The design of a Space-borne multispectral canopy LiDAR to estimate global carbon stock and gross primary productivity

Understanding the dynamics of the global carbon cycle is one of the most challenging issues for the scientific community. The ability to measure the magnitude of terrestrial carbon sinks as well as monitoring the short and long term changes is vital for environmental decision making. Forests form a significant part of the terrestrial biosystem and understanding the global carbon cycle, Above Ground Biomass (AGB) and Gross Primary Productivity (GPP) are critical parameters. Current estimates of AGB and GPP are not adequate to support models of the global carbon cycle and more accurate estimates would improve predictions of the future and estimates of the likely behaviour of these sinks. Various vegetation indices have been proposed for the characterisation of forests including canopy height, canopy area, Normalised Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI). Both NDVI and PRI are obtained from a measure of reflectivity at specific wavelengths and have been estimated from passive measurements. The use of multi-spectral LiDAR to measure NDVI and PRI and their vertical distribution within the forest represents a significant improvement over current techniques. This paper describes an approach to the design of an advanced Multi-Spectral Canopy LiDAR, using four wavelengths for measuring the vertical profile of the canopy simultaneously. It is proposed that the instrument be placed on a satellite orbiting the Earth on a sun synchronous polar orbit to provide samples on a rectangular grid at an approximate separation of 1km with a suitable revisit frequency. The systems engineering concept design will be presented

The utility of MODIS-sPRI for investigating the photosynthetic light-use efficiency in a Mediterranean deciduous forest

The present study investigated the utility of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived sPRI (scaled photochemical reflectance index) and its relationship to photosynthetic light-use efficiency (LUE) calculated from eddy covariance tower data. The analysis was performed over two consecutive years (2003–2004) in a Mediterranean Quercus cerris L. forest site in Italy. Temperature and rainfall conditions differed markedly over the study period, with 2003 being a notable drought year and 2004 a non-drought year. MODIS ocean bands 11 (centred at 531 nm) and 12 (centred at 551 nm) were used for calculating sPRI. LUE exhibited substantial variability within 2003 and 2004, and a moderate relationship between MODIS-sPRI and LUE was observed during the wet year, and for backscattering scenes. This demonstrated the capacity of sPRI to detect xanthophyll cycle activation by vegetation during high light conditions. However, our results show that sPRI should be used with care, particularly under severe water stress conditions, when an increased influence of confounding factors, such canopy structure, illumination, and viewing angles, is observed

Species-Level Classification of Peatland Vegetation Using Ultra-High-Resolution UAV Imagery

Peatland restoration projects are being employed worldwide as a form of climate change mitigation due to their potential for long-term carbon sequestration. Monitoring these environments (e.g., cover of keystone species) is therefore essential to evaluate success. However, existing studies have rarely examined peatland vegetation at fine scales due to its strong spatial heterogeneity and seasonal canopy development. The present study collected centimetre-scale multispectral Uncrewed Aerial Vehicle (UAV) imagery with a Parrot Sequoia camera (2.8 cm resolution; Parrot Drones SAS, Paris, France) in a temperate peatland over a complete growing season. Supervised classification algorithms were used to map the vegetation at the single-species level, and the Maximum Likelihood classifier was found to perform best at the site level (69% overall accuracy). The classification accuracy increased with the spatial resolution of the input data, and a large reduction in accuracy was observed when employing imagery of >11 cm resolution. Finally, the most accurate classifications were produced using imagery collected during the peak (July–August) or early growing season (start of May). These findings suggest that despite the strong heterogeneity of peatlands, these environments can be mapped at the species level using UAVs. Such an approach would benefit studies estimating peatland carbon emissions or using the cover of keystone species to evaluate restoration projects

Measurement of Diurnal Variation in Needle PRI and Shoot Photosynthesis in a Boreal Forest

This article has an erratum: Remote Sens. 2018. 10, 2030. DOI 10.3390/rs10122030. WOS: 000455637600172Peer reviewe

Boundary layers and emitted excitations in nonlinear Schrodinger superflow past a disk

The stability and dynamics of nonlinear Schrodinger superflows past a two-dimensional disk are investigated using a specially adapted pseudo-spectral method based on mapped Chebychev polynomials. This efficient numerical method allows the imposition of both Dirichlet and Neumann boundary conditions at the disk border. Small coherence length boundary-layer approximations to stationary solutions are obtained analytically. Newton branch-following is used to compute the complete bifurcation diagram of stationary solutions. The dependence of the critical Mach number on the coherence length is characterized. Above the critical Mach number, at coherence length larger than fifteen times the diameter of the disk, rarefaction pulses are dynamically nucleated, replacing the vortices that are nucleated at small coherence length

Illumination Geometry and Flying Height Influence Surface Reflectance and NDVI Derived from Multispectral UAS Imagery

Small unmanned aerial systems (UAS) have allowed the mapping of vegetation at very high spatial resolution, but a lack of standardisation has led to uncertainties regarding data quality. For reflectance measurements and vegetation indices (Vis) to be comparable between sites and over time, careful flight planning and robust radiometric calibration procedures are required. Two sources of uncertainty that have received little attention until recently are illumination geometry and the effect of flying height. This study developed methods to quantify and visualise these effects in imagery from the Parrot Sequoia, a UAV-mounted multispectral sensor. Change in illumination geometry over one day (14 May 2018) had visible effects on both individual images and orthomosaics. Average near-infrared (NIR) reflectance and NDVI in regions of interest were slightly lower around solar noon, and the contrast between shadowed and well-illuminated areas increased over the day in all multispectral bands. Per-pixel differences in NDVI maps were spatially variable, and much larger than average differences in some areas. Results relating to flying height were inconclusive, though small increases in NIR reflectance with height were observed over a black sailcloth tarp. These results underline the need to consider illumination geometry when carrying out UAS vegetation survey