AVHRR Channels Research Articles

A case study on the determination of fog optical depth and liquid water path using AVHRR data and relations to fog liquid water content and horizontal visibility

An improved direct method is presented for the calculation of fog optical depth and liquid water path from fog top albedo using AVHRR channel 1. Fog top albedo is determined by means of a simple ra...

Mapping land surface emissivity using AVHRR data application to La Mancha, Spain

Abstract Land surface temperature can be determined applying the split‐window technique to the AVHRR channels 4 and 5. However, for this purpose the knowledge of land surface emissivities in the AVHRR channels 4 and 5 is essential. The paper proposes a simple method for mapping the difference between channels 4 and 5 surface emissivities (?? = ?4 ‐ ?5) at the AVHRR spatial scale. The method is based on the availability of radiosounding data coincident to the NOAA overpass for the study area and on the knowledge of the mean value of the land surface emissivity for channels 4 and 5 (? = (?4 + ?5)/2). Therefore, two simple methods for measuring and mapping the mean value of emissivity are also proposed, which use a reference calibrated sand and the normalized difference vegetation index (NDVI), respectively. And finally, a complete example of application of the methodology developed on the La Mancha region, Spain, is shown.

東北画像データベース

Using the NOAA-HRPT data received at the Tohoku University, a satellite image database for regional researches is produced at the Computer Center of the university. The database is called“Tohoku Image Database: TIDAS”. The TIDAS is open for public, and can be accessed through computer networks. The albedo and brightness temperature processed from the AVHRR channel 2 and channel 4 are geocoded, and sent to the Computer Center for TIDAS production every day. The TIDAS contains the satellite images in 99.2% of the days from April, 1990 to the present. This paper describes the overall features of the TIDAStogether with the related background.

Considerations on problems of NOAA GVI data for global land cover monitoring

Abstract Normalized Difference Vegetation Index (NDVI) in Global Vegetation Index (GVI) products from AVHRR which are provided by NOAA has been founded useful for global land cover monitoring. Though NDVI was designed to eliminate an effect of the change of solar illumination, there are some problems which still have to be removed, such as effects of the solar zenith angle, sampling method of GVI pixels, AVHRR channel degradation, scan angle, atmospheric condition and cloud contamination. In this paper, all factors are described with the emphasis on the effect of solar zenith angle. The effect of solar zenith angle on NDVI was simulated by LOWTRAN 7. The change of solar zenith angle by the delay of equator crossing local time and scan angle was clarified. Furthermore it is indicated that effects of the above factors on temporal variation of weekly NDVI data can be divided into low frequency variation and high frequency variation.

Retrieval of land and sea surface temperature using NOAA-11 AVHRR· data in north-eastern Brazil

Abstract The split-window method is investigated and a simple airborne atmospheric correction model for thermal data is proposed. Analysis shows that the atmospheric transmittance has a quadratic behaviour with the water vapour content in the first few kilometres of a wet atmosphere. The effect of the emissivity is evaluated for the retrieval of surface temperature using data from NOAA-11 AVHRR channels 4 and 5 for two extreme atmospheres. The results indicate that a spectral emissivity variation (Δe) in channels 4 and 5 of ±0.01 is not as important for a wet atmosphere as for a dry atmosphere. The split-window algorithm developed in this work has its parameters dependent on the atmospheric state and the values of these parameters are determined by using radiosonde profiles. Data from eighty-five radiosondes have been used to determine and check the local seasonal equatorial split-window parameters. The results of surface temperature retrieval show that the local seasonal equatorial and daily split-window...

Imation of land surface emissivity differences in the split-window channels of AVHRR

A method for estimating the difference between the channel emissivities in NOAA-AVHRR Channels 4 and 5 is proposed and applied to a data set from the HAPEX-MOBILHY experiment. The method is based on the separation between the atmospheric and emissivity effects in the brightness temperature difference measured with AVHRR Channels 4 and 5. Atmospheric profiles coincident to the satellite overpass and a radiative transfer model are required to estimate the atmospheric correction for brightness temperatures. With this procedure, the emissivity difference Δε is obtained at the satellite spatial and spectral resolution, which has a great interest for correcting thermal images with the split-window technique. The order of magnitude of the error related to the method proposed has been estimated by means of a sensitivity analysis to be better than 0.005.

Detection and removal of cloud contamination from AVHRR images

Describes the characteristics and performance of an algorithm designed to remove the effects of cloud contamination from AVHRR composite images over land. Using information in the temporal NDVI profile, the algorithm detects cloud-contaminated pixels, and optionally replaces these with interpolated values of individual AVHRR channels or channel transformations. As tested, the algorithm detects only those effects of residual clouds that result in a temporary decrease of the NDVI. It was found that the algorithm is capable of identifying clouds of varying opacity as well as cloud shadows present in the composites, and that its use appears preferable to compositing over longer periods. The algorithm can be applied without the need for ancillary information, e.g., on expected surface radiance conditions. Although developed for use in biospheric studies in Canada, it could also be applied at other latitudes where the seasonal trajectories of satellite-derived variables exhibit a single maximum or, by extension, a single minimum. >

AVHRR bidirectional reflectance effects and compositing

The purpose of this study was to assess the magnitude of bidirectional reflectance distribution (BRD) effects in AVHRR Channels 1 and 2 over land, their dependence on land cover, and the possibility of correcting for these effects as part of the AVHRR compositing process. The study was carried out in central Canada using cloud free full (1 km) resolution AVHRR images over 20 days near the peak green period in 1988. All images were coregistered and resampled. Uniform sample sites representing cropland, deciduous and coniferous forest, and wetlands were chosen using Landsat images. The effect of atmospheric corrections and the performance of three vegetation indices were also assessed. The results showed that BRD effects in the AVHRR data depend on land cover type, spectral band, the viewing geometry, and the degree of atmospheric correction. Atmospheric corrections increased the value of NDVI but reduced its variation with satellite zenith angle. BRD dependence in AVHRR Channels 1 and 2 could be modeled quite accurately, but spectral band- and land cover-specific model parameters were required for a good fit with the measurements. It is concluded that in AVHRR compositing based on the maximum NDVI value, the most-cloud-free pixel selection should precede atmospheric corrections and the correction for BRD effects. BRD correction models should be derived using data with similar spectral and spatial characteristics, preferably from the same sensor.

AVHRR split window temperature differences and total precipitable water over land surfaces

Abstract Measurements from the thermal infrared split window channels of the AVHRR sensor were investigated for their relationship to the total atmospheric water vapour amount over land surfaces. The difference in brightness temperature between the AVHRR channel 4 and 5 (10·3–11·3μm and 11·4–12·3μm respectively) was found to be a linear function of total precipitable water, for several stations in differing climatic regimes. For each individual location the total precipitable water was estimated with a standard error ranging from 0·22 to 0·48 cm for the complete range of conditions from wet to dry season or summer to winter. For mid-latitude continental locations there is very little influence of atmospheric aerosols on the relationship while for the African Sahel region the effect of large airborne particulates with a silicate component introduces a significant effect at large values of aerosol optical depth due to absorption. The influence of spectral emissivity variation in the split window region was also observed for arid regions where there is a significant quartz component to the soil. It is concluded that for regional retrieval of precipitable water, this technique provides sufficient accuracy for application to correction of near-infrared satellite data such as AVHRR channel 2 (0·71 –0·98 μm), however the site specific relation between T 4-T 5 and PW needs to be established with independent PW measurements.

Fire and glint in AVHRR's channel 3: a possible reason for the non-saturation mystery

Abstract Evidence from a very strong and rare case of sunglint in a NOAA-11 AVHRR image is used to show that a problem exists in the on-board signal processing of channel 3. This problem, associated only with targets of high reflectivity and/or temperature, causes erroneous indication of digital counts (DN) and calculated brightness temperatures for near-saturation ranges in channel 3 images. The explanation proposed, a spurious conversion of the sensor signal to DNs, fits observations of sunglint and fire detection data in AVHRR images of the NOAA-series satellites which could not otherwise be explained.

On the atmospheric dependence of the split-window equation for land surface temperature

Abstract A split-window equation is derived for land surface temperature, yielding T = T4 + A(T4 − T5) + B(e), where T is the true surface temperature, T4 and T5 are the brightness temperatures measured in AVHRR channels 4 and 5, A is a coefficient related to the atmospheric transmittances in AVHRR channels 4 and 5, being dependent on the atmosphere type and independent on surface emissivity, and B(e) takes into account the emissivity effect, which depends on both the channel surface emissivities (e4 and e5) and the atmosphere type. The atmospheric dependence of split-window coefficients, A and B(e), is discussed by means of satellite measurements simulations and in situ data. It is shown that linear, global-scale algorithms can produce inaccurate estimates of surface temperature when they are applied to areas of reduced atmospheric variability. A simple, non-linear split-window algorithm has been proposed, in which A = a0+ a1(T4− T5). The constants a0and a1 have been calculated from a set of in situ and ...

A parametrised bispectral model for savanna fire detection using AVHRR night images

Abstract Ten years ago Dozier presented a bispectral model for the detection of sub-resolution high temperature features in NOAA AVHRR satellite images. This model builds on Planck's law and theoretically derives brightness temperatures and fractions of sub-resolution fields of high temperatures, such as wildfires, using AVHRR channel 3 and 4 thermal data. The original Dozier model was based on a larger number of assumptions. Most fire detection studies have therefore turned to simpler approaches. Still, the original model has been successfully applied in several fire studies in various ecosystems. Lately, some studies have tried to refine the model. In this study the Dozier model has been modified through inclusion of some steps of parametrisation and applied for savanna fire detection. The parametrisa-tion gives an operational and unbiased approach to extract the temperature of the non-burning part of the ground resolution cell. To bypass the problem of reflected solar radiation in the daytime in the AV...

Calibration Results forNOAA-11AVHRR Channels 1 and 2 from Congruent Path Aircraft Observations

A method for using congruent atmospheric path aircraft-satellite observations to calibrate a satellite radiometer is presented. A calibrated spectroradiometer aboard a NASA ER-2 aircraft at an altitude of 19 km above White Sands (New Mexico) was oriented to view White Sands at the overpass time of the NOAA-11 AVHRR instrument along the same view vector as the satellite instrument. The data from six flights between November 1988 and October 1990 were transformed into corresponding estimates of AVHRR channel radiance at the satellite (derived from the aircraft measurements), and average counts (from the AVHRR measurements), both averaged across the footprint of the spectroradiometer. Prelaunch measurements of the AVHRR spectral response profiles are assumed, and the radiance spectrum measured by the spectroradiometer was adjusted to satellite altitude using the LOWTRAN-7 computer code. Results show reduced gains in both channel 1 (0.65 micron) and channel 2 (0.85 micron), compared to prelaunch values, with little further reduction in gain after 200 days in orbit. Results for the gain ratio (channel 1/channel 2), which is important for the calculation of the normalized vegetation index, show constant in-orbit values 5 percent above the prelaunch value.

Towards a quantitative interpretation of vegetation indices Part 1: Biophysical canopy properties and classical indices

Abstract The information content of vegetation indices currently derived from satellite observations is discussed using a physically‐based approach. These indices can, in principle, be related to some of the biophysical properties of the canopy through a complex set of equations, provided atmospheric effects, the anisotropy of the coupled surface‐atmosphere system, and the morphology and optical heterogeneity of the canopy are taken into account. Atmospheric effects are discussed on the basis of an approximate analytical expression applicable to vegetation indices built from AVHRR channels 1 and 2. These indices strongly depend on the aerosol and water vapor content, a fact that limits their quantitative interpretation in terms of physical and biophysical properties of the canopy. The interaction between the electromagnetic solar radiation and the surface is discussed using physical models of albedos developed for vegetation canopies. Finally, the biophysical leaf model PROSPECT is used to parameterize re...

Estimation of surface heat and moisture fluxes over a prairie grassland: 4. Impact of satellite remote sensing of slow canopy variables on performance of a hybrid biosphere model

Herein, we present the results of a series of numerical experiments using the Ex‐BATS biosphere model, which is an adaptation of Dickinson's biosphere‐atmosphere transfer scheme (BATS). These simulations are used to assess how the model performs when remotely sensed data are used to estimate three key canopy variables. These canopy variables, which effectively represent the slowly changing boundary conditions of a vegetated surface, consist of the total surface albedo, leaf area index, and the nondiurnally varying component of stomatal resistance, referred to as stressed stomatal resistance. The surface albedo is retrieved from NOAA‐AVHRR (advanced very high resolution radiometer) channel 1 spectral reflectance information in conjunction with a directional reflectance model which accounts for the strong diurnal variations in surface reflectance. A 4‐channel vegetation index also retrieved from AVHRR measurements is used to estimate the leaf area index. A similar index derived from high‐resolution SPOT visible and near‐infrared information has been used to describe the spatial variations in such indices which impact the retrieval of the leaf area index. Satellite retrieval of stomatal resistance is based on split‐window skin temperatures from AVHRR channels 4 and 5 from the afternoon overpass (∼1630 LT). Variables derived from the hourly skin temperature observations of GOES‐VISSR have also been examined with respect to retrieval of stomatal resistance. It was found that although stomatal resistance has little correlation with the diurnal amplitude of skin temperature, it is closely related to the daily maximum of skin temperature. Numerical experiments have been conducted to examine model sensitivity to each of these canopy variables. Results indicate that Ex‐BATS is not sensitive to small variations of surface albedo or leaf area index within the range of estimation uncertainty. The rms measurement‐model flux differences in every numerical trial were within 6 W m−2 of the rms differences obtained for the simulations performed using measured albedo and leaf area index. Measured stomatal resistance values were obtained using an inversion form of the model. The resulting stomatal resistances were used to perform a control experiment simulating an ideal satellite retrieval scenario involving one observation per day. The control experiment resulted in improvements of approximately 20 W m−2 in the rms flux differences over the model using a purely hypothetical formulation for stomatal resistance. Simulations using the remotely retrieved stomatal resistances produced significantly reduced rms differences for latent and sensible heat fluxes over the model using the hypothetical formulation. Based on a 55‐day composite involving all days from the four FIFE intensive field campaigns, the sensible and latent heat flux improvements are approximately 25 and 20%, respectively (11 and 8 W m−2). The satellite retrievals are only 20 and 30% less accurate (7 and 10 W m−2) than the idealized results of the control experiment.

Comparison of different sensor data and characteristics of cirrus clouds

Abstract The result of the analysis on the data without atmospheric correction observed with MESSR and VTIR onboard MOS-1, VISSR onboard GMS-3 and AVHRR onboard NOAA-9 indicate the following features. Thin cirrus identified on the image of high gain mode MESSR with albedo of 1 % higher than the sea surface affects the observed sea surface temperature by 1.5°C. The data obtained with GMS VISSR visible channel show a better result than that with VTIR for the target of lower albedo, while observed temperature with VISSR shows about 1 °C lower than that observed with Channel-3 VTIR. The albedo of the sea surface computed from the data of VISSR shows lower value ranging from 1 to 2 % while higher by 1 to 2 % compared with AVHRR channel 1 and 2 respectively. The observed temperature with VISSR is about 1 °C lower than that with Channel 4 of AVHRR while almost equal to that of Channel 5 of AVHRR. The result of adjustment on working bandwidth indicates a fairly good agreement of the values observed with different sensors over targets of comparatively uniform albedo and temperature leading to a conclusion on the advantage of multiple satellites' data in the fields requiring data of frequent observation or in the places where a chance of getting a cloudless image is rare.

Cellular convection over the north‐eastern Atlantic

AbstractConvective clouds over the ocean frequently exhibit organized meso‐scale patterns. A statistical evaluation of 4 years of NOAA satellite images over the north‐eastern Atlantic yields climatological data of the appearance of these patterns and shows that open cellular convection is most abundant. For this convection type, surface and radiosonde data from Weathership M have been analysed. Open convection cells appear at a wide range of positive sea‐air temperature differences up to 12°C and at wind speeds up to 25 m s−1. All diameters have been found to be less than 80 km (average 41 km). Larger diameters are, on average, associated with slightly larger convection heights and, thus, with larger aspect ratios.The scene‐averaged brightness temperature of AVHRR channel 4 exhibits a definite correlation with the sea‐air temperature difference and, less well expressed, with the sensible and latent heat flux. This, in turn, provides a possibility of estimating those quantities by using easily accessible AVHRR satellite data.

Pattern recognition analysis of polar clouds during summer and winter

A pattern recognition algorithm is demonstrated which classifies eighteen surface and cloud types in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the cloud properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for cloud type and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy cloud cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric cloud.

Spatial variability of land surface emissivity in the thermal infrared band: Spectral signature and effective surface temperature

Experimental access to effective surface parameters, surface temperature, and emissivity, relevant to satellite investigations in the thermal infrared band (TIR), is addressed and discussed. The spatial variability of the broad (8–14μ) emissivity was measured over an overall homogeneous area with a movable measuring system. Spectral ground radiances were also measured at many places, the spatial average of which is assumed to represent the effective spectral ground radiance. The effective surface temperature is obtained through renormalization of the effective emissivity signature over the RMS broad band emissivity previously measured. The method is shown to produce the effective surface temperature with an accuracy better than 1 K, without any direct temperature measurement. From the effective signature, the channel emissivities pertaining to a given instrument can be calculated. This has been done for NOAA-11/AVHRR Channels 4 and 5. A preliminary test was made to try and validate nighttime satellite-derived surface temperature by comparison with field effective temperature. The image was acquired during the field experiment. The first result of this attempt is encouraging, although only qualitative because of standard atmospheric corrections. Orientation of future work for better accuracy and reliability is discussed as well.

Atmospheric correction for land surface temperature using NOAA-11 AVHRR channels 4 and 5

In this work, a theoretical model that permits relating the land surface temperature with the temperatures measured by thermal infrared sensors has been developed. The model has been derived by linearization of Planck's function and atmospheric trasmittance. In this way a split-window equation is obtained, which depends on atmospheric water vapor, viewing angle, and channel surface emissivities. Simulations of satellite measurements of land surface temperatures are made using the atmospheric transmittance-radiance model LOWTRAN-7 for NOAA-11 AVHRR Channels 4 and 5. From these simulations the accuracies of linearizations have been checked. The dependence of the split-window coefficients on the aforementioned magnitudes has been analyzed. Thus, it has been demonstrated that the angular dependence can be avoided while the total water vapor dependence must be retained. Therefore, we have obtained a split-window equation for each atmosphere in which the emissivity dependence is linearized in terms of Channel 4 emissivity ϵ 4 and channel emissivity difference, ϵ 4–ϵ 5. The analysis of the emissivity influence shows that the emissivity measurement should be made with an accuracy of 0.005 in order to get an error below to 0.4 K on land surface temperature. Finally, two applications of the split-window method for obtaining sea surface temperature and crop temperatures have been included.