Moderate Resolution Imaging Spectroradiometer Instrument Research Articles

On‐orbit calibration and inter‐comparison of Terra and Aqua MODIS surface temperature spectral bands

Two moderate resolution imaging spectroradiometer (MODIS) instruments have been operating on board the NASA EOS Terra and Aqua spacecraft for 7 and 4.5 years, respectively. The MODIS is a cross‐track scanning radiometer that collects data in 36 spectral bands with wavelengths from visible (VIS) to long‐wave infrared (LWIR). MODIS thermal emissive bands (TEB) on‐orbit calibration is performed using an on‐board blackbody (BB). Bands 31 and 32, with centre wavelengths at 11 and 12 µm, are primarily used for surface temperature (ST) retrieval. This paper provides a brief description of MODIS TEB calibration methodology and presents bands 31 and 32 on‐orbit performance in terms of their calibration stability and detector noise characterization. It also describes an approach to examine the ST spectral band calibration consistency between two MODIS instruments using similar spectral channels of an advanced very high resolution radiometer (AVHRR) instrument currently operated on board NOAA‐16 and NOAA‐17. Inter‐comparison data sets are carefully selected from near‐simultaneous and near‐nadir observations made by each pair of MODIS and AVHRR instruments. Results show that ST spectral bands 31 and 32 in both the Terra and Aqua MODIS are performing better than their design requirements, with excellent calibration stability and satisfactory cross‐sensor calibration consistency. The on‐orbit noise equivalent temperature differences (NEdTs) of all detectors have been continuously below the design specifications of 0.05 K. The calibration coefficients are extremely stable with scan‐by‐scan variations of less than 0.10%. In addition, calibration differences between two MODIS instruments are less than 0.10 K for both bands 31 and 32.

Sources and assumptions for the vicarious calibration of ocean color satellite observations

Spaceborne ocean color sensors require vicarious calibration to sea-truth data to achieve accurate water-leaving radiance retrievals. The assumed requirements of an in situ data set necessary to achieve accurate vicarious calibration were set forth in a series of papers and reports developed nearly a decade ago, which were embodied in the development and site location of the Marine Optical BuoY (MOBY). Since that time, NASA has successfully used data collected by MOBY as the sole source of sea-truth data for vicarious calibration of the Sea-viewing Wide field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer instruments. In this paper, we make use of the 10-year, global time series of SeaWiFS measurements to test the sensitivity of vicarious calibration to the assumptions inherent in the in situ requirements (e.g., very low chlorophyll waters, hyperspectral measurements). Our study utilized field measurements from a variety of sources with sufficient diversity in data collection methods and geophysical variability to challenge those in situ restrictions. We found that some requirements could be relaxed without compromising the ability to vicariously calibrate to the level required for accurate water-leaving radiance retrievals from satellite-based sensors.

Terra and Aqua MODIS inter‐comparison of three reflective solar bands using AVHRR onboard the NOAA‐KLM satellites

Cross‐sensor inter‐comparison is important to assess calibration quality and consistency and ensure continuity of observational datasets. This study conducts an inter‐comparison of Terra and Aqua MODIS (the MODerate Resolution Imaging Spectroradiometer) to examine the overall calibration consistency of the reflective solar bands. Observations obtained from AVHRR (the Advanced Very High Resolution Radiometer) onboard the NOAA‐KLM series of satellites are used as a transfer radiometer to examine three MODIS bands at 0.65 (visible), 0.85 (near‐IR) and 1.64 µm (far near‐IR) that match spectrally with AVHRR channels. Coincident events are sampled at a frequency of about once per month with each containing at least 3000 pixel‐by‐pixel matched data points. Multiple AVHRR sensors on‐board NOAA‐15 to 18 satellites are used to check the repeatability of the Terra/Aqua MODIS inter‐comparison results. The same approach applied in previous studies is used with defined criteria to generate coincident and co‐located near nadir MODIS and AVHRR pixel pairs matched in footprint. Terra and Aqua MODIS to AVHRR reflectance ratios are derived from matched pixel pairs with the same AVHRR used as a transfer radiometer. The ratio differences between Terra and Aqua MODIS/AVHRR give an indication of the calibration biases between the two MODIS instruments. Effects due to pixel footprint mismatch, band spectral differences and surface and atmospheric bi‐directional reflectance distributions (BRDFs) are discussed. Trending results from 2002 to 2006 show that Terra and Aqua MODIS reflectances agree with each other within 2% for the three reflective solar bands.

Assessment of the Visible Channel Calibrations of the VIRS on TRMM and MODIS on Aqua and Terra

Abstract Several recent research satellites carry self-calibrating multispectral imagers that can be used for calibrating operational imagers lacking complete self-calibrating capabilities. In particular, the visible (VIS, 0.65 μm) channels on operational meteorological satellites are generally calibrated before launch, but require vicarious calibration techniques to monitor the gains and offsets once they are in orbit. To ensure that the self-calibrating instruments are performing as expected, this paper examines the consistencies between the VIS channel (channel 1) reflectances of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites and the version 5a and 6 reflectances of the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission using a variety of techniques. These include comparisons of Terra and Aqua VIS radiances with coincident broadband shortwave radiances from the well-calibrated Clouds and the Earth’s Radiant Energy System (CERES), time series of deep convective cloud (DCC) albedos, and ray-matching intercalibrations between each of the three satellites. Time series of matched Terra and VIRS data, Aqua and VIRS data, and DCC reflected fluxes reveal that an older version (version 5a, ending in early 2004) of the VIRS calibration produced a highly stable record, while the latest version (version 6) appears to overestimate the sensor gain change by ∼1% yr−1 as the result of a manually induced gain adjustment. Comparisons with the CERES shortwave radiances unearthed a sudden change in the Terra MODIS calibration that caused a 1.17% decrease in the gain on 19 November 2003 that can be easily reversed. After correction for these manual adjustments, the trends in the VIRS and Terra channels are no greater than 0.1% yr−1. Although the results were more ambiguous, no statistically significant trends were found in the Aqua MODIS channel 1 gain. The Aqua radiances are 1% greater, on average, than their Terra counterparts, and after normalization are 4.6% greater than VIRS radiances, in agreement with theoretical calculations. The discrepancy between the two MODIS instruments should be taken into account to ensure consistency between parameters derived from them. With the adjustments, any of the three instruments can serve as references for calibrating other satellites. Monitoring of the calibrations continues in near–real time and the results are available via the World Wide Web.

MODIS Polarization-Sensitivity Analysis

The moderate resolution imaging spectroradiometer (MODIS) is one of the primary instruments in the Earth Observing System (EOS). Currently, MODIS instruments are onboard the NASA EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. The MODIS reflective solar bands (RSBs) are sensitive to the polarization of incident light, particularly for the visible bands. To derive accurate top-of-the-atmosphere radiances, it is essential to know the polarization sensitivity, characterized by a polarization factor and phase angle, of the instruments. From prelaunch polarization sensitivity measurements, the polarization factors and phase angles for all visible and near-infrared bands of both instruments are derived, analyzed, and compared. The polarization factors are wavelength, angle of incidence on the MODIS scan mirror, and detector-dependent. For Terra MODIS, they are also mirrorside-dependent. The 412-nm band has the largest polarization factor, which is about 0.04 for both instruments. The polarization factors of all other bands are either smaller than or close to 0.02, which is the polarization requirement for the MODIS RSB whose wavelengths are longer than 412 nm. The unexpected one-, three-, and four-cycle anomalies observed in the measurements are analyzed. These anomalies are shown to be likely due to the nonuniformity of the light source and the retro-reflected light from the MODIS optical system. Their impacts on the derived polarization parameters are estimated and discussed.

A comparison of CMAQ‐based aerosol properties with IMPROVE, MODIS, and AERONET data

Evaluation of concentrations predicted by air quality models is needed to ensure that model results are compatible with observations. In this study aerosol properties derived from the Community Multiscale Air Quality (CMAQ) model‐simulated aerosol mass concentrations are compared with routine data from NASA satellite‐borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Sun‐synchronous Terra satellite, NASA's ground‐based Aerosol Robotic Network (AERONET), and the ground‐based Interagency Monitoring of Protected Visual Environment (IMPROVE) network. The motivation for this analysis is to determine how best to use these parameters in evaluating model‐predicted PM2.5 concentrations. CMAQ surface extinction estimates due to scattering at 550 nm wavelength are compared with the IMPROVE nephelometer data obtained from 25 sites within the United States. It is found that model‐predicted surface extinctions bear high correlations with nephelometer measured data. Sulfate fractional aerosol optical depth (AOD) is found to dominate in the northeastern part of the United States; hence ground‐based measurement of sulfate concentrations have been compared with time series of columnar AOD as observed by the MODIS instrument and also with the CMAQ‐predicted tropospheric column values obtained during the June–August period of 2001. CMAQ surface extinctions are found to be relatively higher than the IMPROVE nephelometer observations; however, there is a good agreement between CMAQ AOD trends and AERONET and MODIS data, obtained at the seven AERONET sites located in the eastern United States. CMAQ is also found to capture the day‐to‐day variability in the spatial AOD patterns. Monthly average satellite AOD estimates are found to be higher than the AOD data obtained using the CMAQ‐predicted aerosol concentrations. Seasonal variation of satellite‐measured aerosol intensive property “Angstrom exponent” (a gross indicator of the aerosol size distribution) is presented for four selected sites: one each in the eastern and central parts, and two in the western part of the continental United States. Variability of Angstrom exponent at these four selected sites is analyzed in conjunction with the variation of summertime AOD (observed and modeled), mass concentration (observed and modeled) and modeled SO4 average concentrations during the summer (June–August) period of the year 2001. Annual time series of Angstrom exponent data at the four selected sites show a large east‐west variation.

Principal Component Analysis of Remote Sensing of Aerosols Over Oceans

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We apply principal component analysis (PCA) to estimate how much information about atmospheric aerosols could be retrieved from solar-reflected radiances observed over oceans by a satellite sensor as a function of the number of wavelength bands, viewing angles, and Stokes parameters. It is assumed that our virtual satellite sensor can simultaneously perform multispectral, multiangle, and linear polarization measurements of the radiances, and the following quantities are used to vary: aerosol optical thickness, single-scattering albedo (SSA) of aerosol particles, height of the aerosol layer, aerosol model (includes size distribution parameters and optical properties), and wind speed. The real refractive index was kept constant and, therefore, is not part of the analysis. To calculate the number of significant principal components (SPCs), the cumulative percent variance rule is used, which takes into account anticipated errors of measurements. The reported results predict how much additional information can be retrieved from observations by adding more wavelength, angle, and polarization channels. For example, for the Moderate Resolution Imaging Spectroradiometer instruments <formula formulatype="inline"><tex>$(\lambda &gt; 0.5\ {\rm \mu}\hbox{m})$</tex></formula>, the number of SPCs is two to three; for Multiangle Imaging SpectroRadiometer, three to five; for Polarization and Directionality of the Earth Reflectances, five to ten; while for the future Glory/Aerosol Polarization Sensor instrument, it is 6–11 (when using eight out of its <formula formulatype="inline"><tex>$&gt;$</tex></formula> 100 view angles). The ranges reflect view conditions and analysis method. Our calculations show that the observations should be most sensitive to the aerosol model followed in decreasing order by optical thickness, SSA, and aerosol height. We found that there is no systematic increase in the information about aerosol starting from 10–15 view angles for unpolarized observations and 30 view angles for those with linear polarization. It is achievable with modern detectors to retrieve up to 10 and 16 SPCs from unpolarized and polarized observations, respectively. The methodology and results of our PCA can be useful for estimating the reliability of aerosol parameters retrieved from existing and future satellite observations. </para>

A comparison of algorithms for Near‐Real Time water vapour retrieval from MODIS

When studying the Earth's surface from space it is important that the component of the signal measured by the satellite‐based sensor due to the atmosphere is accurately estimated and removed. Such atmospheric correction requires good knowledge of atmospheric parameters including precipitable water (PW), ozone concentration and aerosol optical depth. To make full use of the capabilities of satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) these parameters should be accurately estimated in Near‐Real Time (NRT) with complete global coverage approximately every two days. NRT retrieval of the required ancillary information facilitates the atmospheric correction of such direct broadcast data from the MODIS instrument in the operational environment. In this paper three Near Infrared (NIR) algorithms for PW retrieval from MODIS are compared to determine which is most suitable for use in an operational MODIS‐based process for the atmospheric correction of spectral reflectance data. Two of the algorithms estimate PW in NRT and gave RMS errors of approximately 0.48 g cm−2 (23%) and 0.59 g cm−2 (28%), respectively, when compared against radiosonde data and modelled PW fields over Western Australia. The third algorithm was the NIR PW product from MODIS (MOD05) archived by the Distributive Active Archive Centre (DAAC). For the same locations the MOD05 NIR PW dataset gave an RMS error of approximately 0.95 g cm−2 (44%). In each of the cases the best results were obtained after optimal cloudmasking of the NIR data. In this paper, the accuracy and suitability of the three algorithms for use in the operational atmospheric correction of MODIS data are evaluated and the importance of an accurate cloudmask for atmospheric correction in NRT is discussed.

Development of the Aqua MODIS NDSI fractional snow cover algorithm and validation results

The principal purpose of this paper is to describe the development and validation of an algorithm to estimate the fraction of snow cover within a 500-m pixel of the Moderate Resolution Imaging Spectroradiometer (MODIS) operating on the Earth Observing System Aqua spacecraft. The performance of this algorithm and algorithms applicable to the MODIS on the Terra spacecraft are compared. Validation efforts show that both pixel-level, fractional snow cover relationships for the Terra and Aqua MODIS instruments work well as quantified by such measures as correlation coefficient (r) and root-mean-square error when compared to Landat-7 Enhanced Thematic Mapper ground-truth observations covering a substantial range of snow cover conditions. Over all the scenes used herein, the correlation coefficients were near 0.9 and the RMSE near 0.10. However, somewhat better performance was found for the Terra MODIS versus the Aqua MODIS over nearly concurrently observed scenes. Furthermore, it is clear that more improvements in fractional snow cover estimates within MODIS pixels should be pursued to better account for variability in slope and aspect, atmospheric effects, snow cover types, and land cover.

Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors

We describe a new global multiyear satellite fire product designed to meet the needs of the global modeling community. We use the new data set to analyze the global distribution of biomass burning using five different temporal metrics derived from 5 years of high‐quality satellite data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS), on board NASA's Terra satellite. The global distributions of fire pixel density, peak month, season length, and annual periodicity are described. As part of our analysis we show, for the first time, the global distribution of the fire radiative power (FRP), a relatively new remotely sensed quantity. We find that low FRP tends to be associated with areas of cropland burning. In the tropics and much of the subtropics, low FRP is also associated with more heavily forested areas, while higher FRP tends to occur in areas of grassland burning. In boreal forests this trend is reversed, with higher FRP occurring in areas of greater tree cover. We next combine 3 years of Terra and Aqua MODIS observations to show that a strong diurnal fire cycle is prevalent at tropical and subtropical latitudes. We also consider the consistency of the fire time series recorded by the two MODIS instruments, and find the month of peak burning and fire season length observed by each to be in good agreement in most areas. However, significant discrepancies with respect to seasonality do occur in some relatively small areas, and are most pronounced in tropical rain forest.

A New Method for Retrieving Band 6 of Aqua MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key research instrument for the NASA Earth Observing System (EOS) mission. It was successfully launched onboard the Terra satellite in December 1999 and Aqua satellite in May 2002. Both MODIS instruments have been working well except that 15 of the 20 detectors in Aqua MODIS band 6 (1.628-1.652 /spl mu/m) are either nonfunctional or noisy. The striping in Aqua MODIS band 6 caused by its nonfunctional or noisy detectors has been a serious problem for MODIS snow products, which use band 6 primarily for snow detection. MODIS scientists have been using Aqua MODIS band 7 (2.105-2.155 /spl mu/m) instead of band 6 for computing the normalized difference snow index to continue detecting global snow coverage. The main objective of this letter is to retrieve Aqua MODIS band 6 using other bands based on their relationships in Terra MODIS. The band retrieval approach proposed in this letter is also very useful for the next generation of MODIS sensor-the Visible/Infrared Imager/Radiometer Suite (VIIRS) band M10 proxy data generation. Such proxy data can support the VIIRS prelaunch end-to-end testing, postlaunch calibration/validation, and data quality checking.

Comparison of aerosol optical thickness measurements by MODIS, AERONET sun photometers, and Forest Service handheld sun photometers in southern Africa during the SAFARI 2000 campaign

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the NASA Terra satellite has been used to monitor aerosol optical thickness (AOT, τ) daily at 10 km×10 km resolution worldwide since August 2000. This information, together with the locations of active fires detected by the MODIS instrument, is essential for understanding the seasonal trends and interannual variability of fires and their impacts on air pollution, atmospheric chemistry, and global climate. We compared aerosol optical thickness derived from MODIS, five automated sun photometers of the Aerosol Robotic Network (AERONET), and 38 Forest Service (FS) handheld sun photometers in western Zambia from 20 August to 20 September 2000. Aerosol optical thicknesses derived from AERONET sun photometers and FS sun photometers were also compared in the same region between mid‐June and late September 2000. Our objectives were to validate the AOT measurements by MODIS and to investigate the factors that affect AOT measurements. We demonstrated that in the regions of intense biomass burning, MODIS aerosol optical thickness was consistently 40–50% lower at 470, 550, and 660 nm compared with ground‐based AOT measurements by automated and handheld sun photometers and airborne measurements by NASA Ames Airborne Tracking 14‐channel Sunphotometers (AATS‐14). The satellite look angles can influence the MODIS AOT values, with the actual MODIS AOT values being as much as 0.06 higher than model‐calculated MODIS AOT values on the right edge of the MODIS scene. This phenomenon may be due to error in the assumed aerosol scattering phase function or surface directional properties. Density of vegetation cover can also affect MODIS measurements of aerosol optical thickness.

Application of deep convective cloud albedo observation to satellite-based study of the terrestrial atmosphere: monitoring the stability of spaceborne measurements and assessing absorption anomaly

An objective method is developed to monitor the stability of spaceborne instruments, aimed at distinguishing climate trend from instrument drift in satellite-based climate observation records. This method is based on four-years of Clouds and the Earth's Radiant Energy System (CERES) broadband observations of deep convective cloud systems with cloud-top temperature lower than 205 K and with large optical depths. The implementation of this method to the CERES instrument stability analysis reveals that the monthly albedo distributions are practically the same for deep convective clouds with CERES measurements acquired from both the Tropical Rainfall Measuring Mission and Terra satellite platforms, indicating that CERES instruments are well calibrated and stable during both missions. Furthermore, with a nonlinear regression neural network narrowband-broadband conversion, this instrument-stability monitoring method can also be applied to narrowband instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Scanner (VIRS). The results show that the drifts associated with both VIRS and MODIS instruments are less than 1% during a four-year period. Since the CERES albedo measurements are highly accurate, the absorptance of these opaque clouds can be reliably estimated. The absorptions of these clouds from observations are around 25%, whereas the absorptions from theory can be as low as 18%, depending on ice cloud microphysics.

Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products

A major focus in global change research is to quantify the amount of gaseous and particulate pollutants emitted from terrestrial vegetation fires. Determination of the emitted radiant energy released during biomass combustion episodes (the so-called fire radiative energy or FRE) has been suggested as a new tool for determining variations in biomass combustion rates and the rate of production of atmospheric pollutants. We review the physical principals behind the remote determination of FRE and present an alternative method for its derivation via analysis of ‘fire pixel’ radiances in the middle infrared spectral region. We compare our method to the existing FRE retrieval approach used in the EOS Moderate Resolution Imaging Spectro-radiometer (MODIS) fire products, and to retrievals of FRE based on derived fire temperature and area made via the so-called Bi-spectral method. We test each FRE retrieval method using both simulated data and imagery from a new experimental space mission, the Bi-spectral InfraRed Detection (BIRD) small satellite, which has sensors specifically designed for the study of active fires. We analyse near simultaneous MODIS and BIRD data of the fires that burned around Sydney, Australia in January 2002. Despite the markedly different pixel size and spectral coverage of these sensors, where the spatial extent of the fire pixel groups detected by MODIS and BIRD are similar, the derived values of FRE for these fires agree to within ±15 %. However, in certain fires, the lower spatial resolution of MODIS appears to prevent many of the less intensely radiating fire pixels being detected as such, meaning MODIS underestimates FRE for these fires by up to 46% in comparison to BIRD. Though the FRE release of each of these low intensity fire pixels is relatively low, their comparatively large number makes their overall FRE significant. Thus, total FRE release of the Sydney fires on 5 January 2002 is estimated to be 6.5×10 9 J s −1 via BIRD but 4.0×10 9 J s −1 via MODIS. The ability of BIRD to resolve individual fire fronts further allows the first accurate calculation of ‘radiative’ fireline intensity from spaceborne measurements, providing values of 15–75 kJ s −1 m −1 for fire fronts that are up to 9 km in length. Finally, we analyse the effectiveness of the satellite-based FRE retrieval methods in estimating the FRE from the active flaming and smouldering components only (FRE Active, believed to be proportional to the rate of biomass combustion), despite the sensor receiving additional radiance from the ‘cooling ground’. The MIR radiance method appears particularly strong in this regard, allowing FRE Active to be estimated to within ±30% in the range 100–100,000 J s −1 m −2. These results provide further confidence in the ability of spaceborne missions to derive physically meaningful values of FRE that could be used to support biomass burning emissions inventories. Future comparisons between FRE derived via MODIS and those from higher spatial resolution BIRD or airborne imagery may allow the MODIS-derived FRE values to be ‘calibrated’ for any systematic underestimation. We therefore expect FRE to become an important tool for enhancing global studies of terrestrial vegetation fires with infrared remote sensing, particularly as the majority of large fires are now imaged four times per day via the MODIS instruments on the Terra and Aqua spacecraft.

Fire and smoke observed from the Earth Observing System MODIS instrument--products, validation, and operational use

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, launched on the National Aeronautics and Space Administration Terra satellite at the end of 1999, was designed with 36 spectral channels for a wide array of land, ocean, and atmospheric investigations. MODIS has a unique ability to observe fires, smoke, and burn scars globally. Its main fire detection channels saturate at high brightness temperatures: 500 K at 4 µm and 400 K at 11 µm, which can only be attained in rare circumstances at the 1 km fire detection spatial resolution. Thus, unlike other polar orbiting satellite sensors with similar thermal and spatial resolutions, but much lower saturation temperatures (e.g. Advanced Very High Resolution Radiometer and Along Track Scanning Radiometer), MODIS can distinguish between low intensity ground surface fires and high intensity crown forest fires. Smoke column concentration over land is for the first time being derived from the MODIS solar channels, extending from 0.41 µm to 2.1 µm. The smoke product has been provisionally validated both globally and regionally over southern Africa and central and south America. Burn scars are observed from MODIS even in the presence of smoke, using the 1.2 to 2.1 µm channels. MODIS burned area information is used to estimate pyrogenic emissions. A wide range of these fire and related products and validation are demonstrated for the wild fires that occurred in northwestern USA in Summer 2000. The MODIS rapid response system and direct broadcast capability is being developed to enable users to obtain and generate data in near real-time. It is expected that health and land management organizations will use these systems for monitoring the occurrence of fires and the dispersion of smoke within two to six hours after data acquisition.

Towards operational monitoring of terrestrial systems by moderate-resolution remote sensing

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is providing a series of products of unparalleled quality and sophistication for the observation and biophysical monitoring of the terrestrial environment. The capabilities of the MODIS sensor of NASA's Terra and Aqua platforms, in observing the terrestrial environment, are a precursor to the operational capabilities of the National Polar Operational Environmental Satellite System (NPOESS) series of missions, which will succeed the current polar operational capabilities of the NOAA series of satellites. Prior to NPOESS, the NPOESS Preparatory Project (NPP) will be launched, acting as a bridge between the two MODIS instruments and the longer term advanced operational capability. The result of these missions will be the establishment of long-term systematic, operational capabilities. Notwithstanding the improvements arising from these missions, there are many lessons to be learnt from current experiences in using MODIS data. Moreover, the timing of the implementation of these missions will provide challenges to users. Additionally, agencies must anticipate a rapid evolution of requirements associated with burgeoning terrestrial programs such as Global Observations of Forest Cover/Global Observations of Landcover Dynamics (GOFC/GOLD) and Terrestrial Carbon Observations (TCO).

Statistical Analysis of the Uncertainties in Cloud Optical Depth Retrievals Caused by Three-Dimensional Radiative Effects

Abstract This paper presents a simple yet general approach to estimate the uncertainties that arise in satellite retrievals of cloud optical depth when the retrievals use one-dimensional radiative transfer theory for heterogeneous clouds that have variations in all three dimensions. For the first time, preliminary error bounds are set to estimate the uncertainty of cloud optical depth retrievals. These estimates can help us better understand the nature of uncertainties that three-dimensional effects can introduce into retrievals of this important product of the Moderate Resolution Imaging Spectroradiometer instrument. The probability distribution of resulting retrieval errors is examined through theoretical simulations of shortwave cloud reflection for a set of cloud fields that represent the variability of stratocumulus clouds. The results are used to illustrate how retrieval uncertainties change with observable and known parameters, such as solar elevation or cloud brightness. Furthermore, the results i...

SCAR‐B fires in the tropics: Properties and remote sensing from EOS‐MODIS

Two moderate resolution imaging spectroradiometer (MODIS) instruments are planned for launch in 1999 and 2000 on the NASA Earth Observing System (EOS) AM‐1 and EOS PM‐1 satellites. The MODIS instrument will sense fires with designated 3.9 and 11 μm channels that saturate at high temperatures (450 and 400 K, respectively). MODIS data will be used to detect fires, to estimate the rate of emission of radiative energy from the fire, and to estimate the fraction of biomass burned in the smoldering phase. The rate of emission of radiative energy is a measure of the rate of combustion of biomass in the fires. In the Smoke, Clouds, and Radiation‐Brazil (SCAR‐B) experiment the NASA ER‐2 aircraft flew the MODIS airborne simulator (MAS) to measure the fire thermal and mid‐IR signature with a 50 m spatial resolution. These data are used to observe the thermal properties and sizes of fires in the cerrado grassland and Amazon forests of Brazil and to simulate the performance of the MODIS 1 km resolution fire observations. Although some fires saturated the MAS 3.9 μm channel, all the fires were well within the MODIS instrument saturation levels. Analysis of MAS data over different ecosystems, shows that the fire size varied from single MAS pixels (50×50 m) to over 1 km2. The 1×1 km resolution MODIS instrument can observe only 30–40% of these fires, but the observed fires are responsible for 80 to nearly 100% of the emitted radiative energy and therefore for 80 to 100% of the rate of biomass burning in the region. The rate of emission of radiative energy from the fires correlated very well with the formation of fire burn scars (correlation coefficient = 0.97). This new remotely sensed quantity should be useful in regional estimates of biomass consumption.

A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data

The authors have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical recession method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of hand-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE/spl Delta/T) and calibration accuracy specifications of the MODIS Instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 /spl mu/m IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K.

Indicators of land-cover change for change-vector analysis in multitemporal space at coarse spatial scales

Abstract Change-vector analysis in multi-temporal space is a powerful tool to analyse the nature and magnitude of land-cover change. The change vector compares the difference in the time-trajectory of a biophysical indicator for successive time periods. This change detection method is applied to three remotely-sensed indicators of land-surface conditions—vegetation index, surface temperature and spatial structure—in order to improve the capability to detect and categorize subtle forms of land-cover change. It is tested in a region of West Africa, using multi-temporal Local Area Coverage imagery obtained by the Advanced Very-High Resolution Radiometer on NOAA-9 and NOAA-II orbiting platforms. The three indicators show a low degree of redundancy and detect different land-cover change processes, which operate at different time scales. Change vector analysis is being developed for application to the land-cover change product to be produced using NASA's Moderate-Resolution Imaging Spectroradiometer instrument, scheduled for flight in 1998 and 2000on EOS-AM and -PM platforms.