SEARCH · Search NASA
Results for “Geostationary satellites”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Automated Detection of Severe Thunderstorm Signatures Within Geostationary Satellite Imagery Using Deep Learning
Explore the source record for details and available documents.
Physically-Based Machine Learning Approach to Dust Detection in NASA/NOAA Geostationary Satellite Imagery
Explore the source record for details and available documents.
Time Series Machine Learning Methods for Surface PM2.5 Estimations Using Geostationary Satellites and Numerical Weather Models
Explore the source record for details and available documents.
Automated Detection of Severe Thunderstorm Signatures Within Geostationary Satellite Imagery Using Deep Learning
Explore the source record for details and available documents.
Detecting Severe Thunderstorm Signatures Within Geostationary Satellite Imagery Using a Deep Learning Model
Explore the source record for details and available documents.
A 3-Channel Algorithm for Retrieving Consistent Cloud Properties Across Different Geostationary Satellites
Explore the source record for details and available documents.
Quantifying Burned Area of Wildfires in the Western United States From Polar-Orbiting and Geostationary Satellite Active-Fire Detections
Background : Accurately estimating burned area from satellites is key to improving biomass burning emission models, studying fire evolution and assessing environmental impact. Previous studies have found that current methods for estimating burned area of fires from satellite active-fire data do not always provide an accurate estimate. Aims and Methods : In this work, we develop a novel algorithm to estimate hourly accumulated burned area based on the area from boundaries of non-convex polygons containing the accumulated Visible Infrared Imaging Radiometer Suite (VIIRS)active-fire detections. Hourly time series are created by combining VIIRS estimates with fire radiative power (FRP) estimates from GOES-17 data. Conclusions, Key Results and Implication : We evaluate the performance of the algorithm for both accumulated and change in burned area between airborne observations, and specifically examine sensitivity to the choice of the parameter controlling how much the boundary can shrink towards the interior of the area polygon. Results of the hourly accumulation of burned area for multiple fires from 2019 and 2020 generally correlate strongly with airborne infrared (IR) observations collected by the United States Forest Service National Infrared Operations (NIROPS), exhibiting correlation coefficient values usually greater than 0.95 and errors <20%.
Development of Limb-Corrected and Intercalibrated Multispectral Composites from the Constellation of Geostationary Satellites
Explore the source record for details and available documents.
Mapping Surface Vapor Pressure Deficits From Geostationary Satellites for Fire Weather Monitoring
The increase in the wildfires were observed globally in accordance with global warming, and to real- time monitoring of wildfire risk in broad scale is demanded for wildfire management to prevent the spread of wildfires. Scientists invented a lot of indices to assess the wildfire risk. Vapor Pressure Deficit (VPD) is one of the most important meteorological components for those indices. Compared to other components of fire weather indices, VPD can change quickly from lower risk to higher risk even in sub-hourly. Therefore, real-time fire risk monitoring requires high-resolution and high- temporal VPD spatial map. Here, we developed VPD estimation method using the GOES Advanced Baseline Imager (ABI) data. Unlike the polar-orbital satellite data, the ABI can observe target region every 10 minutes, so that we can estimate VPD for fire weather in real-time. The method used to estimate VPD is same with the algorithm of NASA Earth Exchange Gridded Daily Meteorology (NEX- GDM), which estimate meteorological variables from ground weather observation and spatial variables based on random forest (RF). We calculated RF importance to select bands of ABI as input of the model. To validate our results, we compared the spatial pattern of our VPD data with the Real- Time Mesoscale Analysis (RTMA) data over the conterminous USA. We sought possibility of applying our method to the region where no real-time high-resolution weather data is available, such as South America. The developed method can produce real-time high-resolution high-frequent VPD data in the continental scale. The derived data from GOES ABI could contribute to improve the fire weather monitoring and lead to prevent wildfires.
Unusual Formaldehyde (HCHO) Vertical Profile Shapes During A Sea Breeze Event: Implications for Geostationary Satellite Trace Gas Retrievals
Explore the source record for details and available documents.
Studying Atmospheric Composition on the Global South with Geostationary Satellites: South American Perspective
Explore the source record for details and available documents.
Smoke absorption retrieval algorithm using critical reflectance method with geostationary satellite over North America
Explore the source record for details and available documents.
On the feasibility of monitoring carbon monoxide in the lower troposphere from a constellation of Northern Hemisphere geostationary satellites. (Part 1)
Explore the source record for details and available documents.
Evaluation and improvement of parameterization methods for estimating cloudy-sky downwelling surface longwave radiation from geostationary satellite data
Explore the source record for details and available documents.
The use of satellites in non-geostationary orbits for unloading geostationary communication satellite traffic peaks. Volume 1: Executive summary
The overall objective of this program was to assess the application, economic benefits, and technology and system implications of satellites in non-geostationary (non-GEO) orbits for off-loading peak traffic from GEO communications satellites. The study was organized into four technical tasks which are described in turn. They are: (1) concepts development; (2) system definition; (3) economic comparisons; and (4) technology requirements definition. Each of these tasks is defined in detail and the results of each are given.