ALBERT

Description: In order to study forests at the global scale, a detailed link budget for a lidar system onboard satellite is presented. It is based on an original approach coupling airborne lidar observations and an end-to-end simulator. The simulator is initialized by airborne lidar measurements performed over temperate and tropical forests on the French territory, representing a wide range of forests ecosystems. Considering two complementary wavelengths of 355 and 1064 nm, the end-to-end simulator computes the performance of spaceborne lidar systems for different orbits. The analysis is based on forest structural (tree top height, quadratic mean canopy height) and optical (forest optical thickness) parameters. Although an ultraviolet lidar appears to be a good candidate for airborne measurements, our results show that the limited energy is not favorable for spaceborne missions with such a wavelength. A near infrared wavelength at 1064 nm is preferable, requiring ~100 mJ laser emitted energy, which is in agreement with current and future spaceborne missions involving a lidar. We find that the signal-to-noise ratio at the ground level to extract both the structural and optical parameters of forests must be larger than 10. Hence, considering the presence of clouds and aerosols in the atmosphere and assuming a stationary forest, a good detection probability of 99% can be reached when 4 or 5 satellite revisits are considered for a lidar system onboard the ISS or ICESat, respectively. This concerns ~90% of forest covers observed from the lidar, which have an optical thickness less than 3.

Description: From an unprecedented experiment using airborne measurements performed over the rich forests of Réunion Island, this paper aims to present a methodology for the classification of diverse tropical forest biomes as retrieved from vertical profiles measured using a full-waveform LiDAR. This objective is met through the retrieval of both the canopy height and the Leaf Area Index (LAI), obtained as an integral of the foliage profile. The campaign involved sites ranging from coastal to rain forest, including tropical montane cloud forest, as found on the Bélouve plateau. The mean values of estimated LAI retrieved from the apparent foliage profile are between ~5 and 8 m2/m2, and the mean canopy height values are ~15 m for both tropical montane cloud and rain forests. Good agreement is found between LiDAR- and MODIS-derived LAI for moderate LAI (~5 m2/m2), but the LAI retrieved from LiDAR is larger than MODIS on thick rain forest sites (~8 against ~6 m2/m2 from MODIS). Regarding the characterization of tropical forest biomes, we show that the rain and montane tropical forests can be well distinguished from planted forests by the use of the parameters directly retrieved from LiDAR measurements.

Description: Amongst all the methodologies readily available to estimate forest canopy and aboveground carbon (AGC), in-situ plot surveys and airborne laser scanning systems appear to be powerful assets. However, they are limited to relatively local scales. In this work, we have developed a full-waveform UV lidar, named ULICE (Ultraviolet LIdar for Canopy Experiment), as an airborne demonstrator for future space missions, with an eventual aim to retrieve forest properties at the global scale. The advantage of using the UV wavelength for a demonstrator is its low multiple scattering in the canopy. Based on realistic airborne lidar data from the well-documented Fontainebleau forest site (south-east of Paris, France), which is representative of managed deciduous forests in temperate climate zones, we estimate the uncertainties in the retrieval of forest vertical structures and AGC. A complete uncertainty study using Monte Carlo approaches is performed for both the lidar-derived tree top height (TTH) and AGC. Our results show a maximum error of 1.2 m (16 tC ha‑1) for the TTH (AGC) assessment. Furthermore, the study of leaf effect on AGC estimate for mid-latitude deciduous forests highlights the possibility for using calibration obtained during only one season to retrieve the AGC during the other, by applying winter and summer airborne measurements.