Retrieval Of Surface Reflectance Research Articles

Atmospheric correction of Landsat ETM+ land surface imagery. I. Methods

To extract quantitative information from the Enhanced Thematic Mapper-Plus (ETM+) imagery accurately, atmospheric correction is a necessary step. After reviewing historical development of atmospheric correction of Landsat Thematic Mapper (TM) imagery, the authors present a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from ETM+ imagery under general atmospheric and surface conditions. This algorithm is therefore suitable for operational applications. A new formula that accounts for adjacency effects is also presented. Several examples are given to demonstrate that this new algorithm works very well under a variety of atmospheric and surface conditions.

Impact of variable atmospheric water vapor content on AVHRR data corrections over land

This paper explores the impact of the integrated water vapor content (IWV) in the atmospheric column on the corrections of optical satellite data over land. First, simulation runs were used to quantify the trends in red and near infrared parts of the electromagnetic spectrum. Second, advanced very high resolution radiometer (AVHRR) measurements obtained over Canada during the 1996 growing season, together with reanalyzed IWV content data, were employed to determine the actual impact of constant IWV values. Third, various options in characterizing IWV for atmospheric corrections of AVHRR composites were examined. It was found that (1) as expected, IWV affects near-infrared radiation substantially more than red, although the latter is also altered; (2) that additional, subtle interactions take place between IWV, radiance levels, and viewing geometry that influence the retrieved surface reflectance; (3) that spatial and temporal variation in IWV caused changes in the normalized difference vegetation index up to 7.5% in relative terms during the peak green period; and (4) that IWV varies so substantially that pixel and date-specific values need to be used for the atmospheric correction of AVHRR data. At present, subdaily gridded IWV data sets from atmospheric data reanalysis projects are the only candidate source for such purpose.

Bandpass-resampling effects on the retrieval of radiance and surface reflectance

Radiative transfer models are often employed to derive the surface reflectance for Earth-looking multispectral scanners or imaging spectrometers. For this purpose the calculated radiances have to be resampled with the spectral channel response functions of the instrument. Three methods of bandpass resampling the product terms of the radiative transfer equation are compared: the exact method and two commonly used approximations. Error budgets for the two approximate methods are given for typical multispectral and hyperspectral sensors. The error depends on the wavelength, bandwidth, atmospheric parameters, and atmospheric path length.

The interrelationship of atmospheric correction of reflectances and surface BRDF retrieval: a sensitivity study

This paper systematically studies the interrelationship between surface bidirectional reflectance distribution function (BRDF) retrieval and atmospheric correction. The study uses the atmospheric correction scheme of the Moderate Resolution Imaging Spectroradiometer (MODIS) and angular sampling expected for MODIS and the Multiangle Imaging SpectroRadiometer (MISR) for different land cover types and optical depths of aerosols. The results show the following two points. 1) Even for a nonturbid atmosphere, the assumption of a Lambertian surface in atmospheric correction causes relative errors in the retrieved surface reflectances that average from 2 to 7% in the red and near-infrared bands, with worst cases showing errors of up to about 15% for turbid conditions. Consequently, it is necessary for improved accuracy to consider surface anisotropy in atmospheric correction. 2) Surface BRDF retrieval and atmospheric correction can be coupled in a converging iteration loop that improves the quality of atmospheric correction and subsequent BRDF retrievals. For example, performing two steps of the iteration loop is already sufficient to obtain mean relative errors of less than 1% in the retrieved surface reflectances even for an atmospheric aerosol optical depth of 0.4. As BRDF retrieval accuracies improve, so do bihemispherical albedo retrieval accuracies, with mean relative errors being 1-5% when using a Lambertian assumption and less than 1% after two iteration steps.

An atmospheric correction procedure for the ATSR-2 visible and near-infrared land surface data

An atmospheric correction procedure for the solar reflecting channels of the Second Along Track Scanning Radiometer (ATSR-2) is described in which the aerosol optical thickness is retrieved from atmospheric simulations using the top-of-atmosphere (TOA) reflectances. The aerosol optical thickness is obtained when the ratio of the corresponding surface reflectances, in the off-nadir view to the nadir view, for two selected sensor channels, are equal. Directional reflectance models have been used to determine the validity of this approach and to determine suitable channel combinations. Simulations of the procedure for realistic surfaces indicate the retrieval of tau A 550 is better than 0.1 when the aerosol meteorology is known. The accuracy of the retrieval of surface reflectance is significantly affected by deviations from the expected aerosol meteorology. Factors affecting the accuracy of the correction procedure are described.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

Little research has focused on the use o f intaging spectrometry for change detection. In this paper, we apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atinospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiativetransfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), .soil, and shade. Temporal and spatial patterns in endineinber fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target. Atmospheric analysis showed a strongly negative linear relation between water vapor and elevation with significant seasonal variation in water vapor. Comparison of AVIRIS estimates of specific humidity to ground-based measures showed good correspondence for all three dates. Analysis of .surface properties showed that GV, NDVI, and liquid water varied in. response to green vegetation and were highly correlated. However, whereas the NDVI peaked between 0.7 and 0.85 in forests, liquid water continued to vary by as much as a factor of two. Seasonal patterns included senescence in herbaceous and nonconiferous vegetation, potential leaf growth in cortiferous forests, and a general increase in shadows. This resulted in seasonal declines in NDVI, GV, and liquid water for non forested vegetation and increases in NPV. Nonconiferous forests showed similar declines in liquid water rend GV and increases in shade and NPV, but they showed an. increase in NDVI. In coniferouns forests, liquid water and NDVI increased seasonally, matching an interpretation of continued growth, but GV decreased owing to increased .shade. The combination of retrieved surface reflectance, atmospheric modeling, and mapping of liquid water demonstrates the utility of imaging spectrometry for change detection. SMA with the use of reference endmembers is an c effective method for monitoring surficial changes. Temporal patterns in NDVI that contradict trends of GV and liquid water in nonconiferous forests raise additional questions about the NDVI. Liquid water may be more appropriate for analysis of high-leaf-area, shadowed forests because it overcomes the problem of saturation with NDVI.

Operational bi-angle approach to retrieve the Earth surface albedo from AVHRR data in the visible band

Abstract The inference of surface spectral reflectance using visible observations is complicated mainly because of scattering effects. In the present paper we attempt a solution to the problem of retrieval of surface reflectance from satellite radiance measurements based on a solution of the radiative transfer equation. We have developed an operational method which relies on multiple view angle observations or multiple solar zenith angle observations of the surface to accomplish part of this task in a routine manner. This approach may be used for ERS-2 ATSR visible bands because there will be two view angle observations for the same area at essentially the same time. This approach can also be used with NOAA satellite AVHRR data by assuming that the distribution of the aerosol does not vary too rapidly as a function of time. Usually it is better to select the AVHRR data from around noon and at dusk in the same day. This approach requires that the visibility of the area should be more than 5 km for multiple...

Retrieval of apparent surface reflectance from AVIRIS data: A comparison of empirical line, radiative transfer, and spectral mixture methods

Three methods for converting Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) radiance data to apparent surface reflectance were compared using data collected over the Lunar Crater Volcanic Field in Nevada and the Pavant Butte tuff cone in Utah. The methods examined were the empirical line method, radiative transfer modeling (using LOWTRAN 7), and spectral mixture analysis using reference endmembers. Of the three, the empirical line and spectral mixture methods both provided good results. The approach utilizing LOWTRAN 7 accentuates noise inherent in AVIRIS data and requires a very accurate estimate of atmospheric water.

Reflectance of antarctic surfaces from multispectral radiometers: The correction of atmospheric effects

Monitoring reflectance of polar icecaps has relevance in climate studies. In fact, climate changes produce variations in the morphology of ice and snow covers, which are detectable as surface reflectance change. Surface reflectance can be retrieved from remotely sensed data. However, absolute values independent of atmospheric turbidity and surface altitude can only be obtained after removing masking effects of the atmosphere. An atmospheric correction model, accounting for surface and sensor altitudes above sea level, is described and validated through data detected over Antarctic surfaces with a Barnes Modular Multispectral Radiometer having bands overlapping those of the Landsat Thematic Mapper. The model is also applied in a sensitivity analysis to investigate error induced in reflectance obtained from satellite data by indeterminacy in optical parameters of atmospheric constituents. Results show that indeterminacy in the atmospheric water vapor optical thickness is the main source of nonaccuracy in the retrieval of surface reflectance from data remotely sensed over Antarctic regions.

Surface reflectance retrieval from satellite and aircraft sensors: Results of sensor and algorithm comparisons during FIFE

Visible to shortwave infrared radiometric data collected by a number of remote sensing instruments on aircraft and satellite platforms were compared over common areas in the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site on August 4, 1989, to assess their radiometric consistency and the adequacy of atmospheric correction algorithms. The instruments in the study included the Landsat 5 thematic mapper (TM), the SPOT 1 high‐resolution visible (HRV) 1 sensor, the NS001 thematic mapper simulator, and the modular multispectral radiometers (MMRs). Atmospheric correction routines analyzed were an algorithm developed for FIFE, LOWTRAN 7, and 5S. A comparison between corresponding bands of the SPOT 1 HRV 1 and the Landsat 5 TM sensors indicated that the two instruments were radiometrically consistent to within about 5%. Retrieved surface reflectance factors using the FIFE algorithm over one site under clear atmospheric conditions indicated a capability to determine near‐nadir surface reflectance factors to within about 0.01 at a reflectance of 0.06 in the visible (0.4–0.7 μm) and about 0.30 in the near infrared (0.7–1.2 μm) for all but the NS001 sensor. All three atmospheric correction procedures produced absolute reflectances to within 0.005 in the visible and near infrared. In the shortwave infrared (1.2–2.5 μm) region the three algorithms differed in the retrieved surface reflectances primarily owing to differences in predicted gaseous absorption. Although uncertainties in the measured surface reflectance in the shortwave infrared precluded definitive results, the 5S code appeared to predict gaseous transmission marginally more accurately than LOWTRAN 7.

Aerosol optical depth retrievals over the Konza Prairie

The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 days in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.

Contrast reduction by the atmosphere and retrieval of nonuniform surface reflectance

A radiative transfer model is developed which gives the upward radiance at nadir for any 1-D Lambertian surface reflectance. This model is used to depict the atmospheric effect on the transmittance of contrast for any 1-D surface reflectance. Here by contrast we mean a general variation of the radiation field across the image. With the aid of this model an inversion algorithm is developed for retrieval of true surface reflectance from high resolution satellite data (e.g., Landsat). This inversion technique can be a useful tool for extraction of surface reflectance from satellite data in the case of a surface reflectance variable in one dimension only (e.g., seashore or near borders of big fields). A sensitivity study of the inversion procedure on the knowledge of atmospheric parameters and sensor calibration was performed. It is shown that this inversion technique is stable even in the presence of errors in the sensor calibration and the atmospheric parameters. The method was applied to Landsat data in two wavelengths. The results show reasonable dependence of the derived surface reflectance on the distance from the seashore.