[1] Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum forest height in three ecosystems; tropical broadleaf forests in Brazil, temperate broadleaf forests in Tennessee, and temperate needleleaf forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured forest canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r 2 = 73%, RMSE = 58.3 Mgha À1 ).

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. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

The Ice, Cloud and land Elevation Satellite (ICESat) mission determines land surface vertical structure within laser footprints due to topographic relief and vegetation using received waveforms recorded by the Geoscience Laser Altimeter System (GLAS). In low‐relief areas with tree cover the waveforms and derived elevation products provide useful biophysical parameters, including maximum canopy height, crown depth, the outer‐canopy ruggedness, and a measure of canopy cover. For areas where within‐footprint topographic relief is large compared to vegetation height, interpretation of the waveforms is complex. The contribution of canopy and ground to received waveforms is illustrated by comparing them with co‐located waveforms computed using an instrument model applied to high resolution Digital Elevation Models (DEMs). The model includes representations of the transmit pulse's spatial and temporal distributions, and the receiver field‐of‐view sensitivity and temporal smoothing. This provides a means to validate GLAS waveforms, elevation products, and footprint geolocation.

[1] The primary goal of the Ice, Cloud and land Elevation Satellite (ICESat) mission is ice sheet elevation change detection. Confirmation that ICESat is achieving its stated scientific requirement of detecting spatially-averaged changes as small as 1.5 cm/year requires continual assessment of ICESat-derived elevations throughout the mission. We use a GPS-derived digital elevation model (DEM) of the salar de Uyuni, Bolivia for this purpose. Using all twelve ICESat passes over the salar survey area acquired to date, we show that the accuracy of ICESat-derived elevations is impacted by environmental effects (e.g., forward scattering and surface reflectance) and instrument effects (e.g., pointing biases, detector saturation, and variations in transmitted laser energy). We estimate that under optimal conditions at the salar de Uyuni, ICESatderived elevations have an absolute accuracy of <2 cm and precision of <3 cm. Citation: