eastward of the 108th meridian with lowest uncertainty found in lakes along the East coast of the USA. The article provides a baseline for understanding the current state of the art in estimating volumetric change of lakes and wetlands using citizen science in anticipation of the recently launched Surface Water and Ocean Topography Mission.

Shahzaib Khan↗

NASA NTRS2016

CosmoQuest: Better Citizen Science Through Education

In the modern era, NASA SMD missions and facilities are producing data at a rate too great for the science community to maximally utilize. While software can help, what is really needed is additional eyes, hands, and minds - help we can find in the form of citizen scientist volunteers. The CosmoQuest virtual research facility has demonstrated through published research results that classroom students and the public can, with proper training and support from Subject Matter Experts (SMEs), fill roles more traditionally filled by university students. The research question behind CosmoQuest's creation was simple: if students and the public are provided a properly scaffolded experience that mirrors that of researchers, will they come and perform as well as our students? and can they rise up to be research collaborators? In creating CosmoQuest, we started with a core of citizen science portals, educational materials for both students and life-long learners, and collaboration areas. These three primary focuses mirror the research, courses, and collaboration spaces that form the foundation of a university department. We then went on to add the features that make a center stand out - we added seminars in the form of Google Hangouts on Air, planetarium content through our Science on the Half Sphere program, and even the chance to vicariously attend conferences through live blogging by our team members. With this design for a virtual research facility, the answer to our foundational question has been a resounding yes; the public can aid us in doing science provided they are properly trained. To meet the needs of our population we have developed four areas of engagement: research, education, media, and community.

Gay, P. L.↗

NASA NTRS2019

Evaluation of GEOS Total Cloud Fraction with GLOBE Citizen Science Observations and Co-Located Satellite Data

Here we evaluate the total cloud fraction in cycled forecast experiments with the NASA Global Earth Observing System (GEOS) model. Forecasts were run for summer and winter periods of 2017/2018 and compared with ground-based and satellite observations. Citizen science observations from the Global Learning and Observations to Benefit the Environment (GLOBE) Program were matched with MODIS satellite overpasses and geostationary cloud fraction, yielding a dataset of coincident observations for comparison with hourly model output. The observations indicate a model bias toward overcast and clear conditions, with underestimation of intermediate cloud fractions. We investigate underestimation of variance in the sub-grid total water probability density function (PDF) as a possible cause. The PDF determines large-scale cloud fraction as the sub-grid fraction with total water exceeding the saturation specific humidity. We conduct model experiments in which the shape, width, and spatial dependence of the PDF are varied, and consider the impacts on cloud fraction relative to the combined observations.

Starke, Matthew↗

NASA NTRS2018

General Aviation Citizen Science Study to Help Tackle Remote Sensing of Harmful Algal Blooms (HABs)

We present a new, low-cost approach, based on volunteer pilots conducting high-resolution aerial imaging, to help document the onset, growth, and outbreak of harmful algal blooms (HABs) and related water quality issues in central and western Lake Erie. In this model study, volunteer private pilots acting as citizen scientists frequently flew over 200 mi of Lake Erie coastline, its islands, and freshwater estuaries, taking high-quality aerial photographs and videos. The photographs were taken in the nadir (vertical) position in red, green, and blue (RGB) and near-infrared (NIR) every 5 s with rugged, commercially available built-in Global Positioning System (GPS) cameras. The high-definition (HD) videos in 1080p format were taken continuously in an oblique forward direction. The unobstructed, georeferenced, high-resolution images, and HD videos can provide an early warning of ensuing HAB events to coastal communities and freshwater resource managers. The scientists and academic researchers can use the data to compliment a collection of in situ water measurements, matching satellite imagery, and help develop advanced airborne instrumentation, and validation of their algorithms. This data may help develop empirical models, which may lead to the next steps in predicting a HAB event as some watershed observed events changed the water quality such as particle size, sedimentation, color, mineralogy, and turbidity delivered to the Lake site. This paper shows the efficacy and scalability of citizen science (CS) aerial imaging as a complimentary tool for rapid emergency response in HABs monitoring, land and vegetation management, and scientific studies. This study can serve as a model for monitoring/management of freshwater and marine aquatic systems.

Ansari, Rafat R.↗

NASA NTRS2017

The First Brown Dwarf Discovered by the Backyard Worlds: Planet 9 Citizen Science Project

The Wide-field Infrared Survey Explorer (WISE) is a powerful tool for finding nearby brown dwarfs and searching for new planets in the outer solar system, especially with the incorporation of NEOWISE and NEOWISE Reactivation data. However, so far, searches for brown dwarfs in WISE data have yet to take advantage of the full depth of the WISE images. To efficiently search this unexplored space via visual inspection, we have launched anew citizen science project, called "Backyard Worlds: Planet 9," which asks volunteers to examine short animations composed of difference images constructed from time-resolved WISE co adds. We report the first new substellar object discovered by this project, WISEA J110125.95+540052.8, a T5.5 brown dwarf located approximately 34 pc from the Sun with a total proper motion of approx.0. "7/ yr. WISEA J110125.95+540052.8 has a WISE W2 magnitude of W2 = 15.37+/- 0.09; our sensitivity to this source demonstrates the ability of citizen scientists to identify moving objects via visual inspection that are 0.9 mag fainter than the W2 single-exposure sensitivity, a threshold that has limited prior motion-based brown dwarf searches with WISE.

Wide-field Infrared Survey Explorer (WISE)↗

NASA NTRS2019

A 3 Gyr White Dwarf with Warm Dust Discovered via the Backyard Worlds: Planet 9 Citizen Science Project

Infrared excesses due to dusty disks have been observed orbiting white dwarfs with effective temperatures between 7200 and 25,000 K, suggesting that the rate of tidal disruption of minor bodies massive enough to create a coherent disk declines sharply beyond 1 Gyr after white dwarf formation. We report the discovery that the candidate white dwarf LSPM J0207+3331, via the Backyard Worlds: Planet 9 citizen science project and Keck Observatory follow-up spectroscopy, is hydrogen dominated with a luminous compact disk (L IR/L star = 14%) and an effective temperature nearly 1000 K cooler than any known white dwarf with an infrared excess. The discovery of this object places the latest time for large-scale tidal disruption events to occur at ~3 Gyr past the formation of the host white dwarf, making new demands of dynamical models for planetesimal perturbation and disruption around post-main-sequence planetary systems. Curiously, the mid-infrared photometry of the disk cannot be fully explained by a geometrically thin, optically thick dust disk as seen for other dusty white dwarfs, but requires a second ring of dust near the white dwarf's Roche radius. In the process of confirming this discovery, we found that careful measurements of WISE source positions can reveal when infrared excesses for white dwarfs are co-moving with their hosts, helping distinguish them from confusion noise.

Debes, John H.↗

NASA NTRS2020

WISE 2150-7520AB: A Very Low-mass, Wide Comoving Brown Dwarf System Discovered through the Citizen Science Project Backyard Worlds: Planet 9

We report the discovery of WISE 2150-7520AB (W2150AB): a widely separated (∼341 au) very low-mass L1 + T8 co-moving system. The system consists of the previously known L1 primary 2MASS J21501592-7520367 and a newly discovered T8 secondary found at position 21:50:18.99–75:20:54.6 (MJD = 57947) using Wide-field Infrared Survey Explorer data via the Backyard Worlds: Planet 9 citizen science project. We present Spitzer ch1 and ch2 photometry (ch1–ch2 = 1.41 ± 0.04 mag) of the secondary and Folded-port InfraRed Echellette prism spectra of both components. The sources show no peculiar spectral or photometric signatures, indicating that each component is likely field age. Using all observed data and the Gaia DR2 parallax of 41.3593 ± 0.2799 mas for W2150A we deduce fundamental parameters of log(L(bol)/L(☉)) = −3.69 ± 0.01, T(eff) = 2118 ± 62 K, and an estimated mass = 72 ± 12 M(Jup) for the L1 and log(L(bol)/L(☉)) = −5.64 ± 0.02, T(eff) = 719 ± 61 K, and an estimated mass = 34 ± 22 M(Jup) for the T8. At a physical separation of ∼341 au this system has E(bin) = 1041 erg, making it the lowest binding energy system of any pair with M(tot) < 0.1 M(Sun) not associated with a young cluster. It is equivalent in estimated mass ratio, E(bin), and physical separation to the ∼2 Myr M7.25 + M8.25 binary brown dwarf 2MASS J11011926-7732383AB (2M1101AB) found in the Chameleon star-forming region. W2150AB is the widest companion system yet observed in the field where the primary is an L dwarf or later.

Jacqueline Faherty↗

NASA NTRS2021

New Candidate Extreme T Subdwarfs from the Backyard Worlds: Planet 9 Citizen Science Project

Schneider et al. presented the discovery of WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5, which appear to be the first examples of extreme T-type subdwarfs (esdTs; metallicity ≤−1 dex, T(eff) ≲ 1400 K). Here, we present new discoveries and follow-up of three T-type subdwarf candidates, with an eye toward expanding the sample of such objects with very low metallicity and extraordinarily high kinematics, properties that suggest membership in the Galactic halo. Keck/NIRES near-infrared spectroscopy of WISEA J155349.96+693355.2, a fast-moving object discovered by the Backyard Worlds: Planet 9 citizen science project, confirms that it is a mid-T subdwarf. With H(W2) = 22.3 mag, WISEA J155349.96+693355.2 has the largest W2 reduced proper motion among all spectroscopically confirmed L and T subdwarfs, suggesting that it may be kinematically extreme. Nevertheless, our modeling of the WISEA J155349.96+693355.2 near-infrared spectrum indicates that its metallicity is only mildly subsolar. In analyzing the J155349.96+693355.2 spectrum, we present a new grid of low-temperature, low-metallicity model atmosphere spectra. We also present the discoveries of two new esdT candidates, CWISE J073844.52−664334.6 and CWISE J221706.28−145437.6, based on their large motions and colors similar to those of the two known esdT objects. Finding more esdT examples is a critical step toward mapping out the spectral sequence and observational properties of this newly identified population.

Aaron M. Meisner↗

NASA NTRSDate not supplied

Hot on the Trail: Mapping Wildland Fires With Citizen Science and Live Image Processing

Heightened fire activity is straining existing firefighting resources and budgets across the nation and worldwide. For this reason, the 2021 NASA Academy at Langley Research Center has the challenge of applying NASA technology to the challenges faced by wild-land firefighting professionals. The approach is three-fold: Data Acquisition, Communications, and Equipment Development. The Communications Team focused on improving data latency for fire mapping and advancing communications between civilians and incident dispatch. The team developed two main concepts to address these areas: First, they tried to identify, map, and transmit fire perimeter data via an Uncrewed Aerial System (UAS), and second, they suggest a fully functioning web-app for early fire detection and fire monitoring using citizen science. This report outlines the materials and methods of these concepts, as well as future work necessary to bring the proposed technology into the field.

UAS data transfer ground stations↗

NASA NTRS2021

Colorado River Basin Water Resources: Pairing Phenology Citizen Science Observations with NASA Earth Observations to Monitor Riparian Vegetation

Native plant species in the Colorado River Basin are currently threatened by non-native species that are changing resource competition dynamics. Monitoring native species is essential for understanding changes in plant health throughout the year as well as how species’ distributions change inter-annually. However, current monitoring of species is limited to local efforts and cannot be efficiently conducted across more extensive regions of the basin. Project partners, including the USA National Phenology Network, United States Geological Survey, and Educating Children Outdoors, provided data and on-the-ground expertise to assist the project. NASA Earth observations, including Landsat 8 Operational Land Imager (OLI), Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and Sentinel-2 MultiSpectral Instrument (MSI) from the European Space Agency, provided remote sensing data that covers the large spatial extent of the basin. This study combined both data sources over the study period of 2013 – 2019 and explored the relationship between on-the-ground phenology observations and remotely sensed phenology signals. The team found that pairing the datasets required spatial coordinates to be accurately logged and that it was necessary to have consistent observations throughout the year by citizen scientists. The team found promising relationships between phenology observations and the two vegetation indices, normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), when study locations were in an area with a high proportion of vegetation within a satellite pixel. The results and methods outlined in this study create new opportunities to leverage remote sensing alongside citizen science data for widespread monitoring of non-native species.

Tyler Pantle↗

NASA NTRSDate not supplied

Citizen Science Approach for Searching and Curating Literature of the Effects of Spaceflight on Cardiovascular Outcomes in Rodents and Humans

The spaceflight environment causes significant changes to the structure and function of the cardiovascular system, including fluid redistribution, alterations in blood pressure, and changes in cardiac output. The goal of this project is to quantitatively summarize the data on the effects of actual or simulated microgravity and radiation exposure resulting from spaceflight on the cardiovascular system. As the first step, a group of investigators approached through a collaboration of the Ames Life Science Data Archive (ALSDA) Analysis Working Group developed a list of relevant cardiovascular search terms. Based on these, medical librarians generated and executed the search strategy in Medline, CINAHL, Embase and NASA repositories. In parallel, we recruited students and young professionals from various space industry-affiliated organizations, resulting in ~100 individuals joining. With this program we aimed to reach students and young people underrepresented in STEM, including first-generation, female, minorities, disadvantaged backgrounds, fostered individuals, etc. These individuals completed a virtual training course on the nature and methodologies of the project. Following this, the participants were structured into teams with more senior/experienced individuals designated as team leaders. Currently, the teams are screening approximately 15,000 studies using the systematic review tool, Covidence. Teams will be extracting and curating data for meta-analysis of the cardiovascular spaceflight literature, but also extracting, submitting, and curating appropriate datasets into the new ALSDA submission portal and repository. This effort will result in collaborative publications based upon the literature meta-analyses, and a number of publicly accessible datasets for reuse, modeling, machine learning, and knowledge graph-type approaches. This approach reduces the length of time to complete title/abstract screening time from 1-2 years needed for this volume of studies, to 3-4 months, while also providing a unique, open-access educational experience to space research and training in knowledge synthesis tools to interested individuals.

space biology↗

NASA NTRS2018

A 3D Citizen Science Video Game for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network aimed at accurately assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. We present here the active learning component of the project, which consists of an interactive video game prototype for tablet and mobile devices where players are able to intuitively label morphology classifications over mm-scale 3D coral reef imagery. Active learning applications present a novel methodology for engaging the public while efficiently providing large-scale training and test data for increasingly complex and data-intensive machine learning algorithms. NeMO-Net trains players on domain-specific knowledge through interactive tutorials and periodically checks players' input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide personalized classification training. Players can rate the classifications of other players, unlock rewards and join a global community as they explore and classify coral reefs and other shallow marine environments.

Citizen Science↗

NASA NTRS2021

GLOBE Observer and the GO on a Trail Data Challenge: A Citizen Science Approach to Generating a Global Land Cover Land Use Reference Dataset

Land cover and land use are highly visible indicators of climate change and human disruption to natural processes. While land cover is frequently monitored over a large area using satellite data, ground-based reference data is valuable as a comparison point. The NASA-funded GLOBE Observer (GO) program provides volunteer-collected land cover photos tagged with location, date and time, and, in some cases, land cover type. When making a full land cover observation, volunteers take six photos of the site, one facing north, south, east, and west (N-S-E-W) respectively, one pointing straight up to capture canopy and sky, and one pointing down to document ground cover. Together, the photos document a 100 meter square of land. Volunteers may then optionally tag each N-S-E-W photo with the land cover types present. Volunteers collect the data through a smartphone app, also called GLOBE Observer, resulting in consistent data. While land cover data collected through GLOBE Observer is ongoing, this paper presents the results of a data challenge held between June 1 and October 15, 2019. Called “GO on a Trail,” the challenge focused on collecting land cover observations at designated points along the Lewis and Clark National Historic Trail (LCNHT), which transects approximately 7,900 kilometers of the United States from east to west. The challenge also included an international component in which participants were recognized for the most data collected during the period. The challenge resulted in more than 2800 land cover data points from around the world with just over 900 land cover data points along the LCNHT. The data collected along the LCNHT is largely within a 1,000 meter corridor along the historic route. Internationally, the challenge had strong participation in Australia, where a Scouts Australia team-based competition was conducted in conjunction with GO on a Trail. GLOBE Observer collections can serve as reference data, ground truthing satellite imagery for the improvement and verification of broad land cover maps. Continued collection using this protocol will build a database documenting climate-related land cover and land use change into the future.

land cover↗

NASA NTRS2015

Citizen Science

Scientists and engineers constantly face new challenges, despite myriad advances in computing. More sets of data are collected today from earth and sky than there is time or resources available to carefully analyze them. Some problems either don't have fast algorithms to solve them or have solutions that must be found among millions of options, a situation akin to finding a needle in a haystack. But all hope is not lost: advances in technology and the Internet have empowered the general public to participate in the scientific process via individual computational resources and brain cognition, which isn't matched by any machine. Citizen scientists are volunteers who perform scientific work by making observations, collecting and disseminating data, making measurements, and analyzing or interpreting data without necessarily having any scientific training. In so doing, individuals from all over the world can contribute to science in ways that wouldn't have been otherwise possible.

distributed computing↗