White paper – On the use of LiDAR data at AmeriFlux sites

Our aim is to inform the AmeriFlux community on existing and upcoming LiDAR technologies (atmospheric Doppler or Raman LiDAR often deployed at flux sites are not considered here), how it is currently used at flux sites, and how we believe it could, in the future, further contribute to the AmeriFlux vision. Heterogeneity in vegetation and ground properties at various spatial scales is omnipresent at flux sites, and 3D mapping of canopy, understory, and ground surface can help move the science forward

Vegetation height products between 60° S and 60° N from ICESat GLAS data.

We present new coarse resolution (0.5� ×0.5�)vegetation height and vegetation-cover fraction data sets between 60� S and 60� N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70m in 0.5m intervals for each 0.5�×0.5�. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r =0.33 to r =0.78, decreases the root-mean-square error by a factor 3 to about 6m (RMSE) or 4.5m (68% error distribution) and decreases the bias from 5.7m to −1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5–6m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r =0.67); the GLAS treecover fraction is compared with the MODIS tree-cover fraction (r =0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface

Identifying Conifer Tree vs. Deciduous Shrub and Tree Regeneration Trajectories in a Space-for-Time Boreal Peatland Fire Chronosequence Using Multispectral Lidar

Wildland fires and anthropogenic disturbances can cause changes in vegetation species composition and structure in boreal peatlands. These could potentially alter regeneration trajectories following severe fire or through cumulative impacts of climate-mediated drying, fire, and/or anthropogenic disturbance. We used lidar-derived point cloud metrics, and site-specific locational attributes to assess trajectories of post-disturbance vegetation regeneration in boreal peatlands south of Fort McMurray, Alberta, Canada using a space-for-time-chronosequence. The objectives were to (a) develop methods to identify conifer trees vs. deciduous shrubs and trees using multi-spectral lidar data, (b) quantify the proportional coverage of shrubs and trees to determine environmental conditions driving shrub regeneration, and (c) determine the spatial variations in shrub and tree heights as an indicator of cumulative growth since the fire. The results show that the use of lidar-derived structural metrics predicted areas of deciduous shrub establishment (92% accuracy) and classification of deciduous and conifer trees (71% accuracy). Burned bogs and fens were more prone to shrub regeneration up to and including 38 years after the fire. The transition from deciduous to conifer trees occurred approximately 30 years post-fire. These results improve the understanding of environmental conditions that are sensitive to disturbance and impacts of disturbance on northern peatlands within a changing climate

The positive net radiative greenhouse gas forcing of increasing methane emissions from a thawing boreal forest-wetland landscape

At the southern margin of permafrost in North America, climate change causes widespread permafrost thaw. In boreal lowlands, thawing forested permafrost peat plateaus (‘forest’) lead to expansion of permafrost‐free wetlands (‘wetland’). Expanding wetland area with saturated and warmer organic soils is expected to increase landscape methane (CH4) emissions. Here, we quantify the thaw‐induced increase in CH4 emissions for a boreal forest‐wetland landscape in the southern Taiga Plains, Canada, and evaluate its impact on net radiative forcing relative to potential long‐term net carbon dioxide (CO2) exchange. Using nested wetland and landscape eddy covariance net CH4 flux measurements in combination with flux footprint modeling, we find that landscape CH4 emissions increase with increasing wetland‐to‐forest ratio. Landscape CH4 emissions are most sensitive to this ratio during peak emission periods, when wetland soils are up to 10 °C warmer than forest soils. The cumulative growing season (May–October) wetland CH4 emission of ~13 g CH4 m−2 is the dominating contribution to the landscape CH4 emission of ~7 g CH4 m−2. In contrast, forest contributions to landscape CH4 emissions appear to be negligible. The rapid wetland expansion of 0.26 ± 0.05% yr−1 in this region causes an estimated growing season increase of 0.034 ± 0.007 g CH4 m−2 yr−1 in landscape CH4 emissions. A long‐term net CO2 uptake of >200 g CO2 m−2 yr−1 is required to offset the positive radiative forcing of increasing CH4 emissions until the end of the 21st century as indicated by an atmospheric CH4 and CO2 concentration model. However, long‐term apparent carbon accumulation rates in similar boreal forest‐wetland landscapes and eddy covariance landscape net CO2 flux measurements suggest a long‐term net CO2 uptake between 49 and 157 g CO2 m−2 yr−1. Thus, thaw‐induced CH4 emission increases likely exert a positive net radiative greenhouse gas forcing through the 21st century

Monitoring boreal forest biomass and carbon storage change by integrating airborne laser scanning, biometry and eddy covariance data

AbstractThis study presents a comparison and integration of three methods commonly used to estimate the amount of forest ecosystem carbon (C) available for storage. In particular, we examine the representation of living above- and below-ground biomass change (net accumulation) using plot-level biometry and repeat airborne laser scanning (ALS) of three dimensional forest plot structure. These are compared with cumulative net CO2 fluxes (net ecosystem production, NEP) from eddy covariance (EC) over a six-year period within a jack pine chronosequence of four stands (~94, 30, 14 and 3years since establishment from 2005) located in central Saskatchewan, Canada. Combining the results of the two methods yield valuable observations on the partitioning of C within ecosystems. Subtracting total living biomass C accumulation from NEP results in a residual that represents change in soil and litter C storage. When plotted against time for the stands investigated, the curve produced is analogous to the soil C dynamics described in Covington (1981). Here, ALS biomass accumulation exceeds EC-based NEP measured in young stands, with the residual declining with age as stands regenerate and litter decomposition stabilizes. During the 50–70year age-period, NEP and live biomass accumulation come into balance, with the soil and litter pools of stands 70–100years post-disturbance becoming a net store of C. Biomass accumulation was greater in 2008–2011 compared to 2005–2008, with the smallest increase in the 94-year-old “old jack pine” stand and greatest in the 14-year-old “harvested jack pine 1994” stand, with values of 1.4 (±3.2) tCha−1 and 12.0 (±1.6) tCha−1, respectively. The efficiency with which CO2 was stored in accumulated biomass was lowest in the youngest and oldest stands, but peaked during rapid regeneration following harvest (14-year-old stand). The analysis highlights that the primary source of uncertainty in the data integration workflow is in the calculation of biomass expansion factors, and this aspect of the workflow needs to be implemented with caution to avoid large error propagations. We suggest that the adoption of integrated ALS, in situ and atmospheric flux monitoring frameworks is needed to improve spatio-temporal partitioning of C balance components at sub-decadal scale within rapidly changing forest ecosystems and for use in national carbon accounting programs

Quantifying land use effects on forested riparian buffer vegetation structure using LiDAR data

Open access article. Creative Commons Attribution 3.0 Unported License (CC BY 3.0) appliesQuantifying variability of forested riparian buffer (FRB) vegetation structure with variation in adjacent land use supports an understanding of how anthropogenic disturbance influences the ability of riparian systems to perform ecosystem services. However, quantifying FRB structure over large regions is a challenge and requires efficient data collection and processing methods that integrate conventional in situ vegetation sampling with remote sensing data. This study uses automated algorithms to process airborne light detection and ranging (LiDAR) data for mapping of riparian vegetation height, canopy cover and corridor width along 5,900 transects using methods validated in 80 mensuration plots in central Pennsylvania, USA. The key objective of this study was to use airborne LiDAR data to quantify differences in edge vs interior vegetation structure as influenced by buffer width and adjacent land use type, continuously throughout a watershed. Riparian vegetation height, canopy cover and buffer width were estimated along FRB transects adjacent to developed (residential/commercial and agricultural) and undeveloped (grassland) land use types and compared to reference transects within larger forested areas and thus without an edge. On average, buffers adjacent to developed land use types were narrower than those adjacent to natural, undeveloped land use types. Approximately 50% of streams in the watershed had FRB corridors 30 m wide. Only 23% of streams had a corridor width 200 m, the width recommended to support key ecosystem services. Undeveloped land use types contained taller riparian vegetation and wider corridors, whereas developed land use types contained shorter riparian vegetation and narrow FRB corridors. Edge effects also affected vegetation structure. Vegetation height was 5–8 m shorter at the interface between the FRB and the adjacent land use (the matrix) than in the naturally occurring stream edge or in the corridor interior. Canopy cover was not influenced by adjacent land use type or width. This study demonstrates that airborne LiDAR data can be used to accurately map riparian buffer vegetation width, height and canopy cover to support ecological based management of riparian corridors over wide areas.Ye

Use of Naturally Available Reference Targets to Calibrate Airborne Laser Scanning Intensity Data

We have studied the possibility of calibrating airborne laser scanning (ALS) intensity data, using land targets typically available in urban areas. For this purpose, a test area around Espoonlahti Harbor, Espoo, Finland, for which a long time series of ALS campaigns is available, was selected. Different target samples (beach sand, concrete, asphalt, different types of gravel) were collected and measured in the laboratory. Using tarps, which have certain backscattering properties, the natural samples were calibrated and studied, taking into account the atmospheric effect, incidence angle and flying height. Using data from different flights and altitudes, a time series for the natural samples was generated. Studying the stability of the samples, we could obtain information on the most ideal types of natural targets for ALS radiometric calibration. Using the selected natural samples as reference, the ALS points of typical land targets were calibrated again and examined. Results showed the need for more accurate ground reference data, before using natural samples in ALS intensity data calibration. Also, the NIR camera-based field system was used for collecting ground reference data. This system proved to be a good means for collecting in situ reference data, especially for targets with inhomogeneous surface reflection properties

Using High Resolution LiDAR Data and a Flux Footprint Parameterization to Scale Evapotranspiration Estimates to Lower Pixel Resolutions

Over the last several decades the hydrologically sensitive Boreal Plains ecoregion of Western Canada has experienced significant warming and drying. To better predict implications of land cover changes on evapotranspiration (ET) and future water resources in this region, high resolution light detection and ranging and energy balance data are used here to spatially parameterize the Penman-Monteith ET model. Within a 5 km × 5 km area of peatland ecosystems, riparian boundaries, and upland mixedwood forests, the influence of land cover heterogeneity on the accuracy of modeled ET is examined at pixel sizes of 1, 10, 25, 250, 500, and 1,000 m, representing resolutions common to popular satellite products (SPOT, Landsat, and MODIS). Modeled ET was compared with tower-based eddy covariance measurements using a weighted flux footprint model. Errors range from 10% to 36% of measured fluxes and results indicate that sensors with small pixel sizes (1 m) offer significantly better accuracy in large heterogeneous flux footprints, while a wider range of pixel sizes (500 m) pixel sizes offered significantly less accuracy, although changes in pixel size within this range offered comparable results

Regional atmospheric cooling and wetting effect of permafrost thaw-induced boreal forest loss

In the sporadic permafrost zone of North America, thaw‐induced boreal forest loss is leading to permafrost‐free wetland expansion. These land cover changes alter landscape‐scale surface properties with potentially large, however, still unknown impacts on regional climates. In this study, we combine nested eddy covariance flux tower measurements with satellite remote sensing to characterize the impacts of boreal forest loss on albedo, eco‐physiological and aerodynamic surface properties, and turbulent energy fluxes of a lowland boreal forest region in the Northwest Territories, Canada. Planetary boundary layer modelling is used to estimate the potential forest loss impact on regional air temperature and atmospheric moisture. We show that thaw‐induced conversion of forests to wetlands increases albedo: and bulk surface conductance for water vapour and decreases aerodynamic surface temperature. At the same time, heat transfer efficiency is reduced. These shifts in land surface properties increase latent at the expense of sensible heat fluxes, thus, drastically reducing Bowen ratios. Due to the lower albedo of forests and their masking effect of highly reflective snow, available energy is lower in wetlands, especially in late winter. Modelling results demonstrate that a conversion of a present‐day boreal forest–wetland to a hypothetical homogeneous wetland landscape could induce a near‐surface cooling effect on regional air temperatures of up to 3–4 °C in late winter and 1–2 °C in summer. An atmospheric wetting effect in summer is indicated by a maximum increase in water vapour mixing ratios of 2 mmol mol−1. At the same time, maximum boundary layer heights are reduced by about a third of the original height. In fall, simulated air temperature and atmospheric moisture between the two scenarios do not differ. Therefore, permafrost thaw‐induced boreal forest loss may modify regional precipitation patterns and slow down regional warming trends

Estimating forest canopy parameters from satellite waveform LiDAR by inversion of the FLIGHT three-dimensional radiative transfer model

The Geoscience Laser Altimeter System (GLAS) has the potential to accurately map global vegetation heights and fractional cover metrics using active laser pulse emission/reception. However, large uncertainties in the derivation of data products exist, since multiple physically plausible interpretations of the data are possible. In this study a method is described and evaluated to derive vegetation height and fractional cover from GLAS waveforms by inversion of the FLIGHT radiative transfer model. A lookup-table is constructed giving expected waveforms for a comprehensive set of canopy realisations, and is used to determine the most likely set of biophysical parameters describing the forest structure, consistent with any given GLAS waveform. The parameters retrieved are canopy height, leaf area index (LAI), fractional cover and ground slope. The range of possible parameters consistent with the waveform is used to give a per-retrieval uncertainty estimate for each retrieved parameter. The retrieved estimates were evaluated first using a simulated data set and then validated against airborne laser scanning (ALS) products for three forest sites coincident with GLAS overpasses. Results for height retrieval show mean absolute error (MAE) of 3.71 m for a mixed temperate forest site within Forest of Dean (UK), 3.35 m for the Southern Old Aspen Site, Saskatchewan, Canada, and 5.13 m for a boreal coniferous site in Norunda, Sweden. Fractional cover showed MAE of 0.10 for Forest of Dean and 0.23 for Norunda. Coefficient of determination between ALS and GLAS estimates over the combined dataset gave R2 values of 0.71 for height and 0.48 for fractional cover, with biases of −3.4 m and 0.02 respectively. Smallest errors were found where overpass dates for ALS data collection closely matched GLAS overpasses. Explicit instrument parameterisation means the method is readily adapted to future planned spaceborne LiDAR instruments such as GEDI