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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 NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗
NASA NTRS2018

The Next Generation of NASA Rapid Response: Worldview Snapshots

The NASA Rapid Response system started in 2001 by serving static subsets of Near Real Time MODIS (Moderate Resolution Imaging Spectroradiometer) imagery acquired from the Terra satellite. Over this time, Rapid Response has been used to support near real time applications such as wildfire and sea ice mapping for hundreds of thousands of users. In 2011, the toolset expanded to include GIBS, the Global Imagery Browse Services, which provides a web map tiling service of over 700 imagery products, and Worldview (https://worldview.earthdata.nasa.gov/), an interactive web application that showcases the products available in GIBS. This year a new application, Worldview Snapshots, has been added to complete the toolset by providing a flexible, low bandwidth method to download personalized subsets for those who do not need or cannot use a fully featured web mapping application. The original Rapid Response subset tool has been retired and we thank it for its seventeen years of service. Stop by to learn more about the next generation of NASA Rapid Response.

Rapid response system↗
NASA NTRSDate not supplied

Keeping Up With the Time(s): Advancing NASA’s Worldview to Facilitate Quick Access to Global Near Real-Time Imagery

Striving to keep up with the constantly changing environment, whether physical or computing, NASA Worldview’s interactive web mapping application continues to make improvements to ensure that avenues to near-real time imagery are quick, easy and accessible. This poster will explore recent additions to NASA Worldview and the Global Imagery Browse Services (GIBS) of near real-time imagery and imagery visualizations - from geostationary to flood mapping visualizations; improvements to access to imagery - from granule swath visualizations to vector interactions with fires and other types of vectors; and improvements to imagery discovery - from enhancements to the timeline to providing more ways to locate relevant imagery in the layer picker.

Min Minnie Wong↗
NASA NTRSDate not supplied

Improving Data Discoverability in NASA Worldview for Spatiotemporally Discontinuous Layers

Over the past ten years, NASA Worldview has continually evolved to remain an essential data visualization application for NASA’s archive of Earth Science data. Hosting over 1000 data layers, each with differing spatial and temporal availability, Worldview has addressed challenges with visualizing this data to ensure that the user interface and user experience remained straightforward to use.

Patrick Moulden↗
DOE OSTI2019

Chapter 16 - Simulating Discrete-Event Models in the Classic Worldviews: A New Approach to Simultaneous Events and Parallel Execution

This chapter describes a new approach to the activity scanning worldview of discrete-event simulation. With this new approach it becomes possible to realize activity scanning simulations with a parallel computer while resolving simultaneous events in a repeatable manner. The motivation for this approach is the two-phase simulation procedure intrinsic to cellular automata, coupled difference equations, and the discrete-event system specification. This new approach is introduced via an intuitively appealing construction of a new simulation procedure for activity scanning models, and this introduction is followed by an embedding of the new approach into the discrete-event system specification. In doing so, we illustrate a practical approach to distributed simulation and demonstrate how the proposed approach can be applied to the event scheduling and process-oriented worldviews.

Nutaro, James J.↗
NASA NTRS2012

Automatic Estimation of Volcanic Ash Plume Height using WorldView-2 Imagery

We explore the use of machine learning, computer vision, and pattern recognition techniques to automatically identify volcanic ash plumes and plume shadows, in WorldView-2 imagery. Using information of the relative position of the sun and spacecraft and terrain information in the form of a digital elevation map, classification, the height of the ash plume can also be inferred. We present the results from applying this approach to six scenes acquired on two separate days in April and May of 2010 of the Eyjafjallajokull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.

pattern recognition↗
NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗
DOE OSTI2023

Automated remote sensing tools to counter illicit maritime activity: vessel detection, bathymetry and topography from WorldView imagery

Illicit maritime activity, such as piracy and smuggling, is a global issue that often occurs in areas where interdiction authorities are sparse, ground-based monitoring technologies like radar lack range and coverage, and dark vessels abound. Our objective was to assess vessel congregation patterns, identify likely beaching areas based on terrain maps, and use them to narrow the search for potential smuggling transfer and overland routes in a specific region along the Puntland coast of Somalia. To accomplish this goal, we developed automated protocols applied to WorldView satellite imagery for (1) vessel detection and size classification, (2) shallow-water bathymetric characterization, and (3) coastal topography mapping. Utilizing a single sensor for vessel detection and topographic and bathymetric extraction at high spatial resolution and at a high re-visit rate provides a simplification to near-shore characterization for monitoring purposes. The extracted topography and bathymetry are then presented as a single, comprehensive perspective of a coastal region. The vessel-detection algorithm identified all vessels larger than approximately 15 metres in length (35 of 35), but misidentified six artefacts (i.e. false positives), resulting in an overall accuracy of 85%. The combined vessel and terrain maps facilitated the identification of a potential beaching and overland transportation route location.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Segmenting water and shadow regions within WorldView imagery using local binary patterns

Many shadow detection algorithms pertaining to remotely sensed imagery exist. Several of these algorithms exploit the spectral characteristics of shadows within imagery to identify shaded regions. However, these algorithms can have problems when water is also present within the imagery because water shares similar spectral characteristics with shadows. Many of these algorithms are applied to small image subsets instead of the image as a whole and frequently are applied to urban environments that require additional use of the normalized difference water index or other features to affect the removal of water from the shadow mask. This diversity of the image scene content coupled with the complexity and wide variety of environmental conditions that satellite imagery can acquire makes reliably separating shadow and water within larger images a complex problem. Thresholding various spectral indices to produce segmentation maps can be challenging when large, complex, and often imbalanced scenes are captured, which may require manual adjustment of algorithmic parameters for different image areas. Here, we present a methodology that makes use of the near-infrared channel using a watershed segmentation algorithm, local binary pattern measurements, and a support vector machine to classify shadow and water within a full WorldView scene. Results are promising with initial accuracies above 97% for both shadow and water.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Oak Ridge National Laboratory Bundle Adjustment of Maxar WorldView and GeoEye Imagery

Since the 1950s, bundle adjustment has been used to correct the geopositioning of imagery. With the increased availability of very high resolution satellite imagery, bundle adjustment has become an increasingly critical topic for both researchers and practitioners. Many studies have explored the bundle adjustment of satellite imagery from Maxar sensors, including the WorldView and GeoEye sensors. In this work, we review some of the recent and relevant literature pertaining to this topic.

47 OTHER INSTRUMENTATION↗
NASA NTRS2015

Quantifying Libya-4 Surface Reflectance Heterogeneity With WorldView-1, 2 and EO-1 Hyperion

The land surface imaging (LSI) virtual constellation approach promotes the concept of increasing Earth observations from multiple but disparate satellites. We evaluated this through spectral and spatial domains, by comparing surface reflectance from 30-m Hyperion and 2-m resolution WorldView-2 (WV-2) data in the Libya-4 pseudoinvariant calibration site. We convolved and resampled Hyperion to WV-2 bands using both cubic convolution and nearest neighbor (NN) interpolation. Additionally, WV-2 and WV-1 same-date imagery were processed as a cross-track stereo pair to generate a digital terrain model to evaluate the effects from large (>70 m) linear dunes. Agreement was moderate to low on dune peaks between WV-2 and Hyperion (R2 <; 0.4) but higher in areas of lower elevation and slope (R2 > 0.6). Our results provide a satellite sensor intercomparison protocol for an LSI virtual constellation at high spatial resolution, which should start with geolocation of pixels, followed by NN interpolation to avoid tall dunes that enhance surface reflectance differences across this internationally utilized site.

Hyperion↗
NASA NTRS2016

Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric Images

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Lee, Seung-Kuk↗
NASA NTRS2018

NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles. The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview website provide a unique view into EOS data through daily full resolution visualizations of hundreds of earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.

Cechini, Matthew↗
NASA NTRS2017

Vegetation Classification of Coffea on Hawaii Island using Worldview-2 Satellite Imagery

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012.

Gaertner, Julie↗
DOE OSTI2024

A neural network for cloud masking in WorldView satellite imagery

This repository includes the cloud detection algorithm used in the manuscript 'Topography controls variability in circumpolar permafrost thaw pond expansion' by Abolt et al. It also includes a demonstration of the algorithm's use at a survey area in northern Alaska and a demonstration of training the algorithm. This dataset includes .pt place-text, .py python, .tif image, .ipynb Jupyter notebook, and .txt text files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

NASA GIBS and Worldview: Leveraging Visualizations to Improve Data Discovery

NASA's Global Imagery Browse Services (GIBS) leverages scientific and community best practices and standards to provide a scalable, compliant, and authoritative source for NASA Earth Observing System (EOS) Earth science data visualizations. Since 2013, its goal has been to "transform how end users interact and discover [EOS] data through visualizations." Imagery layers within GIBS allow end users to easily and quickly interact with full resolution, pre-generated visualizations of scientific parameters. This interactive discovery approach relies on visual observation and identification of phenomena that are not as simply identified otherwise.

Global Imagery Browse Services↗
NASA NTRSDate not supplied

NASA’s Global Imagery Browse Services and Worldview Migrate to Mapbox Vector Tiles: The Drawbacks and Advantages

NASA’s Global Imagery Browse Services (GIBS) is in the process of migrating their vector data from raster tiles to Mapbox Vector Tiles (MVTs). MVTs are becoming ubiquitous in the world of web mapping. Serving data in place of pixels for each feature presents numerous new visualization opportunities as well as various new challenges to overcome. This presentation will cover some of the hardships these teams encountered, the techniques used to overcome those barriers, and it will give you a glimpse at how the user experience was enhanced.

Benjamin King↗