scholarly journals MODIS Aqua Reflective Solar Band Calibration for NASA’s R2018 Ocean Color Products

2019 ◽  
Vol 11 (19) ◽  
pp. 2187 ◽  
Author(s):  
Lee ◽  
Meister ◽  
Franz
Keyword(s):  
Near Infrared ◽  
Spectral Response ◽  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Radiometric Calibration ◽  
Coherent Noise ◽  
Blue Band ◽  
Global Trends ◽  
Moderate Resolution Imaging Spectroradiometer

Remote-sensing ocean color products have stringent requirements on radiometric calibration stability. To address a calibration deficiency in Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua in recent years, the NASA Ocean Biology Processing Group (OBPG) developed a new calibration for reflective solar bands. Prior to the reprocessing of NASA’s ocean color products for 2018 (R2018), the OBPG MODIS products had been based on calibration provided by the MODIS Calibration Support Team (MCST). Several modifications were made to the MCST calibration approach to improve the calibration accuracy for ocean color products. These include 1) applying 936-nm detector normalization to solar diffuser stability monitor (SDSM) data to reduce coherent noise; 2) modeling solar diffuser (SD) degradation wavelength dependency to determine SD degradation in near-infrared and shortwave infrared wavelengths; 3) computing detector gains using SD screen-closed data to better match ocean radiance levels in all bands; 4) performing a simple atmospheric correction to reduce bidirectional reflectance distribution function (BRDF) effects in desert trends; 5) estimating and using modulated relative spectral response (RSR) impact on ocean data to adjust the calibration coefficients; 6) using smoothing to characterize the temporal change in calibration; and characterizing response versus scan angle (RVS) changes using 2nd-order polynomials to improve spatial/temporal calibration stability. Relative to the previous R2014 ocean color products, the R2018 calibration removed the suspect late-mission global trends in blue-band water-leaving reflectance and some anomalously large short-term variability (spikes) in the temporal trend of chlorophyll concentration. This paper will describe the OBPG calibration with a focus on the differences between the MCST and OBPG approaches.

scholarly journals Applying satellite images to spectral signature development of maize production (Zea mays L.) under colombia’s middle tropics conditions

ENTRAMADO ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 256-262
Author(s):  
Edier Fernando Ávila Vélez ◽  
Natalia Escobar Escobar ◽  
Carlos Francisco Morantes Choconta
Keyword(s):  
Satellite Images ◽  
Near Infrared ◽  
Spectral Response ◽  
Spectral Signature ◽  
Growth Stages ◽  
Total Production ◽  
Radiometric Calibration ◽  
Maize Crop ◽  
Maize Production ◽  
Production Stages

Maize is currently the world’s second largest crop in terms of production, after wheat and rice. It is the first cereal as for grain yield per hectare and the second, after wheat, regarding total production. Maize has great economic importance worldwide, both as human and/or animal food, and as a source of a large number of industrial products. New digital technologies are allowing greater monitoring of farming production stages. This research developed the spectral signature of maize fields ground covers across different growth stages (2 months, 2.3 months and 4.3 months). Similarly, this research paper proposes the application of a methodology based on four phases: 1. Maize crop georeferencing, 2. Satellite images selection, 3. Radiometric calibration of images 4. Spectral signature development of maize crops. Spectral response or signature of maize crops at visible and near-infrared wavelengths was obtained, indicating significant changes in crops growth. The use of satellite imagery becomes an interesting tool that introduces an approach towards more accurate and controlled monitoring systems in agricultural production.

scholarly journals Improvement of Atmospheric Correction of Satellite Sentinel-3/OLCI Data for Oceanic Waters in Presence of Sargassum

2022 ◽  
Vol 14 (2) ◽  
pp. 386
Author(s):  
Léa Schamberger ◽  
Audrey Minghelli ◽  
Malik Chami ◽  
François Steinmetz
Keyword(s):  
Near Infrared ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Correction Algorithm ◽  
Infrared Band ◽  
Economic Issues ◽  
Optical Signature ◽  
Color Data ◽  
The Caribbean ◽  
Satellite Ocean Color

The invasive species of brown algae Sargassum gathers in large aggregations in the Caribbean Sea, and has done so especially over the last decade. These aggregations wash up on shores and decompose, leading to many socio-economic issues for the population and the coastal ecosystem. Satellite ocean color data sensors such as Sentinel-3/OLCI can be used to detect the presence of Sargassum and estimate its fractional coverage and biomass. The derivation of Sargassum presence and abundance from satellite ocean color data first requires atmospheric correction; however, the atmospheric correction procedure that is commonly used for oceanic waters needs to be adapted when dealing with the occurrence of Sargassum because the non-zero water reflectance in the near infrared band induced by Sargassum optical signature could lead to Sargassum being wrongly identified as aerosols. In this study, this difficulty is overcome by interpolating aerosol and sunglint reflectance between nearby Sargassum-free pixels. The proposed method relies on the local homogeneity of the aerosol reflectance between Sargassum and Sargassum-free areas. The performance of the adapted atmospheric correction algorithm over Sargassum areas is evaluated. The proposed method is demonstrated to result in more plausible aerosol and sunglint reflectances. A reduction of between 75% and 88% of pixels showing a negative water reflectance above 600 nm were noticed after the correction of the several images.

scholarly journals Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

2014 ◽  
Vol 11 (6) ◽  
pp. 9299-9340
Author(s):  
M. Montes-Hugo ◽  
H. Bouakba ◽  
R. Arnone
Keyword(s):  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Relative Bias ◽  
Wide Field ◽  
Absolute Bias ◽  
Analysis System ◽  
Data Analysis System ◽  
The Impact

Abstract. The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg−1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

scholarly journals UV Reflectance of the Ocean from DSCOVR/EPIC: Comparisons with a Theoretical Model and Aura/OMI Observations

2019 ◽  
Vol 36 (11) ◽  
pp. 2087-2099 ◽  
Author(s):  
Alexander Vasilkov ◽  
Alexei Lyapustin ◽  
B. Greg Mitchell ◽  
Dong Huang
Keyword(s):  
Radiative Transfer ◽  
Chlorophyll Concentration ◽  
Atmospheric Correction ◽  
Ocean Water ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Inherent Optical Properties ◽  
Uv Reflectance ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractUltraviolet (UV) data collected over the ocean by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) are used. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm adapted for EPIC processing performs cloud detection, aerosol retrievals, and atmospheric correction providing the water-leaving reflectance of the ocean at 340 and 388 nm. The water-leaving reflectance is an indicator of the presence of absorbing and scattering constituents in seawater. The retrieved water-leaving reflectance is compared with full radiative transfer calculations based on a model of inherent optical properties (IOP) of ocean water in UV. The model is verified with data collected on the Aerosol Characterization Experiments (ACE) Asia cruise supported by the NASA Sensor Intercomparison for Marine Biological and Interdisciplinary Ocean Studies (SIMBIOS) project. The model assumes that the ocean water IOPs are parameterized through a chlorophyll concentration. The radiative transfer simulations were carried out using the climatological chlorophyll concentration from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua satellite. The EPIC-derived water-leaving reflectance is also compared with climatological Lambertian-equivalent reflectivity (LER) of the ocean derived from measurements of the Ozone Monitoring Instrument (OMI) on board the NASA polar-orbiting Aura satellite. The EPIC reflectance agrees well (within 0.01) with the model reflectance except for oligotrophic oceanic areas. For those areas, the model reflectance is biased low by about 0.01 at 340 nm and up to 0.03 at 388 nm. The OMI-derived climatological LER is significantly higher than the EPIC water-leaving reflectance, largely due to the surface glint contribution. The globally averaged difference is about 0.04.

scholarly journals Atmospheric Correction of GOCI Using Quasi-Synchronous VIIRS Data in Highly Turbid Coastal Waters

2019 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Jie Wu ◽  
Chuqun Chen ◽  
Sravanthi Nukapothula
Keyword(s):  
Coastal Waters ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Turbid Waters ◽  
Aerosol Scattering ◽  
Temporal And Spatial ◽  
Shortwave Infrared ◽  
The Western Pacific

The Geostationary Ocean Color Imager (GOCI) sensor, with high temporal and spatial resolution (eight images per day at an interval of 1 hour, 500 m), is the world’s first geostationary ocean color satellite sensor. GOCI provides good data for ocean color remote sensing in the Western Pacific, among the most turbid waters in the world. However, GOCI has no shortwave infrared (SWIR) bands making atmospheric correction (AC) challenging in highly turbid coastal regions. In this paper, we have developed a new AC algorithm for GOCI in turbid coastal waters by using quasi-synchronous Visible Infrared Imaging Radiometer Suite (VIIRS) data. This new algorithm estimates and removes the aerosol scattering reflectance according to the contributing aerosol models and the aerosol optical thickness estimated by VIIRS’s near-infrared (NIR) and SWIR bands. Comparisons with other AC algorithms showed that the new algorithm provides a simple, effective, AC approach for GOCI to obtain reasonable results in highly turbid coastal waters.

scholarly journals New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

2019 ◽  
Vol 11 (12) ◽  
pp. 1502 ◽  
Author(s):  
Fatima Tuz Zafrin Tuli ◽  
Cibele Teixeira Pinto ◽  
Amit Angal ◽  
Xiaoxiong Xiong ◽  
Dennis Helder
Keyword(s):  
Temporal Stability ◽  
Kendall Test ◽  
Sensor Calibration ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Calibration Source ◽  
Blue Band ◽  
New Approach ◽  
Monotonic Trend ◽  
Moderate Resolution Imaging Spectroradiometer

Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process.

scholarly journals Science impact of MODIS C5 calibration degradation and C6+ improvements

2014 ◽  
Vol 7 (7) ◽  
pp. 7281-7319 ◽  
Author(s):  
A. Lyapustin ◽  
Y. Wang ◽  
X. Xiong ◽  
G. Meister ◽  
S. Platnick ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Atmospheric Correction ◽  
Temporal Trends ◽  
Polarization Sensitivity ◽  
Surface Reflectance ◽  
Blue Band ◽  
Cross Calibration ◽  
Calibration Approach

Abstract. The Collection 6 (C6) MODIS land and atmosphere datasets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra, and to lesser extent, in MODIS Aqua geophysical datasets. Sensor degradation is largest in the Blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström Exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS dataset which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as de-trending and Terra–Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over deserts, we have also developed a de-trending and cross-calibration method which removes residual decadal trends on the order of several tenths of one percent of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1–B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

scholarly journals Comparison of Aerosol Reflectance Correction Schemes Using Two Near-Infrared Wavelengths for Ocean Color Data Processing

2018 ◽  
Vol 10 (11) ◽  
pp. 1791 ◽  
Author(s):  
Jae-Hyun Ahn ◽  
Young-Je Park ◽  
Hajime Fukushima
Keyword(s):  
Radiative Transfer ◽  
Near Infrared ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Weighting Factor ◽  
Simulation Code ◽  
Aerosol Model ◽  
Median Error ◽  
Visible Wavelengths

This paper reanalyzes the aerosol reflectance correction schemes employed by major ocean color missions. The utilization of two near-infrared (NIR) bands to estimate aerosol reflectance in visible wavelengths has been widely adopted, for example by SeaWiFS/MODIS/VIIRS (GW1994), OCTS/GLI/SGLI (F1998), MERIS/OLCI (AM1999), and GOCI/GOCI-II (A2016). The F1998, AM1999, and A2016 schemes were developed based on GW1994; however, they are implemented differently in terms of aerosol model selection and weighting factor computation. The F1998 scheme determines the contribution of the most appropriate aerosol models in the aerosol optical thickness domain, whereas the GW1994 scheme focuses on single-scattering reflectance. The AM1999 and A2016 schemes both directly resolve the multiple scattering domain contribution. However, A2016 also considers the spectrally dependent weighting factor, whereas AM1999 calculates the spectrally invariant weighting factor. Additionally, ocean color measurements on a geostationary platform, such as GOCI, require more accurate aerosol correction schemes because the measurements are made over a large range of solar zenith angles which causes diurnal instabilities in the atmospheric correction. Herein, the four correction schemes were tested with simulated top-of-atmosphere radiances generated by radiative transfer simulations for three aerosol models. For comparison, look-up tables and test data were generated using the same radiative transfer simulation code. All schemes showed acceptable accuracy, with less than 10% median error in water reflectance retrieval at 443 nm. Notably, the accuracy of the A2016 scheme was similar among different aerosol models, whereas the other schemes tended to provide better accuracy with coarse aerosol models than the fine aerosol models.

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