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At least 55 records · Page 3

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

Many land applications require more frequent observations than can be obtained from a single 'Landsat class' sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Reflectance↗

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗

The Harmonized Landsat and Sentinel-2 Surface Reflectance Data Set

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a VirtualConstellation (VC) of surface reflectance (SR) data acquired by the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) aboard Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, bidirectional reflectance distribution function normalization and spectral bandpass adjustment. Three products are derivedfrom the HLS processing chain: (i) S10: full resolution MSI SR at 10 m, 20 m and 60 m spatial resolutions; (ii)S30: a 30 m MSI Nadir BRDF (Bidirectional Reflectance Distribution Function)-Adjusted Reflectance (NBAR);(iii) L30: a 30 m OLI NBAR. All three products are processed for every Level-1 input products from Landsat 8/OLI (L1T) and Sentinel-2/MSI (L1C). As of version 1.3, the HLS data set covers 10.35 million km2 and spans from first Landsat 8 data (2013); Sentinel-2 data spans from October 2015. The L30 and S30 show a good consistency with coarse spatial resolution products, in particular MODIS Collection 6 MCD09CMG products (overall deviations do not exceed 11%) that are used as a reference for quality assurance. The spatial co-registration of the HLS is improved compared to original Landsat 8 L1T and Sentinel 2A L1C products, for which misregistration issues between multi-temporal data are known. In particular, the resulting computed circular errors at 90% for the HLS product are 6.2 m and 18.8 m, for S10 and L30 products, respectively. The main known issue of the current data set remains the Sentinel-2 cloud mask with many cloud detection omissions. The cross-comparison with MODIS was used to flag products with most evident non-detected clouds. A time series outlier filtering approach is suggested to detect remaining clouds. Finally, several time series are presented to highlight the high potential of the HLS data set for crop monitoring.

Landsat Sentinel-2↗

Solid-State Lighting Using Side-by-Side White Phosphorescent Organic Light-Emitting Diodes

White organic light-emitting diodes (WOLEDs) have become increasingly popular for use in solid-state illumination, where diffuse, large area light sources that achieve a high color rendering index and luminous power efficiency are desirable. Color-tunable emission, where the light source combines emission from multiple, separately addressed color elements, is conveniently provided by WOLEDs for the purpose of adapting the lighting source to a particular illumination requirement. In this work, we demonstrate a method for side-by-side positioning of monochromatic blue and yellow phosphorescent OLED stripes that are combined to create tunable white light, using a high resolution mechanical peel-off patterning method. We achieve a peak luminous power efficiency of 17.1 ± 0.3 lm W –1 and an external quantum efficiency of 11.8 ± 0.2% and demonstrate color tunability of the 1960 Commission Internationale d’Eclairage chromaticity coordinates from (u,v) = (0.33,0.36) to (0.12,0.32). This corresponds to a tuning rnge of the color rendering index from 74 ± 1 to 86 ± 1 and the correlated color temperature from 2000 to 8000 ± 500 K. Here, due to the nondestructive nature of the peel-off technique, patterned devices exhibit a lifetime comparable to conventional, shadow mask-patterned devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Power Operations of the Mars Exploration Rovers

The rovers of the National Aeronautics and Space Administration’s (NASA) Mars Exploration Rovers (MER) project, Spirit (MER-A) and Opportunity (MER-B), safely landed on the surface of Mars three weeks apart during January 2004. Spirit and Opportunity were built and operated by the Jet Propulsion Laboratory (JPL), which is managed by the California Institute of Technology (Caltech) for NASA. Spirit landed at Gusev Crater, 14.8 degrees south of the equator, and operated continuously on the surface of Mars from January 4, 2004 until last contact from Spirit on March 22, 2010. Opportunity landed at Meridiani Planum, a location 2.5 degrees south of the Martian equator. Opportunity operated continuously on the Martian surface from January 25, 2004 until the last received transmission from Opportunity on June 10, 2018. The goal of the MER project was to determine if Mars ever had a habitable environment, in particular, if it ever had water. During their missions, both Spirit and Opportunity found evidence that liquid water once flowed on the surface of Mars. Both Spirit and Opportunity used a 1.33 m2 triple-junction solar array as their power sources. Based on observations of the original Mars rover, the Sojourner rover of the Mars Pathfinder mission that landed on Mars on July 4, 1997, the expectation was that the Martian dust would rapidly accumulate on the solar arrays of Spirit and Opportunity, and that the rovers would not have enough energy to continue operations after 90 Martian days (sols). Instead, due in part to lower dust accumulation rates than expected and numerous dust cleaning events, the Spirit and Opportunity rovers continued to operate on the Martian surface for over 2000 sols (MER-A) and 5000 sols (MER-B), respectively. During this time, the rovers experienced multiple Martian winters and several dust storms. Because the sources of solar array energy loss were known, the solar array energy output offered a method to scientifically estimate the loading and aeolian removal of dust from the solar arrays each sol. The MER Power operations team called this value that they calculated the solar array Dust Factor (DF). Dust Factor was defined as the fraction of sunlight that penetrates the accumulated dust on the surface of the solar array. A Dust Factor of 1.0 would indicate that the solar array was perfectly clean. A Dust Factor of 0.6 would indicate that only 60% of the available sunlight was able to penetrate the accumulated dust on the solar arrays. The MER Power subsystem operations team used the Multi-Mission Power Analysis Tool (MMPAT) to perform these Dust Factor calculations. The MMPAT software tool modeled the behavior of the solar arrays and the batteries as they interacted with the spacecraft power loads over the mission timeline. MMPAT also had knowledge (through telemetry and user inputs) of telemetered Power subsystem voltages and currents, atmospheric opacity (Tau), rover surface location, rover attitude, the planetary tilt and distance of Mars from the sun based on day of year, the instantaneous elevation of the sun based on time of day, temperatures (internal and external), terrain masking, and shadowing (due to the camera mast and antennas). Once all of the known sources of array energy loss are accounted, the remaining difference between the expected array energy and the actual array energy determines the solar array Dust Factor. The assumptions made while determining the Dust Factor are 1) that the single measured atmospheric opacity value (Tau) is constant over the course of the entire sol, 2) there is no measurable solar cell degradation, 3) there are no shorted strings and therefore, 4) all unexpected solar array energy losses are due to accumulated dust on the solar array. Although it cannot provide an absolute measure of dust loading, the determination of solar array Dust Factor provides a useful way of tracking dust accumulation and aeolian dust removal trends on Martian spacecraft. Any spacecraft on the Martian surface is vulnerable to dust, especially solar-powered spacecraft. The Spirit and Opportunity rovers were operational on the Martian surface for much longer than expected due in part to aeolian removal of dust from their solar arrays. The first few dust removal events were a pleasant surprise to the MER operations teams; however, over time a pattern began to arise. In over three Mars Years on the surface, the Power operations team tracked the solar array Dust Factor at Gusev Crater (location of MER-A) and observed that there were several significant dust removal and deposition events in Mars Year (MY) 27, even in the absence of a large dust storm. In MY 28 at Gusev Crater, the large atmospheric opacity (Tau) increase lagged significant dust removal events. Overall at Gusev Crater, there was a pattern of steady dust accumulation on the solar arrays, with a small number of significant dust cleaning events. At Meridiani Planum, where Opportunity rover operated for over seven Mars Years (late MY 26 to mid MY 34), a clear and consistent pattern of dust movement emerged. Meridiani Planum had a predictable, seasonally dependent pattern of gradual and continuous dust accumulation and removal. In summary, this paper explains the reasons for the development of the solar array Dust Factor and how it was used in mission operations. In particular, this paper describes the MMPAT software package, how it models array energy, including the important assumptions, model inputs and sources of error. And finally, this paper will show how the calculated solar array Dust Factor was used at Gusev Crater and Meridiani Planum to predict dust accumulation rates and weather patterns, and the importance of this generated data set for current and future solar- powered missions to Mars, such as the InSight lander and the planned Mars Sample Return rover.

Chin, Keith B.↗

The Sensitivity of Coded Mask Telescopes

Simple formulae are often used to estimate the sensitivity of coded mask X-ray or gamma-ray telescopes, but t,hese are strictly only applicable if a number of basic assumptions are met. Complications arise, for example, if a grid structure is used to support the mask elements, if the detector spatial resolution is not good enough to completely resolve all the detail in the shadow of the mask or if any of a number of other simplifying conditions are not fulfilled. We derive more general expressions for the Poisson-noise-limited sensitivity of astronomical telescopes using the coded mask technique, noting explicitly in what circumstances they are applicable. The emphasis is on using nomenclature and techniques that result in simple and revealing results. Where no convenient expression is available a procedure is given which allows the calculation of the sensitivity. We consider certain aspects of the optimisation of the design of a coded mask telescope and show that when the detector spatial resolution and the mask to detector separation are fixed, the best source location accuracy is obtained when the mask elements are equal in size to the detector pixels.

Skinner, Gerald K.↗

Hexagonal uniformly redundant arrays for coded-aperture imaging

Uniformly redundant arrays are used in coded-aperture imaging, a technique for forming images without mirrors or lenses. This technique is especially important for the high energy X-ray and gamma-ray region above 20 kev. In this technique, a mask consisting of opaque (closed) and trasparent (open) areas is placed between the photon sources to be imaged and a position sensitive detector or a detector array. Each source casts a shadow pattern of the mask or aperture onto the detector. This shadow pattern may be viewed as an encoded signal for that source direction. If each possible source code is unique, the detected composite of overlapping shadow patterns may be decoded to produce an image of the source distribution.

Finger, M. H.↗

Detailed Characterization of CZT Detector Response for Improved Coded-Aperture Imaging Performance

Gamma-ray imaging is a powerful method for locating and quantifying sources of radiation. The coded-aperture technique demonstrates superior angular resolution in comparison to other methods (e.g., Compton reconstruction). In this method, a mask constructed of highly attenuating material encodes the scene as a shadow pattern on a position-sensitive detector; this pattern can then be used to recreate the origin(s) of incident radiation. This is typically done through convolution of the mask and shadow patterns. Iterative methods which attempt to reconstruct the observed shadow pattern using a weighted combination of simulated patterns may also be employed. In either case, errors in event position reconstruction due to detector imperfections alter the shadow pattern and will therefore degrade system performance and may introduce imaging artifacts. These effects can be mitigated with a detailed understanding of such errors – allowing for the generation of representative simulations that include the errors and/or correction of raw imager data to remove the errors. We present a calibration process for a commercially available cadmium zinc telluride (CZT) gamma imager which provides a comprehensive characterization of the spatial and energy dependence of event reconstruction. By illuminating a mask featuring a regular grid of pinholes with a calibration source, the localized response of the detector can be measured with fine granularity. These local responses are combined to generate a full detector response map which can be used to distort simulations in a manner that is representative of the observed detector data. Details of the calibration procedure and an assessment of the impact of its end products on the performance of iterative imaging methods will be presented.

Ziock, Klaus-Peter↗

Method of Modeling and Simulation of Shaped External Occulters

The present invention relates to modeling an external occulter including: providing at least one processor executing program code to implement a simulation system, the program code including: providing an external occulter having a plurality of petals, the occulter being coupled to a telescope; and propagating light from the occulter to a telescope aperture of the telescope by scalar Fresnel propagation, by: obtaining an incident field strength at a predetermined wavelength at an occulter surface; obtaining a field propagation from the occulter to the telescope aperture using a Fresnel integral; modeling a celestial object at differing field angles by shifting a location of a shadow cast by the occulter on the telescope aperture; calculating an intensity of the occulter shadow on the telescope aperture; and applying a telescope aperture mask to a field of the occulter shadow, and propagating the light to a focal plane of the telescope via FFT techniques.

Lyon, Richard G.↗

An X-ray shadowgraph to locate transient high-energy celestial sources

A new technique has been developed to locate strong, transient X-ray sources such as the recently discovered gamma ray bursts. The instrument, termed a shadowgraph, locates sources by detecting the X-ray shadow cast by a large occulting mask pattern on an imaging detector. Angular resolutions of from 2 to 10 arc minutes are obtainable while essentially full sky coverage is maintained. The optimum energy range of operation is between 20 keV and 100 keV. The high efficiency X-ray imaging detectors, which make it possible to locate bursts with intensities down to approximately 10 photons/sq cm sec, are capable of detecting single 20 keV photons with a spatial resolution of approximately 0.2 mm. The detectors consist of an X-ray to optical conversion phosphor, a multistage image intensifier, and a CCD image readout.

Fishman, G. J.↗

Influence of auditory fatigue on masked speech intelligibility

Intelligibility of PB word lists embedded in simultaneous masking noise was evaluated before and after fatiguing-noise exposure, which was determined by observing the number of words correctly repeated during a shadowing task. Both the speech signal and the masking noise were filtered to a 2825-3185-Hz band. Masking-noise leves were varied from 0- to 90-dB SL. Fatigue was produced by a 1500-3000-Hz octave band of noise at 115 dB (re 20 micron-Pa) presented continuously for 5 min. The results of three experiments indicated that speed intelligibility was reduced when the speech was presented against a background of silence but that the fatiguing-noise exposure had no effect on intelligibility when the speech was made more intense and embedded in masking noise of 40-90-dB SL. These observations are interpreted by considering the recruitment produced by fatigue and masking noise.

Parker, D. E.↗

Comparison of Cloud Detection Algorithms for Sentinel-2 Imagery

Accurate, automated cloud and cloud shadow detection is a key component of the processing needed to prepare optical satellite imagery for scientific analysis. Many existing cloud detection algorithms rely on temperature information to identify clouds, making detection difficult for imagers that lack a thermal band, like Sentinel-2. To get maximum benefit from Sentinel-2 products it is critical to understand which algorithms best identify clouds and their shadows in images. We examined the relative performance of five different cloud-masking algorithms (Sen2Cor, MAJA, LaSRC, Fmask and Tmask) in 6 Sentinel-2 scenes (28 total images) distributed across the Eastern Hemisphere. Expanding on these comparisons, we tested ensemble approaches to improve results. We tested three ensemble approaches to cloud and shadow classification based on the outputs of the five initial algorithms using the cloud masks in: (1) a majority prediction model; (2) a random forests model; and (3) a conditional logic model. Accuracy assessments show a trade-off between omission and commission errors in cloud detection for individual algorithms across all sites, and some algorithms are better at detecting either clouds or cloud shadows. No single algorithm outperforms the others for both clouds and shadows. Aggregating the results from multiple algorithms produces fewer undetected clouds and higher overall accuracy than any single algorithm, with as high as 2.7% improvement over the top-performing algorithm, suggesting an ensemble approach may be the most useful for processing of Sentinel-2 data.

Sentinel-2↗

Clouds, Radiation, and Climate from the Earth Observing System

In this presentation, I will present and discuss key areas of scientific uncertainty in understanding climate and global change, focusing on specific examples of how EOS will contribute to improving our understanding of global change. In particular, I will describe how scientists intend to use MODIS, an earth-viewing cross-track scanning spectroradiometer to be flown on the Earth Observing System (EOS) AM-1 satellite to be launched in summer 1998, for the remote sensing of cloud properties. MODIS will scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and will provide images in 36 spectral bands between 0.415 and 14-235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmosphere processes. As part of this presentation, I will review the various methods that have been developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. Additional applications of MODIS data to the determination of precipitable water over land will be described, as will the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, shadows on the ground, and fires. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application to aircraft and/or satellite measurements.

King, Michael D.↗

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Platnick, Steven↗

New Multispectral Cloud Retrievals from MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

King, Michael D.↗

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the Aqua satellite in May 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using MODIS data, focusing primarily on (i) the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using MODIS observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).

King, Michael D.↗

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

King, Michael D.↗

MODIS Direct Broadcast and Remote Sensing Applications

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Tsay, Si-Chee↗