Analysis of interannual changes in northern vegetation activityobserved in AVHRR data from 1981 to 1994

This paper reports on the analysis of Pathfinder AVHRR land (PAL) data set that spans the period July 1981 to September 1994. The time series of normalized difference vegetation index (NDVI) data for land areas north of 45° N assembled by correcting the PAL data with spectral methods confirms the northerly greening trend and extension of the photosynthetically active growing season. Analysis of the channel reflectance data indicates that the interannual changes in red and near-infrared reflectances are similar to seasonal changes in the spring time period when green leaf area increases and photosynthetic activity ramps up. Model calculations and theoretical analysis of the sensitivity of NDVI to background reflectance variations confirm the hypothesis that warming driven reductions in snow cover extent and earlier onset of greening are responsible for the observed changes in spectral reflectances over vegetated land areas     

Solar zenith angle effects on forest canopy hemisphericalreflectances calculated with a geometric-optical bidirectionalreflectance model

The bidirectional reflectance distribution function (BRDF) provided by the Li-Strahler geometric-optical forest canopy model has been integrated to provide spectral instantaneous hemispherical reflectances of sparsely vegetated surfaces. Further integration over the Sun's zenith angles can yield daily or longer interval hemispherical reflectances as well. A variety of simulated canopies were modeled with varying solar angles. In all cases, as the geometric-optical model introduced increased shadowing of the surface with increased solar zenith angle, the direct-beam hemispherical surface reflectance gradually decreased. The hemispherical reflectance values are direct beam calculations and do not directly include canopy multiple scattering and leaf specularity or consider the impact of diffuse irradiance. These limitations are acceptable for sparse canopies, in which 3D shadowing effects are large. However, radiative transfer calculations have shown that these phenomena must be incorporated before truly realistic modeling of hemispherical surface reflectances can be achieved for dense canopies     

Atmospheric correction against algorithm for NOAA-AVHRR products:theory and application

Investigation of the effect of atmospheric constituents on NOAA Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared data is presented. The general remote sensing equation, including scattering, absorption, and bidirectional reflectance effects for the AVHRR solar bands, is described. The magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirection reflectance is examined. Possible approaches for acquiring atmospheric information are discussed, and examples of atmospheric correction of surface reflectance and NDVI are given. Invariant effects (ozone absorption and molecular scattering) and variant effects (water vapor absorption and aerosol scattering) are shown to dominate the atmospheric effects in the AVHRR solar bands     

Determination of land and ocean reflective, radiative, andbiophysical properties using multiangle imaging

Knowledge of the directional and hemispherical reflectance properties of natural surfaces, such as soils and vegetation canopies, is essential for classification studies and canopy model inversion. The Multi-angle Imaging SpectroRadiometer (MISR), an instrument to be launched in 1998 onboard the EOS-AM1 platform, will make global observations of the Earth's surface at 1.1-km spatial resolution, with the objective of determining the atmospherically corrected reflectance properties of most of the land surface and the tropical ocean. The algorithms to retrieve surface directional reflectances, albedos, and selected biophysical parameters using MISR data are described. Since part of the MISR data analyses includes an aerosol retrieval, it is assumed that the optical properties of the atmosphere (i.e. aerosol characteristics) have been determined well enough to accurately model the radiative transfer process. The core surface retrieval algorithms are tested on simulated MISR data, computed using realistic surface reflectance and aerosol models, and the sensitivity of the retrieved directional and hemispherical reflectances to aerosol type and column amount is illustrated. Included is a summary list of the MISR surface products     

Improved semi-arid community type differentiation with the NOAAAVHRR via exploitation of the directional signal

Mapping semi-arid vegetation types at the community level is extremely difficult for optical sensors with large ground footprints such as the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). Attempts to use solar wavelength AVHRR data in community type differentiation have often resulted in unacceptable classification errors which are usually attributed to noise from topographic and soil background variations, inaccurate reflectance retrieval and poor registration. One source of variation which is rarely accounted for adequately is the directional signal resulting from the combined effects of the surface bidirectional reflectance distribution function (BRDF) and the variation of viewing and illumination geometry as a function of scan angle, season, latitude and orbital overpass time. In this study, a linear semiempirical kernel-driven BRDF model is used to examine the utility:of the directional signal in community and cover type differentiation over discontinuous but statistically homogeneous semi-arid canopies in Inner Mongolia Autonomous Region, China, and New Mexico, USA. This research shows that the directional signal resulting from the physical structure of the canopy-soil complex can be retrieved to provide information which is highly complementary to that obtained in the spectral domain     

The bidirectional polarized reflectance model of soil

Soil albedo is a critical parameter affecting the Earth's climate and environment. In remote sensing data, analysis of the soil bidirectional reflectance distribution function (BRDF) has to be known. Several models for bidirectional reflectance over soil have been developed. The Hapke bidirectional reflectance model has been widely used for soil modeling. Polarization of radiation reflected by soil carries important information of soil properties. The polarized light always goes with the bidirectional reflectance. Therefore, polarization reflectance of a ground target carries equivalent important information as bidirectional reflectance. Detecting multiangle polarization information of soil becomes a new method in quantitative remote sensing. In this paper, we analyzed the existence of polarization on the soil surface in a 2/spl pi/ space and compared the bidirectional reflectance with the bidirectional polarized reflectance. We then developed a new polarized BRDF model of soil as the bidirectional polarization distribution function (BPDF) model. The BPDF model helps to improve classification and quantitative analysis of soil.     

Atmospheric and angular effects on NDVI temporal profiles derivedfrom ADEOS-POLDER data over India

The variations of NDVI for crops, semi-evergreen forest, dry deciduous forest, and sand have been analyzed as a function of date of acquisition at 670 and 865 am using ADEOS-Polarization and Directionality of Earth Resources (POLDER) data acquired over India. After correcting the data for atmospheric effects, a semi-empirical bidirectional reflectance distribution function (BRDF) model has been fitted to the data to extract angularly normalized target reflectances. It is shown that atmospheric corrections and angular normalization are important in the quantitative analysis of NDVI and its temporal variations     

An algorithm using visible and 1.38-/spl mu/m channels to retrieve cirrus cloud reflectances from aircraft and satellite data

The Moderate Resolution Imaging Spectro-Radiometer (MODIS) on the Terra spacecraft has a channel near 1.38 /spl mu/m for remote sensing of high clouds from space. The implementation of this channel on MODIS was primarily based on previous analysis of hyperspectral imaging data collected with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We describe an algorithm to retrieve cirrus bidirectional reflectance using channels near 0.66 and 1.38 /spl mu/m. It is shown that the apparent reflectance of the 1.38-/spl mu/m channel is essentially the bidirectional reflectance of cirrus clouds attenuated by the absorption of water vapor above cirrus clouds. A practical algorithm based on the scatterplot of 1.38-/spl mu/m channel apparent reflectance versus 0.66-/spl mu/m channel apparent reflectance has been developed to scale the effect of water vapor absorption so that the true cirrus reflectance in the visible spectral region can be obtained. To illustrate the applicability of the present algorithm, results for cirrus reflectance retrievals from AVIRIS and MODIS data are shown. The derived cirrus reflectance in the spectral region of 0.4-1 /spl mu/m can be used to remove cirrus contamination in a satellite image obtained at a visible channel. An example of such an application is shown. The spatially averaged cirrus reflectances derived from MODIS data can be used to establish global cirrus climatology, as is demonstrated by a sample global cirrus reflectance image.     

Aerosol retrieval over land from AVHRR data-application foratmospheric correction

Correction of Advanced Very High Resolution Radiometer (AVHRR) imagery for the aerosol effect requires retrieval of the aerosol loading from the images. Two retrieval algorithms that were previously developed for Landsat are modified for the AVHRR. The methods determine the aerosol optical thickness over land surfaces from AVHRR band one data independently of ancillary information. The first method retrieves aerosols based on the atmospheric effect on the path radiance. This method requires the surface reflectance to be 0.02±0.01, which is found over forests in the red channel. Two techniques are used to screen an AVHRR scene for pixels that have this low reflectance. The qualifying requirements for these techniques are discussed, and the method is demonstrated to retrieve aerosol optical thicknesses to ~±0.1. The second method uses the change in contrast for several scenes to determine the change in the optical thickness between the scenes. A reference scene allows absolute determination. The method has an rms error of ~0.1     

The bidirectional effects of AVHRR measurements over boreal regions

The objectives of this paper are to analyze the bidirectional effects of satellite data over six land-cover types in northern regions, and to test a method for the routine correction of these effects. Analyses and corrections were carried out with both single-day and 10-day composite data obtained by the advanced very high resolution radiometer (AVHRR) from central Canada acquired in 1993/1994, in part, for the boreal ecosystem and atmosphere study (BOREAS). The model of Wu et al. [1995], developed from a separate data set collected at lower latitudes, was employed for correcting the effects. The analysis showed viewing angle dependence in AVHRR channels 1 and 2 from both single-day images and composites. Reflectances at extreme viewing angles are two to four times larger than those observed near nadir. On average, the effects introduce a variation of 30% relative to mean reflectances. Although the effects decrease in the normalized difference vegetation index (NDVI), they are nevertheless significant before the correction. Using the model of Wu et al. [1995], the BRDF-related variability is reduced by about 68% in channel 1 and 71% in channel 2. After a simple adjustment of the model coefficients, a further reduction of 4% (channel 1) and 6% (channel 2) of the BRDF-related variability was achieved for the 10⁶ km² BOREAS region. The effectiveness of the correction with both original and refined model of Wu et al. was found to be weakly dependent on land-cover type. Corrections for coniferous, mixed wood, and cropland are better than other land-cover types (rangelands/pasture, deciduous, and transitional forests) with residual BRDF errors around 0.05 in both channels. Overall, the model (albeit simple) performs reasonably well throughout the growing season. To apply the model, only general knowledge of land-cover type is required, namely forest, cropland, grassland, and bare ground     

Detection of dust over deserts using satellite data in the solarwavelengths

Dust is a dominant feature in satellite images and is suspected to extract large radiative forcing of climate. While remote sensing of dust over the dark oceans is feasible, adequate techniques for remote sensing over the land still have to be developed. Similar to remote sensing of aerosol over vegetated regions, the authors use a combination of visible and mid-IR solar channels to detect dust over the desert. Analysis of Landsat TM images over Senegal taken in 1987 show that the surface reflectance at 0.64 μm is between 0.54±0.05 of the reflectance at 2.1 μm, and reflectance at 0.47 μm is 0.26±0.03 of that at 2.1 μm, surprisingly similar to relationships in non-desert sites. They also found that dust have only a small effect on the surface+atmosphere reflectance at 2.1 μm over the desert. Therefore, in the presence of dust, they use the Landsat TM data at 2.1 μm channel to predict the surface reflectance at 0.64 and 0.47 μm. The difference between the satellite-measured reflectances of surface+atmosphere and the predicted surface reflectances is used to derive the dust-optical thickness τ at 0.64 and 0.47 μm. Results show that τ can be derived within Δτ=±0.5 for the range of 0<τ<2.5, thus enabling detection of dust sources and the estimation of three to five levels of dust opacity over the desert. The method is very sensitive to the correct knowledge of the dust absorption and is equally sensitive to dust in the entire atmospheric column. It is best applied in the red part of the spectrum (around 0.64 μm), where dust was found to be weak-absorbing or nonabsorbing. They plan to use this method as part of the dust monitoring from the Earth-observing system MODIS instrument     

Normalization and comparison of surface temperatures across a range of scales

The Southern Great Plains 1999 (SGP99) Experiment, conducted in Oklahoma, July 8-21, 1999, provided an opportunity to observe spatial and temporal variations in surface temperature. During the experiment, aircraft (Passive/Active L/S-band airborne sensor) and satellite [Advanced Very High Resolution Radiometer (AVHRR) and TIROS Operational Vertical Sounder (TOVS)] sensors collected surface temperature that was compared to in situ observations over the same time period to determine the accuracy and consistency of surface temperature measurements at different spatial resolutions using remotely sensed data. In addition, in situ surface temperature was observed in a 400/spl times/400 m field at various spatial grid spacing: 50 m, 10 m, and 1 m in order to quantify the variability of the spatially distributed behavior of surface temperature during a drydown period. Average differences between the in situ surface temperature observations and the aircraft and satellite sensors utilized during this study ranged from 0.7/spl deg/C (AVHRR High Resolution Picture Transmission) to more than 20/spl deg/C (AVHRR Global Area Coverage (GAC), TOVS). We have shown that the temporal adjustments of the remotely sensed surface temperatures (from aircraft and satellite sensors) shows a better comparison to in situ ground data. A ratio was set up using information derived from a mosaic land surface model to temporally locate the various estimates of surface temperature. The corrected surface temperature comparisons decreased the average differences (with in situ) to as much as 78% [AVHRR (GAC)] and as little as 6% (TOVS). The average difference between remotely sensed and in situ observations was around 48%.     

Effect of orbital drift and sensor changes on the time series of AVHRR vegetation index data

This paper assesses the effect of changes in solar zenith angle (SZA) and sensor changes on reflectances in channel 1, channel 2, and normalized difference vegetation index (NDVI) from the advanced very high resolution radiometer (AVHRR) Pathfinder land data set for the period July 1981 through September 1994. First, the effect of changes in SZA on channel reflectances and NDVI is derived from equations of radiative transfer in vegetation media. Starting from first principles, it is rigorously shown that the NDVI of a vegetated surface is a function of the maximum positive eigenvalue of the radiative transfer equation within the framework of the theory used and its assumptions. A sensitivity analysis of this relation indicates that NDVI is minimally sensitive to SZA changes, and this sensitivity decreases as leaf area increases. Second, statistical methods are used to analyze the relationship between SZA and channel reflectances or NDVI. It is shown that the use of ordinary least squares can generate spurious regressions because of the nonstationary property of time series. To avoid such a confusion, the authors use the notion of cointegration to analyze the relation between SZA and AVHRR data. Results are consistent with the conclusion of theoretical analysis from equations of radiative transfer. NDVI is not related to SZA in a statistically significant manner except for biomes with relatively low leaf area. From the theoretical and empirical analysis, they conclude that the NDVI data generated from the AVHRR Pathfinder land data set are not contaminated by trends introduced from changes in solar zenith angle due to orbital decay and changes in satellites (NOAA-7, 9, 11). As such, the NDVI data can be used to analyze interannual variability of global vegetation activity.     

Impact of variable atmospheric water vapor content on AVHRR datacorrections 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     

Algorithm for global leaf area index retrieval using satellite imagery

Leaf area index (LAI) is one of the most important Earth surface parameters in modeling ecosystems and their interaction with climate. Based on a geometrical optical model (Four-Scale) and LAI algorithms previously derived for Canada-wide applications, this paper presents a new algorithm for the global retrieval of LAI where the bidirectional reflectance distribution function (BRDF) is considered explicitly in the algorithm and hence removing the need of doing BRDF corrections and normalizations to the input images. The core problem of integrating BRDF into the LAI algorithm is that nonlinear BRDF kernels that are used to relate spectral reflectances to LAI are also LAI dependent, and no analytical solution is found to derive directly LAI from reflectance data. This problem is solved through developing a simple iteration procedure. The relationships between LAI and reflectances of various spectral bands (red, near infrared, and shortwave infrared) are simulated with Four-Scale with a multiple scattering scheme. Based on the model simulations, the key coefficients in the BRDF kernels are fitted with Chebyshev polynomials of the second kind. Spectral indices - the simple ratio and the reduced simple ratio - are used to effectively combine the spectral bands for LAI retrieval. Example regional and global LAI maps are produced. Accuracy assessment on a Canada-wide LAI map is made in comparison with a previously validated 1998 LAI map and ground measurements made in seven Landsat scenes.     

A method for accurate geometric correction of NOAA AVHRR HRPT data

A method for the geometric correction of NOAA Advanced Very High Resolution Radiometer (AVHRR) high-resolution picture transmission (HRPT) data is presented. After precise determination of nominal attitude angles for each time instant, geometric correction is done for ground control points (GCPs), and residual errors are interpreted as attitude angle variation effects and in this way corrected. All attitude angle deviations (in pitch, roll, and yaw) are simultaneously corrected by applying to two reference vectors (the vector normal to the scanning plane and the vector that defines the instantaneous viewing direction of the first pixel of each line) a three-axis rotation. A separate program performs the geometric correction, applying the orbital model to each point of the desired output geographical area. An application of this method is presented, in which AVHRR data are registered over a 1:25000 topographic map with subpixel accuracy, allowing the use of AVHRR data in a nearly local scale in combination with other high-resolution data, such as Landsat TM or SPOT     

Vegetation isoline equations for an atmosphere-canopy-soil system

The relationship between the reflectances at two different wavelengths over a three-layer system comprising atmosphere, canopy, and soil layers is derived. This work is an extension of the isoline equation previously derived in a red and near-infrared (NIR) reflectance space for a canopy-soil system. As a result of retaining only the zeroth and first-order interaction terms between the layers, the relationship has a linear form in which the slope and offset are functions of the optical properties of each layer. Numerical examples of isolines based on the derived expressions are obtained under various conditions and are shown to demonstrate some of the known behaviors of isolines. Since the derived expression relates a pair of reflectances, it is expected to be useful for the analysis of satellite data products involving algebraic manipulations of spectral reflectances, such as spectral vegetation indexes.     

目标表面BRDF统计建模中的遗传模拟退火算法

结合基本遗传算法与模拟退火算法,构造出了新的具有全局搜索优化特性的遗传模拟退火算法.根据卫星表面BRDF实验数据和统计模型,引用遗传模拟退火算法,获得样片BRDF模型参数的优化估计,从而获得了三维空间的BRDF分布,其优化参数后的模型在另一部分数据上也得到了很好的吻合验证.     

Prediction and measurement of soil bidirectional reflectance

A model for soil bidirectional reflectance distribution functions in visible and reflective infrared wavelengths is introduced and compared to data acquired in the field. The model is based on the representation of soil surfaces by a collection of opaque spheres sitting on a Lambertian horizontal surface. The model is not sensitive to increases in the sphere area index beyond a value of 0.4. For comparison, soil reflectance factor data were acquired on a tilled field from many view directions and for a range of solar directions. The observed reflectance factor distributions were consistent with those predicted by the function; maximum reflectance occurred in the antisolar direction and reflectance decreased with increasing phase angle. Increasing the surface roughness by different tillage methods did not substantially alter the directional anisotropy of the soil reflectance factors. The model was fit to the data by a nonlinear least-squares procedure     

Remote sensing of water vapor in the near IR from EOS/MODIS

The LOWTRAN-7 code was used to simulate remote sensing of water vapor over 20 different surface covers. The simulation was used to optimize the water vapor channel selection and to test the accuracy of the remote sensing method. The channel selection minimizes the uncertainty in the derived water vapor due to variations in the spectral dependence of the surface reflectance. The selection also minimizes the sensitivity of the selected channels to possible drift in the channel position. The use of additional MODIS channels reduces the errors due to the effect of haze, subpixel clouds and uncertainties in the temperature profile. Remote sensing of the variation of water vapor from day to day will be more accurate, because the surface reflectances vary slowly with time. The method was applied to Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data