scholarly journals Computationally Efficient Methods of Collocating Satellite, Aircraft, and Ground Observations

2009 ◽  
Vol 26 (8) ◽  
pp. 1585-1595 ◽  
Author(s):  
Frederick W. Nagle ◽  
Robert E. Holz
Keyword(s):  
Observation System ◽  
Computationally Efficient ◽  
Laptop Computer ◽  
Geometric Problem ◽  
Temporal Sampling ◽  
Wide Range ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The usefulness of measurements from satellite-borne instruments is enhanced if these measurements can be compared to measurements from other instruments mounted aboard the same or different satellite, with measurements from aircraft, or with ground measurements. The process of associating measurements from disparate instruments and platforms is referred to as collocation. In a few cases, two instruments mounted aboard the same spacecraft have been engineered to function in tandem, but commonly this is not the case. The collocation process may then become an awkward geometric problem of finding which of many observations within one dataset corresponds to an observation in another set, possibly from another platform. This paper presents methods that can be applied to a wide range of satellite, aircraft, and surface measurements that allow for efficient collocation with measurements having varying spatial and temporal sampling. Examples of applying the methods are presented that highlight the benefits of efficient collocation. This includes identifying the occurrence of simultaneous nadir observations (SNOs); collocation of sounder, imager, and active remotely sensed measurements on the NASA Earth Observation System (EOS); and collocation of the polar orbiting imager, sounder, and microwave measurements with geostationary observations. It is possible, using an inexpensive laptop computer, to collocate Moderate Resolution Imaging Spectroradiometer (MODIS) imager observations from the Aqua satellite with geostationary observations rapidly enough to deal with these measurements in real time, making either dataset, enhanced by the other, a potentially operational product. A “tool kit” is suggested consisting of computer procedures useful in collocation.

scholarly journals The importance of temporal collocation for the evaluation of aerosol models with observations

2016 ◽  
Vol 16 (2) ◽  
pp. 1065-1079 ◽  
Author(s):  
N. A. J. Schutgens ◽  
D. G. Partridge ◽  
P. Stier
Keyword(s):  
Remote Sensing Data ◽  
Single Scattering ◽  
Data Sets ◽  
Model Errors ◽  
Model Data ◽  
Sampling Errors ◽  
Temporal Sampling ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. It is often implicitly assumed that over suitably long periods the mean of observations and models should be comparable, even if they have different temporal sampling. We assess the errors incurred due to ignoring temporal sampling and show that they are of similar magnitude as (but smaller than) actual model errors (20–60 %).Using temporal sampling from remote-sensing data sets, the satellite imager MODIS (MODerate resolution Imaging Spectroradiometer) and the ground-based sun photometer network AERONET (AErosol Robotic NETwork), and three different global aerosol models, we compare annual and monthly averages of full model data to sampled model data. Our results show that sampling errors as large as 100 % in AOT (aerosol optical thickness), 0.4 in AE (Ångström Exponent) and 0.05 in SSA (single scattering albedo) are possible. Even in daily averages, sampling errors can be significant. Moreover these sampling errors are often correlated over long distances giving rise to artificial contrasts between pristine and polluted events and regions. Additionally, we provide evidence that suggests that models will underestimate these errors. To prevent sampling errors, model data should be temporally collocated to the observations before any analysis is made.We also discuss how this work has consequences for in situ measurements (e.g. aircraft campaigns or surface measurements) in model evaluation.Although this study is framed in the context of model evaluation, it has a clear and direct relevance to climatologies derived from observational data sets.

scholarly journals Monthly-averaged maps of surface BRDF parameters in ten spectral bands for land and water masses

2018 ◽  
Author(s):  
Philippe Blanc ◽  
Benoit Gschwind ◽  
Lionel Ménard ◽  
Lucien Wald
Keyword(s):  
Original Data ◽  
Observation System ◽  
Creative Commons ◽  
Spectral Bands ◽  
The Usa ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Bidirectional Reflectance Distribution

Abstract. The construction of worldwide maps of surface bidirectional reflectance distribution function (BRDF) parameters is presented. The original data stems from the National Aeronautics and Space Administration (NASA) of the USA which is making available maps of BRDF parameters that are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The first parameter fiso describes the isotropic part of the BRDF while the two others fvol and fgeo describe the anisotropic part and are linked to the viewing and illuminating geometry. The original data has been averaged for each calendar month for the period 2004–2011 and a spatial completion of data was performed, especially in water-covered areas. The resulting complete maps are available in ten spectral bands: [459–479] nm, [545–565] nm, [620–670] nm, [400–700] nm, [841–876] nm, [1230–1250] nm, [1628–1652] nm, [2105–2155] nm, [250–5000] nm, [700–5000] nm, [250–5000] nm. The maps form a Global Earth Observation System of Systems (GEOSS) Data Collection of Open Resources for Everyone (Data-CORE) supporting the GEOSS Data Sharing Principles. They are referenced by the doi:10.23646/85d2cd5f-ccaa-482e-a4c9-b6e0c59d966c and available in NetCDF format under the Creative Commons license CC-BY.

scholarly journals Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework

2021 ◽  
Vol 13 (17) ◽  
pp. 3541
Author(s):  
Jianyu Zheng ◽  
Xin Huang ◽  
Supriya Sangondimath ◽  
Jianwu Wang ◽  
Zhibo Zhang
Keyword(s):  
Vital Role ◽  
Parallel Execution ◽  
Observation System ◽  
Single Node ◽  
Spectral Bands ◽  
Service Oriented ◽  
Moderate Resolution ◽  
Level 3 ◽  
Earth Observation System ◽  
Moderate Resolution Imaging Spectroradiometer

MODIS (Moderate Resolution Imaging Spectroradiometer) is a key instrument onboard NASA’s Terra (launched in 1999) and Aqua (launched in 2002) satellite missions as part of the more extensive Earth Observation System (EOS). By measuring the reflection and emission by the Earth-Atmosphere system in 36 spectral bands from the visible to thermal infrared with near-daily global coverage and high-spatial-resolution (250 m ~ 1 km at nadir), MODIS is playing a vital role in developing validated, global, interactive Earth system models. MODIS products are processed into three levels, i.e., Level-1 (L1), Level-2 (L2) and Level-3 (L3). To shift the current static and “one-size-fits-all” data provision method of MODIS products, in this paper, we propose a service-oriented flexible and efficient MODIS aggregation framework. Using this framework, users only need to get aggregated MODIS L3 data based on their unique requirements and the aggregation can run in parallel to achieve a speedup. The experiments show that our aggregation results are almost identical to the current MODIS L3 products and our parallel execution with 8 computing nodes can work 88.63 times faster than a serial code execution on a single node.

scholarly journals Quality Assessment of PROBA-V LAI, fAPAR and fCOVER Collection 300 m Products of Copernicus Global Land Service

2020 ◽  
Vol 12 (6) ◽  
pp. 1017 ◽  
Author(s):  
Beatriz Fuster ◽  
Jorge Sánchez-Zapero ◽  
Fernando Camacho ◽  
Vicente García-Santos ◽  
Aleixandre Verger ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Accuracy Assessment ◽  
Observation System ◽  
Good Precision ◽  
Area Index ◽  
Global Land ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Temporal Profiles ◽  
Absorbed Photosynthetically Active Radiation

The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data.

scholarly journals Satellite retrievals of dust aerosol over the Red Sea, 2005–2015

2016 ◽  
Author(s):  
Jamie R. Banks ◽  
Helen E. Brindley ◽  
Georgiy Stenchikov ◽  
Kerstin Schepanski
Keyword(s):  
Red Sea ◽  
Dust Aerosol ◽  
The North ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Southern Half ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Highly Correlated ◽  
Summer Time

Abstract. The inter-annual variability of dust aerosol presence over the Red Sea is analysed, with respect to the summer-time latitudinal gradient in dust loading, which is at a maximum in the far south of the Red Sea and at a minimum in the far north. Two satellite aerosol optical depth (AOD) products from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify this loading over the region. Over an eleven-year period from 2005–2015 the July mean SEVIRI AODs at 630 nm vary between 0.48 and 1.45 in the southern half of the Sea, while in the north this varies between 0.22 and 0.66. Validating the AOD retrievals using ship-based measurements from 2010–2015, both instrument retrievals are highly correlated with the surface measurements, with biases of +0.02 for SEVIRI and +0.03 for MODIS. However, inter-retrieval biases are observed to occur at higher dust loadings, with pronounced positive MODIS-SEVIRI AOD biases at AODs greater than ~1. Co-located MISR data indicate broadly equal but opposite biases by the two retrievals when the MISR AOD > 1, +0.12 for MODIS and −0.10 for SEVIRI as compared with MISR, indicating substantial and systematic differences between the retrievals over the Red Sea at high dust loadings.

First-Light Imagery from Suomi NPP VIIRS

2013 ◽  
Vol 94 (7) ◽  
pp. 1019-1029 ◽  
Author(s):  
Donald Hillger ◽  
Thomas Kopp ◽  
Thomas Lee ◽  
Daniel Lindsey ◽  
Curtis Seaman ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Fire Detection ◽  
Satellite System ◽  
Defense Meteorological Satellite Program ◽  
Wide Range ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Low Levels ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Meteorological Satellite

The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011, heralding the next generation of operational U.S. polar-orbiting satellites. It carries the Visible– Infrared Imaging Radiometer Suite (VIIRS), a 22-band visible/infrared sensor that combines many of the best aspects of the NOAA Advanced Very High Resolution Radiometer (AVHRR), the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. VIIRS has nearly all the capabilities of MODIS, but offers a wider swath width (3,000 versus 2,330 km) and much higher spatial resolution at swath edge. VIIRS also has a day/night band (DNB) that is sensitive to very low levels of visible light at night such as those produced by moonlight reflecting off low clouds, fog, dust, ash plumes, and snow cover. In addition, VIIRS detects light emissions from cities, ships, oil flares, and lightning flashes. NPP crosses the equator at about 0130 and 1330 local time, with VIIRS covering the entire Earth twice daily. Future members of the Joint Polar Satellite System (JPSS) constellation will also carry VIIRS. This paper presents dramatic early examples of multispectral VIIRS imagery capabilities and demonstrates basic applications of that imagery for a wide range of operational users, such as for fire detection, monitoring ice break up in rivers, and visualizing dust plumes over bright surfaces. VIIRS imagery, both single and multiband, as well as the day/night band, is shown to exceed both requirements and expectations.

Measuring radiant emissions from entire prescribed fires with ground, airborne and satellite sensors – RxCADRE 2012

2016 ◽  
Vol 25 (1) ◽  
pp. 48 ◽  
Author(s):  
Matthew B. Dickinson ◽  
Andrew T. Hudak ◽  
Thomas Zajkowski ◽  
E. Louise Loudermilk ◽  
Wilfrid Schroeder ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Imaging System ◽  
Combustion Process ◽  
Measurement Development ◽  
Wide Range ◽  
Remotely Piloted Aircraft ◽  
Radiative Power ◽  
Moderate Resolution ◽  
Satellite Sensors ◽  
Moderate Resolution Imaging Spectroradiometer

Characterising radiation from wildland fires is an important focus of fire science because radiation relates directly to the combustion process and can be measured across a wide range of spatial extents and resolutions. As part of a more comprehensive set of measurements collected during the 2012 Prescribed Fire Combustion and Atmospheric Dynamics Research (RxCADRE) field campaign, we used ground, airborne and spaceborne sensors to measure fire radiative power (FRP) from whole fires, applying different methods to small (2 ha) and large (>100 ha) burn blocks. For small blocks (n = 6), FRP estimated from an obliquely oriented long-wave infrared (LWIR) camera mounted on a boom lift were compared with FRP derived from combined data from tower-mounted radiometers and remotely piloted aircraft systems (RPAS). For large burn blocks (n = 3), satellite FRP measurements from the Moderate-resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors were compared with near-coincident FRP measurements derived from a LWIR imaging system aboard a piloted aircraft. We describe measurements and consider their strengths and weaknesses. Until quantitative sensors exist for small RPAS, their use in fire research will remain limited. For oblique, airborne and satellite sensors, further FRP measurement development is needed along with greater replication of coincident measurements, which we show to be feasible.

scholarly journals Bi-Directional Reflectance Factor Determination of the Railroad Valley Playa

2019 ◽  
Vol 11 (22) ◽  
pp. 2601 ◽  
Author(s):  
Bruegge ◽  
Coburn ◽  
Elmes ◽  
Helmlinger ◽  
Kataoka ◽  
...  
Keyword(s):  
Correction Factor ◽  
Correction Term ◽  
Vicarious Calibration ◽  
Rapid Acquisition ◽  
Reflectance Factor ◽  
Moderate Resolution ◽  
Surface Measurements ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Spectrometer Data

Vicarious calibration is the determination of an on-orbit sensor’s radiometric response using measurements over test sites such as Railroad Valley (RRV), Nevada. It has the highest accuracy when a remote sensor’s view angle is aligned with that of the surface measurements, namely at a nadir view. For view angles greater than 10, the dominant error is the uncertainty in the off-nadir correction factor. The factor is largest in the back-scatter principal plane and can reach 20%. The Orbiting-Carbon Observatory has access to a number of datasets to determine this deviation. These include measurements from field instruments such as the Portable Apparatus for Rapid Acquisition of Bidirectional Observation of the Land and Atmosphere (PARABOLA), as well as satellite measurements from Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS). The correction factor derived from PARABOLA is consistent in time and space to within 2% for view angles as large as 30. Field spectrometer data show that the correction term is spectrally invariant. For this reason, a time-invariant model of RRV surface reflectance, along with empirically derived coefficients, is sufficient to use in the calibration of off-nadir sensors, provided there has been no recent rainfall. With this off-nadir correction, calibrations can be expected to have uncertainties within 5%.

scholarly journals Viewing Geometry Dependencies in MODIS Cloud Products

2010 ◽  
Vol 27 (9) ◽  
pp. 1519-1528 ◽  
Author(s):  
B. C. Maddux ◽  
S. A. Ackerman ◽  
S. Platnick
Keyword(s):  
Zenith Angle ◽  
Global Radiation ◽  
Cloud Amount ◽  
Radiation Budget ◽  
Cloud Properties ◽  
Wide Range ◽  
Moderate Resolution ◽  
Level 3 ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure

Abstract Characterizing the earth’s global cloud field is important for the proper assessment of the global radiation budget and hydrologic cycle. This characterization can only be achieved with satellite measurements. For complete daily coverage across the globe, polar-orbiting satellites must take observations over a wide range of sensor zenith angles. This paper uses Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 data to determine the effect that sensor zenith angle has on global cloud properties including the cloud fraction, cloud-top pressure, effective radii, and optical thickness. For example, the MODIS cloud amount increases from 57% to 71% between nadir and edge-of-scan (∼67°) observations, for clouds observed between 35°N and 35°S latitude. These increases are due to a combination of factors, including larger pixel size and longer observation pathlength at more oblique sensor zenith angles. The differences caused by sensor zenith angle bias in cloud properties are not readily apparent in monthly mean regional or global maps because the averaging of multiple satellite overpasses together “washes out” the zenith angle artifact. Furthermore, these differences are not constant globally and are dependent on the cloud type being observed.

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