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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Evaluating atmospheric correction models for retrieving surface temperatures from the AVHRR over a tallgrass prairie

The effects of atmospheric attenuation on surface radiative temperatures obtained by the AVHRR over a tallgrass prairie area in the Flint Hills of Kansas are examined. Six atmospheric correction models developed primarily for sea-surface temperature studies are used to test their utility for retrieval of radiative temperatures over the land surface. An uncertainty of + or - 3.0 C was found for the AVHRR data, and used to evaluate the performance of a given model. When the difference between in situ and AVHRR surface temperatures was smaller than the uncertainty, the model was judged to be adequate. Among the six models evaluated, only the NOAA split-window model consistently adjusted the AVHRR surface temperatures within + or - 3.0 C of the in situ measurements.

Cooper, D. I.↗
NASA NTRS1990

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.↗
NASA NTRS1989

Analysis of forest disturbance using TM and AVHRR data

A methodology that will be used to determine the proportions of undisturbed, successional vegetation and recently disturbed land cover within coniferous forests using remotely sensed data from the advanced very high resolution radiometer (AVHRR) is presented. The method uses thematic mapper (TM) data to determine the proportions of the three stages of forest disturbance and regrowth for each AVHRR pixel in the sample areas, and is then applied to interpret all AVHRR imagery. Preliminary results indicate that there are predictable relationships between TM spectral response and the disturbance classes. Analysis of ellipse plots from a TM classification of the disturbed forested landscape indicates that the forest classes are separable in the red (0.63-0.69 micron) and near-infrared (0.76-0.90 micron) bands, providing evidence that the proportion of disturbance classes may be determined from AVHRR data.

Spanner, Michael A.↗
NASA NTRS1990

Retrieval of precipitable water from AVHRR split window imagery

The application of the split window variance ratio (SWVR) technique for estimating precipitable water values to AVHRR data in order to study regional and mesoscale moisture variability over land is examined. The formulation of the SWVR technique is based on the strong correlation between precipitable water and the split window channel transmittance ratio. The square of the transmittance ratio is estimated from the observed brightness temperature scene variations. The application of the SWVR technique to AVHRR data for the retrieval of total precipitable water involves calculating the split wind channel image variances and then relating the variance ratio to precipitable water. Preliminary results of the application of the SWVR technique to several passes of AVHRR imagery indicate that precipitable water values consistent with ground truth and other remote sensing measurements can be derived from AVHRR data.

Jedlovec, Gary L.↗
NASA NTRS1993

Calibration results for NOAA-11 AVHRR 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.

Abel, Peter↗
NASA NTRS1993

Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

Emery, William↗
NASA NTRS1994

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.

Key, Jeff↗
NASA NTRS1995

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Key, Jeff↗
NASA NTRS1995

Sea ice motions in the Central Arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.

Emery, William↗
NASA NTRS1994

Retrieval of sizes and total masses of particles in volcanic clouds using AVHRR bands 4 and 5

The advanced very high resolution radiometer (AVHRR) sensor on polar orbiting NOAA satellites can discriminate between volcanic clouds and meteorological clouds using two-band data in the thermal infrared. This paper is aimed at developing a retrieval of the particle sizes, optical depth, and total masses of particles from AVHRR two-band data of volcanic clouds. Radiative transfer calculations are used with a semi-transparent cloud model that is based on assumptions of spherical particle shape, a homogeneous underlying surface, and a simple thin cloud parallel to the surface. The model is applied to observed AVHRR data from a 13-hour old drifting cloud from the August 19, 1992, eruption of Crater Peak/Spurr Volcano, Alaska. The AVHRR data fit in the range of results calculated by the model, which supports its credibility. According to the model results, the average of effective particle radius in the test frame of this cloud is in the range of 2 to 2.5 micrometer, the optical depth at 12 micrometer is about 0.60 - 0.65. The total estimated mass of ash in the air amounts to 0.24 - 0.31 x 10(exp 6) tons, which is about 0.7-0.9% of the mass measured in the ashfall blanket. Sensitivity tests show that the mass estimate is more sensitive to the assumed ash size distribution than it is to the ash composition.

Wen, Shiming↗
NASA NTRS1993

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

Steffen, K.↗
NASA NTRS1997

NOAA AVHRR Land Surface Albedo Algorithm Development

The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 micro-m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 micro-m) and near-IR (0.7-1.3 micro-m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.

Toll, D. L.↗
NASA NTRS2001

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

Fowler, Charles↗
NASA NTRS2008

Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

Brown, Molly E.↗
NASA NTRS2015

Evaluation of Long-Term Calibrations of the AVHRR Visible Radiances

Two systematic calibrations have been compiled for the visible radiances measured by the series of AVHRR instruments flown on the NOAA operational polar weather satellites: one by the International Satellite Cloud Climatology Project (ISCCP), anchored on NASA ER-2 underflights in the 1980s and early 1990s and covering the period 1981-2009, and one by the PATMOS-x project, anchored on comparisons to the MODIS instruments on the Aqua and Terra satellites in the 2000s and covering the period 1979-2010 (this result also includes calibration for the near-IR channels). Both methods have had to extend their anchor calibrations over a long series of instruments using different vicarious approaches, so a comparison provides an opportunity to evaluate how well this extension works by cross-checking the results at the anchor points. The basic result of this comparison is that for the ''afternoon'' series of AVHRRs, the calibrations agree to within their mutual uncertainties. However, this retrospective evaluation also shows that the representation of the time variations can be simplified. The ISCCP procedure had much more difficulty extending the calibration to the ''morning'' series of AVHRRs with the calibrations for NOAA-15 and NOAA-17 exceeding the estimated uncertainties. Given the general agreement, a new calibration for all AVHRR visible radiances (except TIROS-N, NOAA-6, NOAA-19, and MetOp-A) is proposed that is based on the average of the best linear fits to the two time records. The estimated uncertainty of these calibrations is 63% absolute (scaled radiance units).

Advanced Very High Resolution Radiometer↗
NASA NTRS1984

Surface vegetative biomass modelling from combined AVHRR and Landsat satellite data

A methodology for the estimation of regional biomass on the basis of Landsat and Polar Orbiter Satellite Advanced Very High Resolution Radiometer (AVHRR) imagery has been developed by the present study, which concentrated on the Sierra Nevada-Cascade Mountains ecological province of California. The Landsat data are only used initially, to calibrate the AVHRR-based biomass data. The essential element of the present approach is a 'pixel proportions' model. An integer block of Landsat pixels corresponds to each AVHRR pixel. The Landsat pixels are converted into biomass pixels using species biomass expression equations available in the literature.

Logan, T. L.↗
NASA NTRS1986

Directional reflectance response in AVHRR red and near-IR bands for three cover types and varying atmospheric conditions

Surface directional red and near-infrared reflectances of bare soil, orchard grass, and fescue were extracted from a multitemporal data set to correspond to NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) scanning and illumination geometry at 30 deg latitude. Radiances were simulated at satellite altitude and a ratio vegetation index was calculated. The results show that off-nadir directional reflectance measured at the surface in the red and near-IR portions of the spectrum are approximately maintained with AVHRR viewing and illumination characteristics. The two-channel reflectance response is such that the ratio vegetation index is more constant with scan angle and atmospheric conditions than individual channels. It is shown that inclusion of atmospheric and surface reflectance data can greatly improve interpretation of AVHRR data, when knowledge of the range of atmospheric conditions and approximate directional reflectances of major cover types are known.

Holben, B.↗
NASA NTRS1989

Evidence for Phanerozoic reactivation of the Najd Fault System in AVHRR, TM, and SPOT images of central Arabia

SPOT stereoscopic and TM multispectral images support evidence in AVHRR thermal-IR images of a major unmapped shear zone in Phanerozoic cover rocks southeast of the ancient Najd Fault System in the Arabian Shield. This shear zone and faults of the Najd share a common alignment, orientation, and sinistral sense of movement. These similarities suggest a 200-km extension of the Najd Fault System and reactivation since it formed in the late Precambrian. Topographic and lithologic features in the TM and SPOT data along one of three faults inferred from the AVHRR data indicate sinistral offsets up to 2.5 km, en echelon folds and secondary faults like those predicted by models of left-lateral strike-slip faulting. The age of the affected outcrops indicates reactivation of Najd faults in the Cretaceous, judging from TM and SPOT data or in the Tertiary, based on AVHRR data. The total length of the system visible at the surface measures 1300 km. If the Najd Fault System is extrapolated beneath sands of the Empty Quarter to faults of a similar trend in South Yemen, the shear zone would span the Arabian Plate. Furthermore, if extensions into the Arabian Sea bed and into Egypt proposed by others are considered, it would exceed 3000 km.

Andre, Constance G.↗