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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Building Climate Resilience at NASA Ames

NASA Ames Research Center, located at the southern end of the San Francisco Bay (SFB) estuary has identified three primary vulnerabilities to changes in climate. The Ames Climate Adaptation Science Investigator (CASI) workgroup has studied each of these challenges to operations and the potential exposure of infrastructure and employees to an increased frequency of hazards. Sea level rise inundation scenarios for the SFB Area generally refer to projected scenarios in mean sea level rather than changes in extreme tides that could occur during future storm conditions. In the Summer of 2014, high resolution 3-D mapping of the low lying portion of Ames was performed. Those data are integrated with improved sea level inundation scenarios to identify the buildings, basements and drainage systems potentially affected. We will also identify the impacts of sea level and storm surge effects on transportation to and from the Center. This information will help Center Management develop future Master Plans. Climate change will also lead to changes in temperature, storm frequency and intensity. These changes have potential impacts on localized floods and ecosystems, as well as on electricity and water availability. Over the coming decades, these changes are going to be imposed on top of ongoing land use and land cover changes, especially those deriving from continued urbanization and increase in impervious surface areas. These coupled changes have the potential to create a series of cascading impacts on ecosystems, including changes in primary productivity and disturbance of hydrological properties and increased flood risk.The majority of the electricity used at Ames is supplied by hydroelectric dams, which will be influenced by reductions in precipitation or changes in the timing or phase of precipitation which reduces snow pack. Coupled with increased demand for summertime air conditioning and other cooling needs, NASA Ames is at risk for electricity shortfalls. To assess the anticipated energy usage as climate changes, the Ames CASI team is collecting historical energy usage data from Ames facilities, historical weather data, and projected future weather parameters from the CASI Climate subgroup. This data will be incorporated into the RETScreen model to predict how energy usage at Ames will change over the coming century.

climate↗
DOE OSTI2024

Optimizing DOE Opportunities to Research Land–Atmosphere Interactions in the U.S. Southeast (Workshop Report)

The southeastern United States (Southeast), with its complex and varied environments, is an area of tremendous economic, ecological, and societal importance to the country. The region is characterized by heterogeneous landscapes (i.e., geology and soil type) and a long history of human land use coupled with a warm temperature regime and high precipitation. As a result, soil erosion and deposition are pronounced, vegetation recovery is rapid, and human modification is extensive across the region. To better understand land–atmosphere interactions in this important and complex region, research communities supported by the U.S. Department of Energy’s Biological and Environmental Research (BER) program identified the Southeast as a priority region of interest. In fall 2024, the third Atmospheric Radiation Measurement Mobile Facility (AMF3), one of three mobile monitoring facilities designed to collect atmospheric and climate data from undersampled regions around the world, will begin operations in northwestern Alabama’s Bankhead National Forest (BNF). The AMF3-BNF 5-year deployment, from 2024–2029, will monitor the effects of feedbacks among aerosols, clouds, and precipitation on plant physiology and canopy-scale fluxes. It will also focus on scale aggregation to resolve the role of local forcing on larger-scale processes. To enable broader AMF3 involvement by the science community, the BER Environmental System Science (ESS) program organized the Southeast Land– Atmosphere Research Opportunities (SELARO) workshop in August 2023. The purpose was to identify gaps in scientific understanding of terrestrial processes in the Southeast (defined as states bounded by the Gulf of Mexico to the south, the Atlantic Ocean to east, the Mississippi River to the west, and extending through Tennessee and North Carolina to the north) and explore opportunities to use the AMF3-BNF deployment to coordinate and leverage research efforts across the region. Many parts of the Southeast have experienced repeated anthropogenic forcings. Farming, hunting, burning, and settlement of the region by Indigenous Peoples first shaped the distribution of plant communities, which in turn influenced European colonization patterns. Timber harvesting was common during the expansion of European settlements, and production forestry continues today. Agricultural production was extensive and then waned through the 20th century, creating a period of afforestation following agricultural abandonment. Today, many formerly agricultural landscapes are undergoing rapid urbanization and suburbanization. Overlying these patterns of anthropogenic land use are frequent disturbances from hurricanes, tornadoes, wildfires, drought, flooding, ice storms, and the occasional blizzard. An additional characteristic of the Southeast is its overall landscape complexity. Unlike the western United States, where broad expanses may share similar characteristics, Southeast topography, drainage patterns, vegetation, and development patterns vary widely across relatively small spatial scales (<1 km). This is due to the region’s underlying geology and soil development, species biodiversity patterns, and land ownership and use coupled with strong forces of erosion, weathering, and rapid plant growth in the warm, wet climate.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Research on the application of satellite remote sensing to local, state, regional and national programs involved with resource management and environmental quality

A program designed to involve state, regional and local agency personnel in the application of remote sensing is reported. During this period fifteen applications projects were initiated in support of twenty-five separate state, county and municipal agencies or entities. Eight of the projects were completed with positive results which aided the agencies involved. These results included information which contributed to decisions on: (1) selection of a route for a scenic parkway, (2) policy development on open land use, (3) policy related to urban development, (4) a major reservoir project by a governor's staff, (5) control tactics and damage assessment during flooding conditions on the Kansas and Missouri rivers, and (6) initiating a program of habitat inventory by remote sensing by the Kansas Forestry, Fish and Game Commission.

Barr, B. G.↗
NASA NTRS2017

Increasing Resiliency to Extreme Weather

We work at NASA's Goddard Institute for Space Studies, integrating the agency's satellite imagery and projections of extreme weather events into urban planning. In recent weeks, we have watched as Christian's hometown, Houston, has been ransacked by historic rainfall and flooding and Hurricane Irma has battered the U.S. Virgin Islands, Puerto Rico and Florida. Then, Hurricane Maria devastated Puerto Rico leaving millions of people without power. Sea-level rise, storm surge, warm ocean temperatures, and extreme rainfall interacted to exacerbate the damages incurred by Hurricanes Harvey, Irma, and Maria. Coastal flooding combined with inland flooding to wreak extraordinary havoc.

Rosenzweig, Cynthia↗
DOE OSTI2024

Anthropogenic effects on flood hazards in a hyper-arid watershed: The 2015 Atacama floods

An unprecedented precipitation event in the hyper-arid Atacama Desert of Northern Chile occurred in March 2015. Geomorphic alterations to the river channel and the coastal zone, coupled with the exceptional magnitude of the rainfall, caused catastrophic damage and loss of life. On the coast of the El Salado watershed, legacy mine tailings infilled the watershed-ocean connection, while the river channel was altered both by tailings and urbanization. The consequences of this event resulted from the coupling of anthropogenic geomorphic changes with an unusual climate event. Lack of field data, complex geomorphology and sediment loads influenced by human activity make analysing floods in these regions especially challenging. The objective of this work is to improve our understanding of the factors that control flood hazards by using numerical simulations to reconstruct the 2015 flood in El Salado. We carry out unsteady two-dimensional simulations fully coupled with the sediment concentration to identify the influence of tailing deposits, considering high-resolution data of the pre- and post-2015 flood topography. In conclusion, the results highlight the importance of specific event-based studies, using models that can help designing better strategies for climate change adaptation and risk mitigation, while providing information for risk reduction and channel restoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗
NASA NTRS1978

Land Use Planning

Computer technology, aerial photography and space imagery are being combined in a NASA community services program designed to help solve land use and natural resource planning problems. As urban areas grow, so grows the need for comprehensive, up-to-date information on which to base intelligent decisions regarding land use. State and local planners need information such as the nature of urban change, where the changes are occurring, how they affect public safety, transportation, the economy, tax assessment, sewer systems, water quality, flood hazard, noise impact and a great variety of other considerations. Most importantly they need continually updated maps. Preparing timely maps, gathering the essential data and maintaining it in orderly fashion are becoming matters of increasing difficulty. The NASA project, which has nationwide potential for improving efficiency in the planning process, is a pilot program focused on Tacoma, Washington and surrounding Pierce County. Its key element, developed by Jet Propulsion Laboratory (JPL), is a computerized Land Use Management Information System (LUMIS).

Source record↗
DOE OSTI2026

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗
DOE OSTI2023

Coast-Urban-Rural Atmospheric Gradient Experiment

Accurately representing the climate and weather variability within cities and providing well-tested representations of the impacts of urban systems on the atmospheric environment are challenges for current earth system models (ESMs). Field data for testing and developing these models are critical to addressing these limitations. The Atmospheric Radiation Measurement (ARM) user facility will support a field campaign aimed at understanding how different surface-atmosphere interactions around a city are influencing its climate. The Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) is expected to operate from December 2024 to November 2025 in and around Baltimore, Maryland. With its aging infrastructure, growing susceptibility to heat and flooding, and ongoing issues with air and water pollution, Baltimore is characteristic of many large industrial cities in the Eastern United States. ARM, a U.S. Department of Energy (DOE) Office of Science user facility, plans to deploy one of its three mobile observatories at Morgan State University’s Clifton Park site in downtown Baltimore. Ancillary ARM sites are also planned for rural Maryland, northwest of the city; and to the southern end of Kent Island in Chesapeake Bay. Data from CoURAGE will complement measurements from the Baltimore Social-Environmental Collaborative (BSEC), one of four DOE Urban Integrated Field Laboratories that will operate in cities across the United States to study urban climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

What Caused the August 2002 Catastrophic Floods in Central Europe?

The catastrophic August 2002 floods in central Europe followed very intense rains over a span of several days, reported over a large region. On Aug. 12 meteorological stations over an elongated swath, from the vicinity of Saltzburg (Austria) in the south to the vicinity of Berlin in the north, reported precipitation exceeding 100 mm/day. Synoptic analysis points to a jet streak in the mid-Atlantic. moving eastward, which reached Spain on about 9th of August. An understanding of the mechanism that ultimately produced the unprecedented rains was derived conveniently from the GEOS 3 Model developed at NASA Goddard Space Flight Center. Examining the scenarios of omega, we observe on Aug. 10, OOZ, a center of ascending vertical motions, stronger than 0.6 Pa/s at the 700 hPa level over the western Mediterranean. Advecting moist and warm air to higher levels from the near-ocean level, the center moved eastward, reaching the northern Adriatic on Aug. 11, OOZ, then continuing northeast to the regions where most intense precipitation was reported on Aug. 12. The omega at 850 hPa shows a closely similar pattern but especially interesting is the 850 omega pattern on Aug. 12, 12Z, which shows descending motions stronger than 0.4 Pa/s over the eastern Po Valley (northern Italy), and an elongated region of ascending motions stronger than 1.0 Pa/s coinciding in extent with the extreme-precipitation region on that day. At that time, the cyclone which formed over the Po Valley, was centered on eastern Czech Republic, producing on its western side these strong ascending motions over the precipitation region. The pattern of the surface-pressure lows provides further insight into the processes, and specifically, the Aug. 12,06Z map, shows a 996 mb low over the western Czech Republic. The flooding following the extreme rains was acerbated by the fact that river-channels were made narrower over the recent decades by the urbanization of river banks.

Otterman, J.↗
NASA NTRS2018

Enhancing New York City's Resilience to Sea Level Rise and Increased Coastal Flooding

The large population and major economic assets along New York City's extensive waterfront face exposure to sea level rise (SLR) and coastal flooding. The New York City Panel on Climate Change (NPCC), an advisory group of academic and private-sector experts, provides the city with scientific guidance on future climate risks. Here we highlight current NPCC research on sea level rise, coastal flooding, with some of the City's current and planned responses.Twentieth century SLR in New York City (2.8 cm/decade) exceeded the global average (1.2-1.9 cm/decade), underscoring a greater regional risk. In 2015, the NPCC projected a 2080s SLR of 46-99 cm relative to 2000-2004 (25th -75th percentile) at the Battery, with high-end SLR estimates (90th percentile) of 1.9 m by 2100. Growing evidence of potential instability of the West Antarctic Ice Sheet (WAIS) suggests the possibility of even higher future sea levels. We therefore present a new low probability, yet high impact SLR scenario for New York City, which incorporates these ice sheet instabilities. The new SLR projections will be combined with coastal flood return period curves for the 100-year storm flood levels. Related ongoing research examines changes in storm characteristics, surge--sea level rise interactions, and mapping of neighborhoods at risk.Guided by NPCC findings, New York City undertakes programs to strengthen coastal defenses, tailored to specific neighborhood needs. NPCC in collaboration with the city, continues to investigate vulnerability to extreme climate events, such as inland floods and coastal storms, and to develop stronger links with community-based stakeholder groups. New York City's plans to enhance coastal urban resiliency stand as a model for other urban coastal centers as they prepare for climate change.

Gornitz, Vivien↗
NASA NTRSDate not supplied

Airborne Observations of Aerosol Properties in Southeast Asia: Overview of Emissions, Cloud Processing, and Long Range Transport during NASA CAMP2Ex

The Southwest Monsoon represents an important synoptic scale meteorological feature that modulates precipitation throughout Southeast Asia. In addition, southwesterly flow can funnel large amounts of biomass burning aerosol into heavily populated areas throughout the Philippines, mixing with urban emissions and representing a significant air quality issue. From a climate perspective, understanding interactions between these particles and clouds has important societal ramifications through frequent extreme periods of flood and drought. Here we present airborne observations made in support of the NASA CAMP2Ex (Cloud and Aerosol Monsoonal Processes-Philippines Experiment) mission aboard the Wallops Flight Facility P-3 research aircraft, based at Clark International Airport in the Luzon region of Northern Philippines. Nineteen research flights were conducted in August-October of 2019. An extensive suite of aerosol microphysical, optical, and chemical instrumentation was deployed, along with trace gas and remote sensing measurements, to characterize aerosol emissions and their vertical/spatial variability associated with moderately convective marine cloud systems in the region. Analysis will focus on characterizing disparate aerosol sources with respect to derived chemical and optical properties relevant to global circulation modeling. For example, higher than expected mass scattering efficiencies for aged biomass burning emissions, derived from a combination of nephelometer and aerosol mass spectrometer measurements, are attributed to increased particle size and decreased density. Results will also illustrate the evolution of aerosols from Indonesian agricultural biomass burning activities into the Philippines region, in comparison with urban emissions from the megacity Manila and transported air masses from mainland Asia.

Luke David Ziemba↗
NASA NTRS1975

Urban construction and safety project

The purpose and functions of NASA technology applications temas (TAT) are described, with emphasis on the activities of the Urban and Construction and Safety Project. The transfer and implementation of technology is discussed in five activities. Topics include: flat conductor cable, NASA house and compendium, flood insurance studies, tornado studies, and the controller for stationary diesels.

Source record↗
NASA NTRS2007

TRMM's Contribution to Our Knowledge of Climatology, Storms and Floods

The Tropical Rainfall Measuring Mission (TRMM) has successfully completed nearly ten years in orbit. A brief review of the history and accomplishments of this joint mission between the U.S. and Japan is presented. Research highlights will focus on the seasonal cycle of a TRMM-based rainfall climatology, which takes advantage of the multiple rain estimates available from TRMM. Examples will be given of the use of TRMM data to diagnose the impact of man on precipitation patterns through urbanization and the effect of pollution. Use of TRMM data for tropical cyclone operational analysis in the U.S. will also be shown. Methods for generating 3-hourly rainfall information from multiple satellites using TRMM to calibrate all the information will be described as will application of such information to study extreme rainfall events and associated floods and landslides. These results will emphasize the breadth of science success achieved with the 10-year record of observations from the only rain radar and passive microwave instrument combination in space. The outlook for continued operation of the TRMM satellite and progress in TRMM science and applications will be addressed.

Adler, Robert↗
DOE OSTI2023

Microbiome response in an urban river system is dominated by seasonality over wastewater treatment upgrades

Background: Microorganisms such as coliform-forming bacteria are commonly used to assess freshwater quality for drinking and recreational use. However, such organisms do not exist in isolation; they exist within the context of dynamic, interactive microbial communities which vary through space and time. Elucidating spatiotemporal microbial dynamics is imperative for discriminating robust community changes from ephemeral ecological trends, and for improving our overall understanding of the relationship between microbial communities and ecosystem health. We conducted a seven-year (2013–2019) microbial time-series investigation in the Chicago Area Waterways (CAWS): an urban river system which, in 2016, experienced substantial upgrades to disinfection processes at two wastewater reclamation plants (WRPs) that discharge into the CAWS and improved stormwater capture, to improve river water quality and reduce flooding. Using culture-independent and culture-dependent approaches, we compared CAWS microbial ecology before and after the intervention. Results: Examinations of time-resolved beta distances between WRP-adjacent sites showed that community similarity measures were often consistent with the spatial orientation of site locations to one another and to the WRP outfalls. Fecal coliform results suggested that upgrades reduced coliform-associated bacteria in the effluent and the downstream river community. However, examinations of whole community changes through time suggest that the upgrades did little to affect overall riverine community dynamics, which instead were overwhelmingly driven by yearly patterns consistent with seasonality. Conclusions: This study presents a systematic effort to combine 16S rRNA gene amplicon sequencing with traditional culture-based methods to evaluate the influence of treatment innovations and systems upgrades on the microbiome of the Chicago Area Waterway System, representing the longest and most comprehensive characterization of the microbiome of an urban waterway yet attempted. We found that the systems upgrades were successful in improving specific water quality measures immediately downstream of wastewater outflows. Additionally, we found that the implementation of the water quality improvement measures to the river system did not disrupt the overall dynamics of the downstream microbial community, which remained heavily influenced by seasonal trends. Such results emphasize the dynamic nature of microbiomes in open environmental systems such as the CAWS, but also suggest that the seasonal oscillations remain consistent even when perturbed.

16S rRNA gene sequencing↗
NASA NTRSDate not supplied

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as the optical and SAR data proves high resolution (5-10 m) imagery, and SAR data is unaffected by cloud cover and light availability (day vs. night), which are common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a MODIS snow mask product to mask global snow coverage, which would affect land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd watershed located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management..

Lori Berberian↗
NASA NTRS2023

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management.

Inundation↗
NASA NTRSDate not supplied

FloodPlanet: High-Resolution Commercial Imagery for Training and Validation of Deep Learning-Based Models of Inundation Extent

Flooding events are becoming increasingly frequent worldwide and are known to cause extensive damage. Public optical and radar satellite imagery can be used to detect large areas of inundation in rural areas, however, long revisit times and coarse spatial resolution limit applications for short-lived events and urban areas. Commercial constellations such as those operated by Planet offer increased spatial and temporal resolution and can supplement mapping efforts to provide more information to disaster response, relief, and mitigation efforts. Deep learning requires high quality labeled data for training across coincident sensors. The FloodPlanet dataset presented here contains labeled surface water for 18 events across the world based on Planetscope imagery with coincident Harmonized Landsat Sentinel-2 ( HLS) or Sentinel-1 and builds upon the previously existing Sen1Floods11, xBD, and NASA Sentinel-1 datasets. Sen1Floods11 includes 4,831 512x512 pixel overlapping tiles of coincident Sentinel-1 and Sentinel-2 data observing 11 flood events across the world from 2017-2019. The dataset contains a combination of automated and hand-labeled surface water for use in training and validation of inundation modeling efforts. The xBD dataset identifies flood-damaged buildings and indicates the scale of damage to each (none, minor, moderate, and major) from four flood events which occurred in the United States, India, Nepal, and Bangladesh from the same time period. The NASA dataset contains hand-labeled water bodies observed in Sentinel-1 imagery during five flood events within the 2017-2019 period. The effort presented here utilizes observations from these previously investigated flood events to generate labels of surface water at the 3-5m spatial resolution provided by Planetscope and facilitate the comparison between public and commercial data. A data pipeline was built which uses clustering algorithms to pick the most suitable overlapping chips between the public data and PlanetScope data for manual labeling. Labels were created manually using NASA’s ImageLabeler tool and include areas of high- and low-confidence water. The high confidence designation is reserved for areas of open, unobstructed water while low confidence is used for areas of suspected water beneath vegetation, clouds, or cloud shadows. Expected to be released in late 2022, the FloodPlanet dataset will include tiled imagery with a unique ID for each 1024x1024 pixel tile, 7 bands of HLS data, and high- and low-confidence flood labels in both shapefile and tiff formats. The authors will follow Spatial Temporal Access Catalog (STAC) guidelines to release FloodPlanet on the Radiant Earth ML hub, which hosts public datasets for machine learning.

Alexander Melancon↗