scholarly journals Correcting Himawari-8 Advanced Himawari Imager Data for the Production of Vivid True-Color Imagery

2019 ◽  
Vol 36 (3) ◽  
pp. 427-442 ◽  
Author(s):  
Mark A. Broomhall ◽  
Leon J. Majewski ◽  
Vincent O. Villani ◽  
Ian F. Grant ◽  
Steven D. Miller
Keyword(s):  
Temporal Resolution ◽  
Rayleigh Scattering ◽  
Lookup Table ◽  
Asia Pacific ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Aesthetic Appearance ◽  
Spatial Coverage ◽  
True Color ◽  
Color Imagery

AbstractObservations of top-of-atmosphere radiances from the Advanced Himawari Imager (AHI) blue, green, and red spectral bands can be used to produce high-temporal-resolution, true-color imagery at 1-km spatial resolution over the Asia–Pacific region. To enhance interpretability and aesthetic appearance of these images, the top-of-atmosphere radiance data are processed to remove the Rayleigh-scattered atmospheric component, corrected for limb effects, blended with brightness temperature data from a thermal infrared window band at night, and the resultant imagery adjusted to optimize contrast. The contribution of Rayleigh scattering to the AHI observations is calculated by interpolating radiative transfer parameters from a preconstructed set of lookup tables, which are specifically created for the Himawari-8 AHI instrument. A surface reflectance value for each pixel is calculated after the Rayleigh contribution is removed. The spectrally dependent reflectance values produced from the lookup table differ from the exact calculation by up to 18% at the planetary limb, over 100% at the solar terminator, and by less than 0.5% at low to moderate solar and sensor zenith angles. The subsequent corrections applied for limb effects mitigate the areas with high interpolation error, which slightly reduces the spatial coverage, but provides Rayleigh-corrected surface reflectance products that have interpolation errors at or below 0.5%. Resolution sharpening increases the nominal pixel size from 1000 to 500 m while still producing sharp images. The resultant images are colorful, visually intuitive, high contrast, and of sufficient spatial and temporal resolution to provide a unique and complementary observational tool for use by weather forecasters and the general public alike.

scholarly journals Comparison of Landsat and Land-Based Phenology Camera Normalized Difference Vegetation Index (NDVI) for Dominant Plant Communities in the Great Basin

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1139 ◽  
Author(s):  
Keirith Snyder ◽  
Justin Huntington ◽  
Bryce Wehan ◽  
Charles Morton ◽  
Tamzen Stringham
Keyword(s):  
Great Basin ◽  
Plant Communities ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spatial Scales ◽  
Plant Phenology ◽  
High Temporal Resolution ◽  
Spatial Coverage

Phenology of plants is important for ecological interactions. The timing and development of green leaves, plant maturity, and senescence affects biophysical interactions of plants with the environment. In this study we explored the agreement between land-based camera and satellite-based phenology metrics to quantify plant phenology and phenophases dates in five plant community types characteristic of the semi-arid cold desert region of the Great Basin. Three years of data were analyzed. We calculated the Normalized Difference Vegetation Index (NDVI) for both land-based cameras (i.e., phenocams) and Landsat imagery. NDVI from camera images was calculated by taking a standard RGB (red, green, and blue) image and then a near infrared (NIR) plus RGB image. Phenocam NDVI was calculated by extracting the red digital number (DN) and the NIR DN from images taken a few seconds apart. Landsat has a spatial resolution of 30 m2, while phenocam spatial resolution can be analyzed at the single pixel level at the scale of cm2 or area averaged regions can be analyzed with scales up to 1 km2. For this study, phenocam regions of interest were used that approximated the scale of at least one Landsat pixel. In the tall-statured pinyon and juniper woodland sites, there was a lack of agreement in NDVI between phenocam and Landsat NDVI, even after using National Agricultural Imagery Program (NAIP) imagery to account for fractional coverage of pinyon and juniper versus interspace in the phenocam data. Landsat NDVI appeared to be dominated by the signal from the interspace and was insensitive to subtle changes in the pinyon and juniper tree canopy. However, for short-statured sagebrush shrub and meadow communities, there was good agreement between the phenocam and Landsat NDVI as reflected in high Pearson’s correlation coefficients (r > 0.75). Due to greater temporal resolution of the phenocams with images taken daily, versus the 16-day return interval of Landsat, phenocam data provided more utility in determining important phenophase dates: start of season, peak of season, and end of season. More specific species-level information can be obtained with the high temporal resolution of phenocams, but only for a limited number of sites, while Landsat can provide the multi-decadal history and spatial coverage that is unmatched by other platforms. The agreement between Landsat and phenocam NDVI for short-statured plant communities of the Great Basin, shows promise for monitoring landscape and regional-level plant phenology across large areas and time periods, with phenocams providing a more comprehensive understanding of plant phenology at finer spatial scales, and Landsat extending the historical record of observations.

scholarly journals New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection

2016 ◽  
Vol 97 (3) ◽  
pp. 385-395 ◽  
Author(s):  
Christopher S. Ruf ◽  
Robert Atlas ◽  
Paul S. Chang ◽  
Maria Paola Clarizia ◽  
James L. Garrison ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Inner Core ◽  
Dynamic Range ◽  
Surface Wind ◽  
Ocean Surface ◽  
Tropical Convection ◽  
High Temporal Resolution ◽  
Short Time Scale ◽  
Temporal Sampling ◽  
Spatial Coverage

Abstract The Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TCs) and tropical convection. The mission’s two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short-time-scale processes such as the rapid intensification phase of TC development and the ability of the surface measurements to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission’s goal is to support significant improvements in our ability to forecast TC track, intensity, and storm surge through better observations and, ultimately, better understanding of inner-core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low-frequency GPS signals. The mission will deploy an eight-spacecraft constellation in a low-inclination (35°) circular orbit to maximize coverage and sampling in the tropics. Each CYGNSS spacecraft carries a four-channel radar receiver that measures GPS navigation signals scattered by the ocean surface. The mission will measure inner-core surface winds with high temporal resolution and spatial coverage, under all precipitating conditions, and over the full dynamic range of TC wind speeds.

scholarly journals HIGH TEMPORAL RESOLUTION PERMAFROST MONITORING USING A MULTIPLE STACK INSAR TECHNIQUE

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1171-1176 ◽  
Author(s):  
J. Eppler ◽  
M. Kubanski ◽  
J. Sharma ◽  
J. Busler
Keyword(s):  
Temporal Resolution ◽  
Surface Deformation ◽  
High Temporal Resolution ◽  
Test Cases ◽  
Surficial Geology ◽  
Spatial Coverage ◽  
Northern Regions ◽  
Multi Temporal ◽  
Deformation Patterns

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. <br><br> Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. <br><br> The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure.

scholarly journals A high-resolution record of early Paleozoic climate

2021 ◽  
Vol 118 (6) ◽  
pp. e2013083118
Author(s):  
Samuel L. Goldberg ◽  
Theodore M. Present ◽  
Seth Finnegan ◽  
Kristin D. Bergmann
Keyword(s):  
Temporal Resolution ◽  
Temporal Trends ◽  
High Temporal Resolution ◽  
Early Paleozoic ◽  
Bulk Rock ◽  
Carbonate Platforms ◽  
Fluid Exchange ◽  
Middle Ordovician ◽  
Spatial Coverage ◽  
Clumped Isotope

The spatial coverage and temporal resolution of the Early Paleozoic paleoclimate record are limited, primarily due to the paucity of well-preserved skeletal material commonly used for oxygen-isotope paleothermometry. Bulk-rock δ18O datasets can provide broader coverage and higher resolution, but are prone to burial alteration. We assess the diagenetic character of two thick Cambro–Ordovician carbonate platforms with minimal to moderate burial by pairing clumped and bulk isotope analyses of micritic carbonates. Despite resetting of the clumped-isotope thermometer at both sites, our samples indicate relatively little change to their bulk δ18O due to low fluid exchange. Consequently, both sequences preserve temporal trends in δ18O. Motivated by this result, we compile a global suite of bulk rock δ18O data, stacking overlapping regional records to minimize diagenetic influences on overall trends. We find good agreement of bulk rock δ18O with brachiopod and conodont δ18O trends through time. Given evidence that the δ18O value of seawater has not evolved substantially through the Phanerozoic, we interpret this record as primarily reflecting changes in tropical, nearshore seawater temperatures and only moderately modified by diagenesis. Focusing on the samples with the most enriched, and thus likely least-altered, δ18O values, we reconstruct Late Cambrian warming, Early Ordovician extreme warmth, and cooling around the Early–Middle Ordovician boundary. Our record is consistent with models linking the Great Ordovician Biodiversification Event to cooling of previously very warm tropical oceans. In addition, our high-temporal-resolution record suggests previously unresolved transient warming and climate instability potentially associated with Late Ordovician tectonic events.

scholarly journals Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2376
Author(s):  
Lijuan Chen ◽  
Ying Fei ◽  
Ren Wang ◽  
Peng Fang ◽  
Jiamei Han ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Temporal Resolution ◽  
Deep Understanding ◽  
Atmospheric Environment ◽  
P Value ◽  
High Temporal Resolution ◽  
Surface Reflectance ◽  
Polar Orbiting Satellite ◽  
Solar Angle

High temporal resolution aerosol optical depth (AOD) products are very important for the studies of atmospheric environment and climate change. Geostationary Ocean Color Imager (GOCI) is a suitable data source for AOD retrieval, as it can monitor hourly aerosol changes and make up for the low temporal resolution deficiency of polar orbiting satellite. In this study, we proposed an algorithm for retrieving high temporal resolution AOD using GOCI data and then applied the algorithm in the Yangtze River Delta, a typical region suffering severe air pollution issues. Based on Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance determined by MODIS V5.2 algorithm and MODIS Bidirectional Reflectance Distribution Function (BRDF) data, after spectral conversion between MODIS and GOCI, the GOCI surface reflectance at different solar angles were obtained and used to retrieve AOD. Five indicators including correlation coefficient (R), significant level of the correlation (p value), mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) were employed to analyze the errors between the Aerosol Robotic Network (AERONET) observed AOD and the GOCI retrieved AOD. The results showed that the GOCI AOD retrieved by the continental aerosol look-up table was consistent with the AERONET AOD (R > 0.7, p ≤ 0.05). The highest R value of Taihu Station and Xuzhou CUMT Station are both 0.84 (8:30 a.m.); the minimum RMSE at Taihu and Xuzhou-CUMT stations were 0.2077 (11:30 a.m.) and 0.1937 (10:30 a.m.), respectively. Moreover, the results suggested that the greater the solar angle of the GOCI sensor, the higher the AOD retrieval accuracy, while the retrieved AOD at noon exhibited the largest error as assessed by MAE and MRE. We concluded that the inaccurate estimation of surface reflectance was the root cause of the retrieval errors. This study has implications in providing a deep understanding of the effects of solar angle changes on retrieving AOD using GOCI.

scholarly journals Atmospheric Correction of True-Color RGB Imagery with Limb Area-Blending Based on 6S and Satellite Image Enhancement Techniques Using Geo-Kompsat-2A Advanced Meteorological Imager Data

2021 ◽  
Author(s):  
Minsang Kim ◽  
Jun-Hyung Heo ◽  
Eun-Ha Sohn
Keyword(s):  
Satellite Image ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Radiative Transfer Model ◽  
High Temporal Resolution ◽  
Transfer Model ◽  
Green Band ◽  
Color Distribution ◽  
True Color ◽  
Color Imagery

AbstractThis study aims for producing high-quality true-color red-green-blue (RGB) imagery that is useful for interpreting various environmental phenomena, particularly for GK2A. Here we deal with an issue that general atmospheric correction methods for RGB imagery might be breakdown at high solar/viewing zenith angle of GK2A due to erroneous atmospheric path lengths. Additionally, there is another issue about the green band of GK2A of which centroid wavelength (510 nm) is different from that of natural green band (555 nm), resulting in the unrealistic RGB imagery. To overcome those weakness of the RGB imagery for GK2A, we apply the second simulation of the satellite signal in the solar spectrum radiative transfer model look-up table with improved information considering altitude of the reflective surface to reduce the exaggerated atmospheric correction, and a blending technique that mixed the true-color imagery before and after atmospheric correction which produced a naturally expressed true-color image. Consequently, the root mean square error decreased by 0.1–0.5 in accordance with the solar and view zenith angles. The green band signal was modified by combining it with a veggie band to form hybrid green which adjust centroid wavelength of approximately 550 nm. The original composite of true-color RGB imagery is dark; therefore, to brighten the imagery, histogram equalization is conducted to flatten the color distribution. High-temporal-resolution true-color imagery from the GK2A AMI have significant potential to provide scientists and forecasters as a tools to visualize the changing Earth and also expected to intuitively understand the atmospheric phenomenon to the general public.

scholarly journals Assessing the Potential Benefits of the Geostationary Vantage Point for Generating Daily Chlorophyll-a Maps in the Baltic Sea

2018 ◽  
Vol 10 (12) ◽  
pp. 1944
Author(s):  
Marco Bellacicco ◽  
Daniele Ciani ◽  
David Doxaran ◽  
Vincenzo Vellucci ◽  
David Antoine ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Temporal Resolution ◽  
Ocean Color ◽  
Low Earth Orbit ◽  
Empirical Orthogonal Functions ◽  
Optimal Interpolation ◽  
High Temporal Resolution ◽  
Orthogonal Functions ◽  
Spatial Coverage ◽  
Potential Benefits

Currently, observations from low-Earth orbit (LEO) ocean color sensors represent one of the most used tools to study surface optical and biogeochemical properties of the ocean. LEO observations are available at daily temporal resolution, and are often combined into weekly, monthly, seasonal, and annual averages in order to obtain sufficient spatial coverage. Indeed, daily satellite maps of the main oceanic variables (e.g., surface phytoplankton chlorophyll-a) generally have many data gaps, mainly due to clouds, which can be filled using either Optimal Interpolation or the Empirical Orthogonal Functions approach. Such interpolations, however, may introduce large uncertainties in the final product. Here, our goal is to quantify the potential benefits of having high-temporal resolution observations from a geostationary (GEO) ocean color sensor to reduce interpolation errors in the reconstructed hourly and daily chlorophyll-a products. To this aim, we used modeled chlorophyll-a fields from the Copernicus Marine Environment Monitoring Service’s (CMEMS) Baltic Monitoring and Forecasting Centre (BAL MFC) and satellite cloud observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor (on board the geostationary satellite METEOSAT). The sampling of a GEO was thus simulated by combining the hourly chlorophyll fields and clouds masks, then hourly and daily chlorophyll-a products were generated after interpolation from neighboring valid data using the Multi-Channel Singular Spectral Analysis (M-SSA). Two cases are discussed: (i) A reconstruction based on the typical sampling of a LEO and, (ii) a simulation of a GEO sampling with hourly observations. The results show that the root mean square and interpolation bias errors are significantly reduced using hourly observations.

Multidetector-row Computed Tomography in the Assessment of Coronary Artery Disease – New Techniques and Insights

2010 ◽  
Vol 6 (2) ◽  
pp. 43 ◽  
Author(s):  
Andreas H Mahnken ◽  
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Data Acquisition ◽  
Temporal Resolution ◽  
High Temporal Resolution ◽  
Multidetector Row ◽  
Ct Scanners ◽  
Artery Disease ◽  
Cardiac Mdct

Over the last decade, cardiac computed tomography (CT) technology has experienced revolutionary changes and gained broad clinical acceptance in the work-up of patients suffering from coronary artery disease (CAD). Since cardiac multidetector-row CT (MDCT) was introduced in 1998, acquisition time, number of detector rows and spatial and temporal resolution have improved tremendously. Current developments in cardiac CT are focusing on low-dose cardiac scanning at ultra-high temporal resolution. Technically, there are two major approaches to achieving these goals: rapid data acquisition using dual-source CT scanners with high temporal resolution or volumetric data acquisition with 256/320-slice CT scanners. While each approach has specific advantages and disadvantages, both technologies foster the extension of cardiac MDCT beyond morphological imaging towards the functional assessment of CAD. This article examines current trends in the development of cardiac MDCT.

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