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NASA NTRSDate not supplied

MISR Level 1B2 Terrain Data (MI1B2T_V3)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Terrain data are re-projected to the terrain altitude. In this product, surface data from all cameras will appear in the same geographic location. Thus, this product is the primary input to Level 2 aerosol/surface processing, which requires co-registration of the L1B2 imagery at the surface. Clouds will still be displaced due to their elevation above the surface, but this time with respect to the terrain rather than the ellipsoid. (The mountain location T is now assigned the geographic location at T, and the Cloud at F appears at the geographic location T.) In Level 2 aerosol/surface processing, algorithms are applied to screen out the clouds. Terrain data only exist for MISR blocks containing some land. [Location=GLOBAL LAND] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track).; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

IMAGERY↗
NASA NTRSDate not supplied

MISR Level 2 TOA/Cloud Classifier parameters (MIL2TCCL_V2)

The TOA/Cloud Classifiers contain the Angular Signature Cloud Mask (ASCM), a scene classifier calculated using support vector machine technology (SVM) both of which are on a 1.1 km grid, and cloud fractions at 17.6 km resolution that are available in different height bins (low, middle, high) and are also calculated on an angle-by-angle basis. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=17.6 km; Longitude_Resolution=17.6 km; Horizontal_Resolution_Range=10 km - < 50 km or approximately .09 degree - < .5 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, Daily - < Weekly].

AM-1↗
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗
NASA NTRSDate not supplied

MISR Level 2 Aerosol parameters (MIL2ASAE_V1)

The Aerosol data contain aerosol optical depth, aerosol physical model, ancillary meteorological data, and related parameters. The aerosol data include tropospheric aerosol optical depth, Angstrom exponent and single scattering albedo on 17.6 km centers, aerosol mixture identifier and retrieval residuals, and ancillary data including assumed ozone optical depth and retrieval flags. For complete information about the aerosol mixtures, the user will need to order the MISR Aerosol Climatology Product (MIANACP) to obtain Aerosol Physical and Optical Properties (APOP) and the Mixture files. The Mixture files list up to 3 component models used in each mixture, with their relative compositional fractions, and includes ancillary information such as single scattering albedo. The APOP gives detailed information for the component particle models. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km - 17.6 km; Longitude_Resolution=1.1 km - 17.6 km; Horizontal_Resolution_Range=1 km - < 10 km or approximately .01 degree - < .09 degree; Temporal_Resolution=about 15 orbits/day].

CIRRUS OPTICAL DEPTH↗
NASA NTRS2021

Multi-Angle Imager for Aerosols (MAIA) spectral and radiometric calibration

The Multi-angle Imaging SpectroRadiometer (MISR) was launched as part of NASA’s Terra satellite suite of instruments. Still operational, it makes use of observations from multiple view angles to retrieve aerosol abundance and particle properties. The Multi-Angle Imager for Aerosols (MAIA) instrument improves on this heritage by incorporating polarimetry and an expanded spectral range. Combining these data with surface measurements, the relationship between pollution and human health will be explored. MAIA has just completed camera testing, building on the experience from MISR. Spectral calibration now makes use of a double subtractive monochromator, built with the intent to allow the exit slit output to be uniform in spectral content. For radiometric testing, hardware upgrades have included adding UV lamps to the 1.65 cm (65") integrating sphere, use of a NIST-traceable sphere to establish absolute radiances, and the addition of a UV transfer spectrometer to support characterization of the sphere output from 300 to 2500 nm. During camera build, Newton’s rings were observed in the detector Quantum Efficiency (QE) measurements. This is due to etaloning within the detector itself. Etaloning was also evident in the spectral and radiometric characterizations performed on the completed camera. Spectral metrics, including center wavelength and width, are presented here using a moment’s analysis. This better represents the band properties, particularly in bands where fringing is observed, as compared to a full-width at half-maximum determination. It is believed that the MAIA camera has been carefully characterized, and meet its spectral and radiometric requirements.

Harten, Gerard Van↗
NASA NTRS2005

Comparison of Coincident Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depths over Land and Ocean Scenes Containing Aerosol Robotic Network Sites

The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), launched on 18 December 1999 aboard the Terra spacecraft, are making global observations of top-of-atmosphere (TOA) radiances. Aerosol optical depths and particle properties are independently retrieved from these radiances using methodologies and algorithms that make use of the instruments corresponding designs. This paper compares instantaneous optical depths retrieved from simultaneous and collocated radiances measured by the two instruments at locations containing sites within the Aerosol Robotic Network (AERONET). A set of 318 MISR and MODIS images, obtained during the months of March, June, and September 2002 at 62 AERONET sites, were used in this study. The results show that over land, MODIS aerosol optical depths at 470 and 660 nm are larger than those retrieved from MISR by about 35% and 10% on average, respectively, when all land surface types are included in the regression. The differences decrease when coastal and desert areas are excluded. For optical depths retrieved over ocean, MISR is on average about 0.1 and 0.05 higher than MODIS in the 470 and 660 nm bands, respectively. Part of this difference is due to radiometric calibration and is reduced to about 0.01 and 0.03 when recently derived band-to-band adjustments in the MISR radiometry are incorporated. Comparisons with AERONET data show similar patterns.

Moderate Resolution Imaging Spectroradiometer (MOD↗
NASA NTRS2003

On-Orbit Cross-Calibration of AM Satellite Remote Sensing Instruments using the Moon

On April 14,2003, three Earth remote sensing spacecraft were maneuvered enabling six satellite instruments operating in the visible through shortwave infrared wavelength region to view the Moon for purposes of on-orbit cross-calibration. These instruments included the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer on the Earth Observing System (EOS) Terra spacecraft, the Advanced Land Imager (ALI) and Hyperion instrument on Earth Observing-1 (EO-1) spacecraft, and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the SeaStar spacecraft. Observations of the Moon were compared using a spectral photometric mode for lunar irradiance developed by the Robotic Lunar Observatory (ROLO) project located at the United States Geological Survey in Flagstaff, Arizona. The ROLO model effectively accounts for variations in lunar irradiance corresponding to lunar phase and libration angles, allowing intercomparison of observations made by instruments on different spacecraft under different time and location conditions. The spacecraft maneuvers necessary to view the Moon are briefly described and results of using the lunar irradiance model in comparing the radiometric calibration scales of the six satellite instruments are presented here.

Butler, James J.↗
NASA NTRS2011

October Cloud Increases Over the Arctic Ocean as Observed by MISR and CALIPSO

The Beaufort and East Siberian Sea (BESS) shows a large increase in surface air temperature (SAT) in the recent decade for months of Sep-Nov, and NASA's Terra satellite have provided valuable measurements for this important decade of the intensified Arctic warming. In particular, MISR data since 2000 and CALIPSO cloud measurements since 2006 reveal a significant increase of low cloud cover in October, which is largest in the daylight Arctic months (March-October). Causes of the warming remain unclear; but increased absorption of summer solar radiation and autumn low cloud formation have been suggested as a positive ice-temperature-cloud feedback in the Arctic. The observed increase of low cloud cover supports the theorized positive ice-temperature-cloud feedback, whereby more open water in the Arctic Ocean increases summer absorption of solar radiation, and subsequent evaporation, which leads to more low clouds in autumn. Trapping longwave radiation, these clouds effectively lengthen the melt season and reduce perennial ice pack formation, making sea ice more vulnerable to the next melt season

Wu, Dong L.↗
NASA NTRS2010

MISR CMVs and Multiangular Views of Tropical Cyclone Inner-Core Dynamics

Multi-camera stereo imaging of cloud features from the MISR (Multiangle Imaging SpectroRadiometer) instrument on NASA's Terra satellite provides accurate and precise measurements of cloud top heights (CTH) and cloud motion vector (CMV) winds. MISR observes each cloudy scene from nine viewing angles (Nadir, +/-26(sup o), +/-46(sup o), +/-60(sup o), +/-70(sup o)) with approximatel 275-m pixel resolution. This paper provides an update on MISR CMV and CTH algorithm improvements, and explores a high-resolution retrieval of tangential winds inside the eyewall of tropical cyclones (TC). The MISR CMV and CTH retrievals from the updated algorithm are significantly improved in terms of spatial coverage and systematic errors. A new product, the 1.1-km cross-track wind, provides high accuracy and precision in measuring convective outflows. Preliminary results obtained from the 1.1-km tangential wind retrieval inside the TC eyewall show that the inner-core rotation is often faster near the eyewall, and this faster rotation appears to be related linearly to cyclone intensity.

hurricanes↗
NASA NTRSDate not supplied

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

The multispectral imaging sensors on the Terra platform have been operating for over two decades facilitating a variety of scientific applications. The MODIS sensor provides the largest spectral coverage of 0.41 to 14.2 μm, acquiring data at three different spatial resolutions, 250 m, 500 m, and 1 km. The MISR instrument views the Earth using nine discrete cameras pointed at fixed angles including viewing the nadir direction at a spatial resolution of 275 m and covering a wavelength range from 0.44 to 0.86 μm. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization, with calibration monitored on-orbit using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. Vicarious techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean and Dome Concordia, thereby covering the different parts of the dynamic range. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR.

Intercalibration↗
NASA NTRS2000

Recent Results From The Nasa Earth Science Terra Mission and Future Possibilities

The NASA Earth Sciences Enterprise has made some remarkable strides in recent times in using developing, implementing, and utilizing spaceborne observations to better understand how the Earth works as a coupled, interactive system of the land, ocean, and atmosphere. Notable examples include the Upper Atmosphere Research (UARS) Satellite, the Topology Ocean Experiment (TOPEX) mission, Landsat-7, SeaWiFS, the Tropical Rainfall Monitoring Mission (TRMM), Quickscatt, the Shuttle Radar Topography Mission (SRTM), and, quite recently, the Terra'/Earth Observing System-1 mission. The Terra mission, for example, represents a major step forward in providing sensors that offer considerable advantages and progress over heritage instruments. The Moderate Resolution Imaging Spectrometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Measurements of Pollution in the Troposphere (MOPITT), the Advanced Spaceborne Thermal Emissions and Reflections (ASTER) radiometer, and the Clouds and Earth's Radiant Energy System (CERES) radiometer are the instruments involved. Early indications in March indicate that each of these instruments are working well and will be augmenting data bases from heritage instruments as well as producing new, unprecedented observations of land, ocean, and atmosphere features. Several missions will follow the Terra mission as the Earth Observing mission systems complete development and go into operation. These missions include EOS PM-1/'Aqua', Icesat, Vegetation Canopy Lidar (VCL), Jason/TOPEX Follow-on, the Chemistry mission, etc. As the Earth Observing systems completes its first phase in about 2004 a wealth of data enabling better understanding of the Earth and the management of its resources will have been provided. Considerable thought is beginning to be placed on what advances in technology can be implemented that will enable further advances in the early part of the 21st century; e.g., in the time from of 2020. Concepts such as 'constellation' missions or 'formation flying' with 'sensorcraft', 'sensor webs', autonomous operation of satellites, more on-board processing and delivery to individual users, data synthesis and analysis in real-time, etc. are being considered. With the data now having been and soon to be received plus the very real possibilities of further advances in use and applicability of data the potential for very significant gains in knowledge for Earth studies and applications looks quite high in the next decade or two.

Salomonson, Vincent V.↗
NASA NTRSDate not supplied

MISR Geometric Parameters (MIB2GEOP_V2)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The MISR Level 1B2 Geometric Parameters data product is part of the georectified radiance product. It contains the geometric parameters which measure the sun and view angles at the reference ellipsoid. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=17.6 km; Longitude_Resolution=17.6 km; Horizontal_Resolution_Range=10 km - < 50 km or approximately .09 degree - < .5 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly].

AM-1↗
NASA NTRS2021

Calibration of the DSCOVR EPIC Visible and NIR Channels using Multiple LEO Radiometers

The first five years of operation of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange one point have produced results that uniquely complement the data from currently operating low orbit Earth-observing instruments. In this paper we describe an updated unified approach to EPIC calibration. In this approach, calibration coefficients and their trends were obtained by comparing EPIC observations to the measurements from polar orbiting radiometers. In this study L1B reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua and Terra satellites, Multi-angle Imaging Spectroradiometer (MISR) onboard Terra and Visible Infrared Imaging Radiometer (VIIRS) onboard the Suomi National Polar-orbiting Partnership (Suomi NPP) spacecraft were used to infer calibration coefficients for four EPIC visible and near-infrared channels: 443 nm, 551 nm, 680 nm, and 780 nm. EPIC Version three measurements made between June 2015 and August 2020 were used for comparison. The calibration procedure identifies the most homogeneous low Earth orbit radiometer scenes matching scattering angles that are temporarily and spatially collocated with EPIC observations. These scenes are used to determine reflectance to count (R/C) ratios in spectrally analogous channels. Seasonal average R/C ratios were analyzed to obtain EPIC calibration gains and trends. The trends for the full dataset period are not statistically significant except in the 443 nm channel. No significant changes in calibration were found after the instrument’s exit from safe hold in March 2020. The R/C ratios were also used to determine the differences in EPIC gains resulting from separate calibrations: against MODIS Aqua or Terra, as well as against forward or aftward MISR cameras. Statistical tests indicate that the differences between the two datasets are not significant except in the 780 nm channels where Aqua-derived coefficients may be around 2% lower compared to Terra. The dependence of EPIC calibration gains on the instrument scattering angle and on DSCOVR-Earth distance were investigated. Lastly, model Low Earth Orbit (LEO) reflectances calculated to match the EPIC viewing geometry were employed to study how EPIC calibration coefficients depend on EPIC-LEO viewing geometry differences. The effect of LEO and EPIC angular mismatch on calibration was shown to be small.

deep space climate observatory/earth polychromatic↗
NASA NTRSDate not supplied

MISR Level 1A CCD Science data, all cameras (MIL1A_V1)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

CCD↗
NASA NTRSDate not supplied

MISR Level 1A CCD Science data, all cameras (MIL1A_V2)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

AM-1↗
NASA NTRS2013

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

remote sensing↗
NASA NTRS2011

Multi-Sensor Aerosol Products Sampling System

Global and local properties of atmospheric aerosols have been extensively observed and measured using both spaceborne and ground-based instruments, especially during the last decade. Unique properties retrieved by the different instruments contribute to an unprecedented availability of the most complete set of complimentary aerosol measurements ever acquired. However, some of these measurements remain underutilized, largely due to the complexities involved in analyzing them synergistically. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have established a Multi-sensor Aerosol Products Sampling System (MAPSS), which consistently samples and generates the spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of aerosol products from multiple spacebome sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Samples of satellite aerosol products are extracted over Aerosol Robotic Network (AERONET) locations as well as over other locations of interest such as those with available ground-based aerosol observations. In this way, MAPSS enables a direct cross-characterization and data integration between Level-2 aerosol observations from multiple sensors. In addition, the available well-characterized co-located ground-based data provides the basis for the integrated validation of these products. This paper explains the sampling methodology and concepts used in MAPSS, and demonstrates specific examples of using MAPSS for an integrated analysis of multiple aerosol products.

Petrenko, M.↗