Application of angular models to AVHRR data for determination of the clear‐sky planetary albedo over land surfaces

Self Cite

144

Abstract. A set of algorithms is combined for a simple derivation of land surface albedo from measurements of reflected visible and near-infrared radiation made by the advanced very high resolution radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites. The system consists of a narrowband-to-broadband conversion and bidirectional correction at the top of the atmosphere and an atmospheric correction. We demonstrate the results with 1 month worth of data from the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) global vegetation index (GVI) weekly data set and the NOAA/NASA Pathfinder Atmosphere (PATMOS) project daily data. Error analysis of the methodology indicates that the surface albedo can be retrieved with 10-15% relative accuracy. Monthly albedo maps derived from September 1989 GVI and PATMOS data agree well except for small discrepancies attributed mainly to different preprocessing and residual atmospheric effects. A 5-year mean September map derived from the GVI multiannual time series is consistent with that derived from low-resolution Earth Radiation Budget Experiment data as well as with a September map compiled from ground observations and used in many numerical weather and climate models. Instantaneous GVI-derived albedos were found to be consistent with surface albedo measurements over various surface types. The discrepancies found can be attributed to differences in areal coverage and representativeness of the satellite and ground data. The present pilot study is a prototype for a routine real-time production of high-resolution global surface albedo maps from NOAA AVHRR Global Area Coverage (GAC) data.

Section: Measurementssupporting

confidence: 62%

Mapping global land surface albedo from NOAA AVHRR

Csiszar¹,

Gutman²

1999

Self Cite

144

“…Albedo is important because even small changes in its magnitude can lead to variations in radiative forcing, to which climate is extremely sensitive [ Ingram et al , 1989; Houghton et al , 2001; Dirmeyer and Shukla , 1994]. The spatial complexity and temporal variations of surface properties mean that practical albedo estimates over large area are usually derived from satellite observations [ Strugnell et al , 2001; Cihlar et al , 2002; Gutman et al , 1989]. Most land surfaces reflect incident radiation anisotropically.…”

Section: Introductionmentioning

confidence: 99%

Surface bidirectional reflectance and albedo properties derived using a land cover–based approach with Moderate Resolution Imaging Spectroradiometer observations

Luo¹

2005

[1] Surface bidirectional reflectance distribution function (BRDF) and albedo maps are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) multiday surface reflectance composites with a 500-m spatial resolution (MODIS product MOD09A1/MYD09A1). The proposed method dubbed land cover-based fitting employs the processing of clear-sky reflectance data for similar land cover types and takes into account the magnitude of normalized difference vegetation index (NDVI). The BRDF is derived through the fitting of pixel data sorted into small bins according to the values of angular variables and NDVI. Robust statistical processing is applied to reduce the influence of noise and outliers. This method increases the success rate of the fitting process and enables more accurate monitoring of surface temporal changes during periods of rapid spring vegetation green up and autumn leaf fall, as well as changes due to agricultural practices and snow cover variations. The approach is specifically applied over the Atmospheric Radiation Measurement Program Southern Great Plains area. Results are compared to alternative BRDF/albedo products, such as the MOD43 albedo and Multiangle Imaging Spectroradiometer surface products that are derived through a pixel-based fitting process. A good agreement was generally found between different data sets. For example, the average biases in the visible and near-infrared bands are usually less than 0.01 and 0.02, respectively, and correlation coefficients are typically larger than 0.80. An analysis of these differences identifies some unique advantages of the proposed method, such as the ability to capture rapidly changing surface properties and an increased performance in the case of reduced number of clear-sky observations because of frequent cloudy conditions. Results suggest that the developed land cover-based methodology is valuable for the purpose of surface BRDF and albedo mapping using MODIS observations. Citation: Luo, Y., A. P. Trishchenko, R. Latifovic, and Z. Li (2005), Surface bidirectional reflectance and albedo properties derived using a land cover -based approach with Moderate Resolution Imaging Spectroradiometer observations,

“…A fourstep hybrid cloud-screening technique is used here that employs different algorithms to cope with different cloud conditions. The first step removes overcast pixels that do not meet one or more of the following criteria [Gutman et al, 1987;Gutman, 1991]:…”

Section: Cloud Screeningmentioning

confidence: 86%

“…Since this study is concerned with clear-sky conditions only, overcast and cloud-contaminated pixels were screened out. Many algorithms have been proposed for detecting and classifying clouds using remotely sensed data [Coakley and Bretherton, 1982;Arking and Childs, 1985;Saunders, 1986;Gutman et al, 1987;Saunders and Kriebel, 1988]. A fourstep hybrid cloud-screening technique is used here that employs different algorithms to cope with different cloud conditions.…”

Section: Cloud Screeningmentioning

confidence: 99%

Effects of land cover type and greenness on advanced very high resolution radiometer bidirectional reflectances: Analysis and removal

Wu¹,

Li²,

Cihlar³

1995

117

The objectives of the study are (1) to examine the effects of land cover type, green biomass, and solar zenith angle (SZA) on the bidirectional reflectance distributions (BRDs) of the visible and near‐infrared advanced very high resolution radiometer (AVHRR) data from NOAA 11 over terrestrial surfaces; and (2) to correct for these effects by developing BRD functions (BRDF). Four land cover types are examined: barren, grassland, forest, and cropland. The data used consist of 1‐km daily AVHRR measurements for three growing seasons collected over 19 homogeneous land sites (20×20 km2 for each site) in the conterminous United States and parts of Canada. BRD is found to be strongly land cover dependent. For the same cover type, BRD is altered significantly by the green biomass present (represented by the normalized difference vegetation index (NDVI)). The effects of SZA on BRDs are also observed over all surface types under investigation. Semiempirical BRDFs were developed to account for these effects that are the functions of the SZA, satellite viewing zenith angle, relative azimuth angle, and NDVI. Good agreements were found between the observed and the modeled bidirectional dependencies for wide ranges of NDVI and SZA. A single BRDF appears to be sufficient for bidirectional correction of the clear‐sky AVHRR measurements made over a specific land cover type throughout a season. Finally, the developed BRDFs were used to normalize AVHRR reflectance data to a common geometry and to infer the hemispherical albedos for monitoring the seasonal variations of land surfaces.