Atmospheric aerosol measurements from the ATSR-SLSTR series of dual-view satellite instruments 1995-2022.

A data record, spanning 24 years, is presented of global atmospheric total aerosol optical depth and also the aerosol optical depth due to fine-mode constituents, typically of anthropogenic origin. Original measurements of reflectance were provided at approximately 1-km resolution by a series of dual-view satellite instruments: the Along-Track Scanning Radiometer 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR), and Sea and Land Surface Temperature Radiometers (SLSTRs). These were processed to retrieve aerosol properties at 10-km resolution and then collated over daily and monthly timescales on a 1° × 1° latitude-longitude grid.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods.

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables.

Amazon forests maintain consistent canopy structure and greenness during the dry season.

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data. We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors.

Computationally efficient method for retrieving aerosol optical depth from ATSR-2 and AATSR data.

We present a robust and computationally efficient method for retrieving aerosol optical depth (AOD) from top-of-atmosphere ATSR-2 (Along-Track Scanning Radiometer) and AATSR (Advanced ATSR) reflectance data that is formulated to allow retrieval of the AOD from the 11 year archive of (A)ATSR data on the global scale. The approach uses a physical model of light scattering that requires no a priori information on the land surface. Computational efficiency is achieved by using precalculated lookup tables (LUTs) for the numerical inversion of a radiative-transfer model of the atmosphere.