Mapping spatially-temporally continuous shortwave albedo for global land surface from MODIS data

Abstract

Land-surface albedo plays a critical role in the Earth's radiant energy budget studies. Satellite remote sensing is an effective approach to acquire regional and global albedo observations. However, owing to cloud coverage, seasonal snow and sensor malfunctions, spatially-temporally continuous albedo datasets are often inaccessible. GLASS preliminary albedo datasets (GLASS02A2<i>x</i>, <i>x</i> = 1, 2, 3 and 4) are newly developed global daily land-surface albedo products. Like other products, GLASS02A2<i>x</i> albedo surfers from large areas of missing data. Beside this, sharp fluctuations exist in GLASS02A2<i>x</i> time series due to data noise and algorithm uncertainties. In this study, a statistics-based temporal filterer (STF) is proposed to fill the data gaps and smooth the fluctuations in GLASS02A2<i>x</i> albedo time series. The result of STF algorithm is the GLASS final albedo product (GLASS02A06). Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODIS product, the final GLASS albedo product is much more competent in capturing the surface albedo variations. Although the STF algorithm is designed for GLASS albedo product, it is able to incorporate other albedo products. The STF method may also be applied to other parameters, such as the LAI and soil moisture

A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies

“…The albedo product from MODIS data is based on two direct albedo estimation algorithms from surface reflectance (AB1), TOA radiance (AB2, Qu et al 2013), and the Statistics-based Temporal Filtering (STF) fusion algorithm that integrates these two intermediate albedo products (Liu et al 2012).…”

Consistent estimation of multiple parameters from MODIS top of atmosphere reflectance data using a coupled soil-canopy-atmosphere radiative transfer model

“…The GLASS surface albedo product is based on two direct albedo estimation algorithms from MODIS surface reflectance and TOA reflectance (Qu et al, 2014). A temporal filter (STF) method was designed to integrate these two intermediate albedo products Liu et al, 2012). The GLASS surface albedo product has the same spatial and temporal resolution as the GLASS LAI product.…”

The Global Land Surface Satellite (GLASS) Remote Sensing Data Processing System and Products

“…The GLASS final albedo product in eight-day steps is obtained by merging the results obtained from AB1 and AB2 in a 16-day time window after 2000 or in a 32-day time window before 2000 through a Statistics-Based Temporal Filtering (STF) algorithm [30]. The STF detects and eliminates the occasional abnormal values in the intermediate products, and it fills missing values through temporal filtering supported by a prior database.…”