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Preparations for Next Moonwalk Simulations Underway (and Underwater)

2023 Aeronautics Research Mission Directorate Associate Administrator (AA) Awards

Unmanned Aerial Systems Pilot (UASP) Kit Development Team

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NASA Ames Research Center
Joey Mercer*
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NASA Glenn Research Center
Charles Sheehe
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ASRC Federal Data Solutions, LLC
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Charles Whatley
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2023 AA Award Honorees

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Mar 06, 2024
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      Introduction
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      Animation 1. This visualization shows the change in vegetation in Maryland from January 1 to December 30, 2016, using Normalized Difference Vegetation Index (NDVI) data from Harmonized Landsat Sentinel-2 (HLS). The visualization shows land on both sides of the Chesapeake Bay, where red represents bare soil and green indicates healthy, growing vegetation. Animation credit: Michael Taylor [Science Systems and Applications Inc. (SSAI)], Matthew Radcliff [USRA], and Jeffrey Masek [GSFC]. Caption adapted from Laura Rocchio [SSAI] The Dawn of HLS
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      “HLS meets a need that people have been asking for for a long time,” said Masek.
      What began as a research question with an experimental product evolved into an operational project with the involvement of the Satellite Needs Working Group (SNWG). SNWG is an interagency effort to develop solutions that address Earth observation needs of civilian federal agencies. Every two years, SNWG conducts a survey of federal agencies to see how their work could benefit from satellite data. The answers span the gamut of application areas, from water quality monitoring to disaster recovery to planning how best to protect and use natural resources. SNWG brings these ideas to NASA, USGS, and the National Oceanic and Atmospheric Administration (NOAA) – the three main U.S. government providers of satellite data. These agencies work together to create and implement solutions that serve those needs. NASA plays a critical role in every step of the SNWG process, including leading the assessment of survey responses from over 30 federal agencies, managing and supporting the implementation of identified solutions, and encouraging solution co-design with federal partners to maximize impact.
      The HLS surface reflectance product was an outcome of the very first SNWG solution cycle in 2016. This product was expanded, following additional SNWG requests in 2020 and 2022. The 2020 cycle saw the creation of nine HLS-derived vegetation indices, and the 2022 cycle aimed for a six-hour latency product.
      The U.S. Department of Agriculture (USDA) now uses HLS to map crop emergence at the field scale in the corn belt, allowing farmers to better plan their growing seasons. Ranchers in Colorado use the dataset to decide where to graze their cattle during periods of drought. HLS also informs the use and termination of cover crops in the Chesapeake Bay area. In 2024, the Federal Emergency Management Agency (FEMA) employed HLS to identify where to focus aid in the aftermath of Hurricane Helene.
      A New and Improved HLS
      In the July 2025 issue of Remote Sensing of Environment, a team of researchers outlined the HLS V2.0 surface reflectance dataset and algorithms. The team included seven NASA co-authors, members of the 2018–2023 Landsat Science Team, and ESA. The lead author, Junchang Ju [GSFC—Remote Sensing Scientist], has been the technical lead on HLS since its inception. Co-author Christopher Neigh [GSFC—Landsat 8/9 Project Scientist] is the principal investigator on the HLS project. V2.0, which was completed in Summer 2023, incorporates several major improvements over HLS V1.4, the most recent publicly available HLS product. HLS V1.4 covered about 30% of the global land area, providing data on North America and other select locations. HLS V2.0 provides data at a spatial resolution of 30 m (98 ft) with near-global coverage from 2013 onward. The dataset includes all land masses except Antarctica. HLS V2.0 also has key algorithmic improvements in atmospheric correction, cloud masking, and bidirectional reflectance distribution function (BRDF) correction. Together, these algorithms “harmonize” the data, or ensure that the distinct Landsat and Sentinel-2 datasets can effectively be used interchangeably – see Animation 2.
      Animation 2: The visualization provides the Normalized Difference Vegetation Index (NDVI) data from Harmonized Landsat Sentinel-2 (HLS) for farm fields south of Columbus, NE. The red represents bare soil and green represents healthy, growing vegetation. The animation runs from January 1 to December 30, 2016. Animation credit: Michael Taylor [SSAI], Matthew Radcliff [USRA], and Jeffrey Masek [GSFC]. Caption adapted from Laura Rocchio [SSAI] HLS V2.0 in Action
      The increased frequency of observations improved the ability of the scientific community to track disaster recovery, changes in phenology, agricultural intensification, rapid urban growth, logging, and deforestation. Researchers are already putting these advances to use.
      The land disturbance product (DIST-ALERT) is a global land change monitoring system that uses HLS V2.0 data to track vegetation anomalies in near real-time – see Figure 1. DIST-ALERT captures agricultural expansion, urban growth, fire, flooding, logging, drought, landslides, and other forces of change to vegetation. Amy Pickens [University of Maryland, Department of Geographical Sciences—Assistant Research Professor] said that HLS is the perfect dataset for tracking disturbances because of the frequency of observations.
      DIST-ALERT was created through Observational Products for End-Users from Remote Sensing Analysis (OPERA), a project at NASA/Jet Propulsion Laboratory (JPL). OPERA products respond to agency needs identified by the SNWG. In 2018, SNWG identified tracking surface disturbance as a key need. OPERA partnered with the Global Land Analysis and Discovery (GLAD) lab at University of Maryland to develop the change detection algorithm.
      To track changes in vegetation, the DIST-ALERT system establishes a rolling baseline – meaning that for any given pixel, the vegetation cover is compared against vegetation cover from the same 31-day window in the previous three years. The primary algorithm detects any vegetation loss relative to the established baseline. A secondary algorithm flags any spectral anomaly (i.e., any change in reflectance) compared to that same baseline. This approach ensures that the algorithm catches non-vegetation change (e.g., new building or road projects in unvegetated areas). Used together, these algorithms can identify long-term changes in agricultural expansion, deforestation, and urbanization alongside short-term changes in crop harvest, drought, selective logging, and the impacts of disasters. On average, DIST-ALERT is made available on LP DAAC within six hours of when new HLS data is available. Currently, the dataset does not provide attribution to disturbances.
      Figure 1. In March 2025, wildfires burned through South Korea, resulting in heavy vegetation loss. [left] Output of the DIST-ALERT product on NASA Worldview from May 8, 2025, with vegetation loss in percent flagged with varying levels of confidence. Yellow and red represent areas with confirmed vegetation cover losses of right] Natural-color image captured by the Multi-Spectral Instrument (MSI) aboard Sentinel-2C on May 8, 2025. The large brown burn scar in the center of the image corresponds to vegetation loss detected by DIST-ALERT. It stands in contrast to the surrounding green vegetation. Figure credit: NASA Earthdata Disturbance alerts already exist in some ecosystems. Brazil’s National Institute for Space Research [Instituto Nacional de Pesquisas Espaciais (INPE)] runs two projects that detect deforestation in the Amazon: Programa de Cálculo do Desflorestamento da Amazônia (PRODES) and Sistema de Detecção de Desmatamento em Tempo Real (DETER). The GLAD lab created its own forest loss alerts – GLAD-L and GLAD-S2 – using Landsat and Sentinel-2 data respectively. Global Forest Watch integrates GLAD-L and GLAD-S2 data with Radar for Detecting Deforestation (RADD) observations – derived from synthetic aperture radar data from Copernicus Sentinel-1 – into an integrated deforestation alert.
      The implementation of these alert systems, some of which have been around for decades, have been shown to impact deforestation rates in the tropics. For example, a 2021 study in Nature Climate Change found that deforestation alerts decreased the probability of deforestation in Central Africa by 18% relative to the average 2011–2016 levels.
      DIST-ALERT is distinct from other alert systems in a few ways. First, it has global coverage. Second, the rolling baseline allows for tracking changes in seasonality and disturbances to dynamic ecosystems. When HLS V2.0 data are input to DIST-ALERT, the system is also better at identifying disturbances in cloudy ecosystems than other individual alert systems – because it is more likely to obtain clear observations. This also enables it to identify the start and end of the disturbance more precisely.
      Pickens said that the DIST-ALERT team is already working with end-users who are implementing their data product. She has spoken to some who use the system to help logging companies prove that they are complying with regulations. The U.S. Census Bureau is also using DIST-ALERT to monitor fast-growing communities so that they can do targeted assessments in the interim between the larger decennial census.
      Alongside DIST-ALERT, OPERA has also been developing the Dynamic Surface Water eXtent (DSWx) product suite, which employs HLS to track surface water (e.g., lakes, reservoirs, rivers, and floods) around the globe – see Figure 2. These new products represent the new applications made possible by the HLS interagency and international collaboration.
      Figure 2. The map shows flood extent and estimates of flood depth in areas west of Porto Alegre, Brazil on May 6, 2024. The flood extent is from the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Dynamic Surface Water eXtent product, which uses Harmonized Landsat Sentinel-2 data. The flood depth estimate is from the Floodwater Depth Estimation Tool (FwD ET). The darkest blue areas represent floodwater at least 5 m (20 ft) deep. Much of the inundated floodplain is light blue, which equates to depths of between 0.1–1 m (4–40 in). Figure credit: Lauren Dauphin [NASA’s Earth Observatory], Dinuke Munasinghe [JPL], Sagy Cohen [University of Alabama], and Alexander Handwerger [JPL] Conclusion
      HLS is set to continue improving land monitoring efforts across the globe. Meanwhile, the HLS science team is working to improve the algorithms for a more seamless harmonization of Landsat 8 and 9 and Sentinel-2 data. They are also working to improve the cloud-masking algorithm, have recently released vegetation indices, and are working on developing a low-latency (six-hour) HLS surface reflectance product, all while incorporating user feedback.
      Looking ahead, the launch of future Sentinel and Landsat satellites will further the development of HLS. The additional data and unique capabilities will continue to meet researchers’ need for more frequent, high-quality satellite observations of Earth’s land surface.
      Madeleine Gregory
      NASA’s Goddard Space Flight Center/Science Systems and Applications Inc.
      madeleine.s.gregory@nasa.gov
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      Last Updated Aug 25, 2025 Related Terms
      Earth Science View the full article
    • By NASA
      3 min read
      Preparations for Next Moonwalk Simulations Underway (and Underwater)
      The high-altitude WB-57 aircraft departed July 8, 2025, from Ellington Field in Houston, Texas, headed to the Texas Hill Country. The aircraft will use the DyNAMITE (Day/Night Airborne Motion Imager for Terrestrial Environments) sensor system to take video mosaics of the area to assist with the emergency response effort. Photo Credit: NASA/Morgan Gridley In response to recent flooding near Kerrville, Texas, NASA deployed two aircraft to assist state and local authorities in ongoing recovery operations.

      The aircraft are part of the response from NASA’s Disasters Response Coordination System, which is activated to support emergency response for the flooding and is working closely with the Texas Division of Emergency Management, the Federal Emergency Management Agency (FEMA), and the humanitarian groups Save the Children and GiveDirectly.

      Persistent cloud-cover has made it difficult to obtain clear satellite imagery, so the Disasters Program coordinated with NASA’s Airborne Science Program at NASA’s Johnson Space Flight Center in Houston to conduct a series of flights to gather observations of the impacted regions. NASA is sharing these data directly with emergency response teams to inform their search and rescue efforts and aid decision-making and resource allocation.

      The high-altitude WB-57 aircraft operated by NASA Johnson departed from Ellington Field on July 8 to conduct aerial surveys. The aircraft is equipped with the DyNAMITE (Day/Night Airborne Motion Imager for Terrestrial Environments) sensor.

      The DyNAMITE sensor views the Guadalupe River[KA1] [RC2]  and several miles of the surrounding area, providing high-resolution imagery critical to assessing damage and supporting coordination of ground-based recovery efforts. This system enables real-time collection and analysis of data, enhancing situational awareness and accelerating emergency response times.

      In addition, the agency’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) is flying out of NASA’s Armstrong Flight Research Center in Edwards, California, aboard a Gulfstream III. Managed by the agency’s Jet Propulsion Laboratory in Southern California, the UAVSAR team is planning to collect observations over the Guadalupe, San Gabriel, and Colorado river basins Wednesday, Thursday, and Friday. Because UAVSAR can penetrate vegetation to spot water that optical sensors are unable to detect, the team’s goal is to characterize the extent of flooding to help with understanding the amount of damage within communities.

      Flights are being coordinated with FEMA, the Texas Division of Emergency Management, and local responders to ensure data is quickly delivered to those making decisions on the ground. Imagery collected will be sent to NASA’s Disaster Response Coordination System.

      Additionally, the Disasters Program, which is part of NASA’s Earth Science Division, is working to produce maps and data to assess the location and severity of flooding in the region and damage to buildings and infrastructure. These data are being shared on the NASA Disasters Mapping Portal as they become available.

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      Last Updated Jul 09, 2025 Related Terms
      Earth Applied Sciences Program Earth Science Division Ellington Field Floods General Jet Propulsion Laboratory Johnson Space Center NASA Aircraft NASA Headquarters Science Mission Directorate WB-57 Explore More
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