scholarly journals First Evidence of Peat Domes in the Congo Basin using LiDAR from a Fixed-Wing Drone

2020 ◽  
Vol 12 (14) ◽  
pp. 2196
Author(s):  
Ian J. Davenport ◽  
Iain McNicol ◽  
Edward T. A. Mitchard ◽  
Greta Dargie ◽  
Ifo Suspense ◽  
...  
Keyword(s):  
Congo Basin ◽  
Surface Elevation ◽  
Laser Altimeter ◽  
Tropical Peatlands ◽  
Upward Slope ◽  
Peat Surface ◽  
Shallow Basin ◽  
Airborne Vehicle ◽  
Cuvette Centrale

The world’s most extensive tropical peatlands occur in the Cuvette Centrale depression in the Congo Basin, which stores 30.6 petagrams of carbon (95% CI, 6.3–46.8). Improving our understanding of the genesis, development and functioning of these under-studied peatlands requires knowledge of their topography and, in particular, whether the peat surface is domed, as this implies a rain-fed system. Here we use a laser altimeter mounted on an unmanned airborne vehicle (UAV) to measure peat surface elevation along two transects at the edges of a peatland, in the northern Republic of Congo, to centimetre accuracy and compare the results with an analysis of nearby satellite LiDAR data (ICESat and ICESat-2). The LiDAR elevations on both transects show an upward slope from the peatland edge, suggesting a surface elevation peak of around 1.8 m over ~20 km. While modest, this domed shape is consistent with the peatland being rainfed. In-situ peat depth measurements and our LiDAR results indicate that this peatland likely formed at least 10,000 years BP in a large shallow basin ~40 km wide and ~3 m deep.

UAV and Spaceborne LiDAR Gives First Evidence of Peat Domes in the Congo Basin

2020 ◽  
Author(s):  
Ian Davenport ◽  
Iain McNicol ◽  
Edward Mitchard ◽  
Simon Lewis ◽  
Donna Hawthorne ◽  
...  
Keyword(s):  
Congo Basin ◽  
Surface Elevation ◽  
Deep Basin ◽  
Laser Altimeter ◽  
Past Work ◽  
Upward Slope ◽  
Peat Surface ◽  
Airborne Vehicle ◽  
Cuvette Centrale

<p>The peatlands of the Cuvette Centrale depression in the Congo Basin store between 6.3 and 46.8 petagrams of carbon. To improve our understanding of the genesis, development and functioning of these peatlands, we need to know if their surface is domed. Past work using satellite-based instruments has established that if the peatland surface is domed, it is very shallow, below 2‑3 m over a distance of 26km. We used a laser altimeter mounted on an unmanned airborne vehicle (UAV) to measure peat surface elevation along two transects at the edges of a peatland  to centimetre accuracy, and combined the results with an analysis of local ICESat and ICESat-2 returns. The LiDAR elevations show an upward slope inwards from both edges, and the ICESat and ICESat-2 returns suggest a peak around 1.8 m  above the edges. This matches our expectations of a rainfed peatland and, combined with prior measurements of peat depth, indicates that this peatland formed in a 3 m-deep basin.</p>

Mapping the aerodynamic roughness of the Greenland ice sheet surface using ICESat-2

2021 ◽  
Author(s):  
Maurice van Tiggelen ◽  
Paul C.J.P. Smeets ◽  
Carleen H. Reijmer ◽  
Bert Wouters ◽  
Jakob F. Steiner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Elevation ◽  
Spatiotemporal Variability ◽  
Atmospheric Models ◽  
Laser Altimeter ◽  
Eddy Covariance Measurements ◽  
Aerodynamic Roughness

<p>The roughness of a natural surface is an important parameter in atmospheric models, as it determines the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately, this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available.</p><p>In this study, we take advantage of the measurements of the ICESat-2 satellite laser altimeter. We use the geolocated photons product (ATL03) to retrieve a 1-m resolution surface elevation product over the K-transect (West Greenland ice sheet). In combination with a bulk drag partitioning model, the retrieved surface elevation is used to estimate the aerodynamic roughness length (z<sub>0m</sub>) of the surface.</p><p>We demonstrate the high precision of the retrieved ICESat-2 elevation using co-located UAV photogrammetry, and then evaluate the modelled aerodynamic roughness against multiple in situ eddy-covariance observations. The results point out the importance to use a bulk drag model over a more empirical formulation.</p><p>The currently available ATL03 geolocated photons are used to map the aerodynamic roughness along the K-transect (2018-2020). We find a considerable spatiotemporal variability in z<sub>0m</sub>, ranging between 10<sup>−4</sup> m for a smooth snow surface to more than 10<sup>−1</sup> m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.</p>

scholarly journals Evaluation of FORMOSAT-2 and PlanetScope Imagery for Aboveground Oil Palm Biomass Estimation in a Mature Plantation in the Congo Basin

2020 ◽  
Vol 12 (18) ◽  
pp. 2926
Author(s):  
Pierre Migolet ◽  
Kalifa Goïta
Keyword(s):  
Remote Sensing ◽  
Oil Palm ◽  
Aboveground Biomass ◽  
Fourier Transforms ◽  
Canopy Structure ◽  
Principal Component ◽  
Congo Basin ◽  
Biomass Estimation ◽  
Mean Square Errors

The present study developed methods using remote sensing for estimation of total dry aboveground biomass (AGB) of oil palm in the Congo Basin. To achieve this, stem diameters at breast height (DBH, 1.3 m) and stem heights were measured in an oil palm plantation located in Gabon (Congo Basin, Central Africa). These measurements were used to determine AGB in situ. The remote sensing approach that was used to estimate AGB was textural ordination (FOTO) based upon Fourier transforms that were applied, respectively, to PlanetScope and FORMOSAT-2 satellite images taken from the area. The FOTO method is based on the combined use of two-dimensional (2D) Fast Fourier Transform (FFT) and Principal Component Analysis (PCA). In the context of the present study, it was used to characterize the variation in canopy structure and to estimate the aboveground biomass of mature oil palms. Two types of equations linking FOTO indices to in situ biomass were developed: multiple linear regressions (MLR); and multivariate adaptive spline regressions (MARS). All best models developed yielded significant results, regardless of whether they were derived from PlanetScope or from FORMOSAT-2 images. Coefficients of determination (R2) varied between 0.80 and 0.92 (p ≤ 0.0005); and relative root mean-square-errors (%RMSE) were less than 10.12% in all cases. The best model was obtained using MARS approach with FOTO indices from FORMOSAT-2 (%RMSE = 6.09%).

scholarly journals Freeboard, snow depth and sea-ice roughness in East Antarctica from in situ and multiple satellite data

2011 ◽  
Vol 52 (57) ◽  
pp. 242-248 ◽  
Author(s):  
Thorsten Markus ◽  
Robert Massom ◽  
Anthony Worby ◽  
Victoria Lytle ◽  
Nathan Kurtz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Correlation Coefficient ◽  
Satellite Data ◽  
Snow Depth ◽  
Large Scale ◽  
Mean Difference ◽  
Laser Altimeter ◽  
In Situ Data ◽  
Ice Roughness

AbstractIn October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km × 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50–500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. the results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

scholarly journals High-resolution inventory to capture glacier disintegration in the Austrian Silvretta

2021 ◽  
Author(s):  
Andrea Fischer ◽  
Bernd Seiser ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Ice Age ◽  
Surface Elevation ◽  
Glacier Changes ◽  
Wide Range ◽  
Elevation Data ◽  
Glacier Ice ◽  
Geodetic Mass Balance

Abstract. Eastern Alpine glaciers have been receding since the LIA maximum, but the majority of glacier margins could be delineated unambiguously for the last Austrian glacier inventories. Even debris-covered termini, changes in slope, colour or the position of englacial streams enabled at least an in situ survey of glacier outlines. Today the outlines of totally debris-covered glacier ice are fuzzy and raise the theoretical discussion if these glaciogenic features are still glaciers and should be part of the respective inventory – or part of an inventory of transient cryogenic landforms. A new high-resolution glacier inventory (area and surface elevation) was compiled for the years 2017 and 2018 to quantify glacier changes for the Austrian Silvretta region in full. Glacier outlines were mapped manually, based on orthophotos and elevation models and patterns of volume change of 1 to 0.5 m spatial resolution. The vertical accuracy of the DEMs generated from 6 to 8 LiDAR points per m2 is in the order of centimetres. calculated in relation to the previous inventories dating from 2004/2006 (LiDAR), 2002, 1969 (photogrammetry) and to the Little Ice Age maximum extent (moraines). Between 2004/06 and 2017/2018, the 46 glaciers of the Austrian Silvretta lost −29 ± 4 % of their area and now cover 13.1 ± 0.4 km2. This is only 32 ± 2 % of their LIA extent of 40.9 ± 4.1 km2. The area change rate increased from −0.6 %/year (1969–2002) to −2.4 %/year (2004/06–2017/18). The annual geodetic mass balance showed a loss increasing from −0.2 ± 0.1 m w.e./year (1969–2002) to –0.8 m ±0.1 w.e./year (2004/06–2017/18) with an interim peak in 2002–2004/06 at −1.5 ± 0.7 m w.e./year. Identifying the glacier outlines offers a wide range of possible interpretations of former glaciers that have evolved into small and now totally debris-covered cryogenic geomorphological structures. Only the patterns and amounts of volume changes allow us to estimate the area of the buried glacier remnants. To keep track of the buried ice and its fate, and to distinguish increasing debris cover from ice loss, we recommend inventory repeat frequencies of three to five years and surface elevation data with a spatial resolution of one metre.

scholarly journals Data-driven estimates of evapotranspiration and its drivers in the Congo Basin

2020 ◽  
Author(s):  
Michael W. Burnett ◽  
Gregory R. Quetin ◽  
Alexandra G. Konings
Keyword(s):  
Water Balance ◽  
Interannual Variability ◽  
Global Climate ◽  
Weighted Average ◽  
Remotely Sensed ◽  
Congo Basin ◽  
Balance Model ◽  
Climate Data ◽  
Atmospheric Co2 Concentrations

Abstract. Evapotranspiration (ET) from tropical forests serves as a critical moisture source for regional and global climate cycles. However, the magnitude, seasonality, and interannual variability of ET in the Congo Basin remain poorly constrained due to a scarcity of direct observations, despite it being the second-largest river basin the world and containing a vast region of tropical forest. In this study, we applied a water balance model to an array of remotely-sensed and in-situ datasets to produce monthly, basin-wide ET estimates spanning April 2002 to November 2016. Data sources include water storage changes estimated from the Gravity Recover and Climate Experiment (GRACE) satellites, in-situ measurements of river discharge, and precipitation from several remotely sensed sources. An optimal precipitation dataset was determined as a weighted average of interpolated data by Nicholson et al. (2018), Climate Hazards Infrared Precipitation with Station Version 2 (CHIRPS2) data, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks−Climate Data Record product (PERSIANN−CDR), with the relative weights based on the error magnitudes in each dataset as determined by triple collocation. The resulting water balance-derived ET (ETwb) features a long-term average that is consistent with previous studies (117.2 ± 3.5 cm/year), but displays greater seasonal and interannual variability than six global ET products. The seasonal cycle of ETwb generally tracks that of precipitation over the basin, with the exception that ETwb is greater in March–April–May (MAM) than in the relatively wetter September–October–November (SON) periods. This pattern appears to be driven by seasonal variations in diffuse photosynthetically-active radiation (PAR) fraction, net radiation (Rn), and soil water availability. From 2002–2016, Rn, PAR, and vapor-pressure deficit (VPD) all increase significantly within the Congo Basin; however, no corresponding trend occurred in ETwb. We hypothesize that the stability of ETwb over the study period despite sunnier and less humid conditions is likely due to increasing atmospheric CO2 concentrations that offset the impacts of rising VPD and irradiance on stomatal water use efficiency (WUE).

scholarly journals MABEL photon-counting laser altimetry data in Alaska for ICESat-2 simulations and development

2016 ◽  
Vol 10 (4) ◽  
pp. 1707-1719 ◽  
Author(s):  
Kelly M. Brunt ◽  
Thomas A. Neumann ◽  
Jason M. Amundson ◽  
Jeffrey L. Kavanaugh ◽  
Mahsa S. Moussavi ◽  
...  
Keyword(s):  
New Technology ◽  
Photon Counting ◽  
Sampling Strategy ◽  
Laser Altimeter ◽  
Glacier Surface ◽  
Algorithm Development ◽  
In Situ Data ◽  
Melt Ponds ◽  
Water Saturated

Abstract. Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is scheduled to launch in late 2017 and will carry the Advanced Topographic Laser Altimeter System (ATLAS), which is a photon-counting laser altimeter and represents a new approach to satellite determination of surface elevation. Given the new technology of ATLAS, an airborne instrument, the Multiple Altimeter Beam Experimental Lidar (MABEL), was developed to provide data needed for satellite-algorithm development and ICESat-2 error analysis. MABEL was deployed out of Fairbanks, Alaska, in July 2014 to provide a test dataset for algorithm development in summer conditions with water-saturated snow and ice surfaces. Here we compare MABEL lidar data to in situ observations in Southeast Alaska to assess instrument performance in summer conditions and in the presence of glacier surface melt ponds and a wet snowpack. Results indicate the following: (1) based on MABEL and in situ data comparisons, the ATLAS 90 m beam-spacing strategy will provide a valid assessment of across-track slope that is consistent with shallow slopes (< 1°) of an ice-sheet interior over 50 to 150 m length scales; (2) the dense along-track sampling strategy of photon counting systems can provide crevasse detail; and (3) MABEL 532 nm wavelength light may sample both the surface and subsurface of shallow (approximately 2 m deep) supraglacial melt ponds. The data associated with crevasses and melt ponds indicate the potential ICESat-2 will have for the study of mountain and other small glaciers.

scholarly journals Sea ice thickness retrieval algorithms based on in situ surface elevation and thickness values for application to altimetry

2013 ◽  
Vol 118 (8) ◽  
pp. 3807-3822 ◽  
Author(s):  
Burcu Ozsoy-Cicek ◽  
Stephen Ackley ◽  
Hongjie Xie ◽  
Donghui Yi ◽  
Jay Zwally
Keyword(s):  
Sea Ice ◽  
Surface Elevation ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Retrieval Algorithms

scholarly journals Mapping the aerodynamic roughness of the Greenland ice sheet surface using ICESat-2: Evaluation over the K-transect

2021 ◽  
Author(s):  
Maurice van Tiggelen ◽  
Paul C. J. P. Smeets ◽  
Carleen H. Reijmer ◽  
Bert Wouters ◽  
Jakob F. Steiner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Horizontal Resolution ◽  
Spatiotemporal Variability ◽  
Atmospheric Models ◽  
Laser Altimeter ◽  
Laser Altimeters ◽  
Aerodynamic Roughness

Abstract. The aerodynamic roughness of heat, moisture and momentum of a natural surface is an important parameter in atmospheric models, as it co-determines the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available. In this study we adapt a bulk drag partitioning model to estimate the aerodynamic roughness length (z0m) such that it can be applied to 1D (i.e. unidirectional) elevation profiles, typically measured by laser altimeters. We apply the model to a rough ice surface on the K-transect (western Greenland ice sheet) using UAV photogrammetry, and evaluate the modelled roughness against in situ eddy-covariance observations. We then present a method to estimate the topography at 1 m horizontal resolution using the ICESat-2 satellite laser altimeter, and demonstrate the high precision of the satellite elevation profiles against UAV photogrammetry. The currently available satellite profiles are used to map the aerodynamic roughness during different time periods along the K-transect, that is compared to an extensive dataset of in situ observations. We find a considerable spatiotemporal variability in z0m, ranging between 10−4 m for a smooth snow surface over 10−1 m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.

scholarly journals Accuracy assessment of late winter snow depth mapping for tundra environments using Structure-from-Motion photogrammetry

2020 ◽  
pp. 1-17
Author(s):  
Branden Walker ◽  
Evan J. Wilcox ◽  
Philip Marsh
Keyword(s):  
Structure From Motion ◽  
Snow Depth ◽  
Accuracy Assessment ◽  
In Situ Measurements ◽  
Surface Elevation ◽  
Late Winter ◽  
Unmanned Aerial Systems ◽  
Snow Surface ◽  
Winter Snow

Arctic tundra environments are characterized by a spatially heterogeneous end-of-winter snow depth resulting from wind transport and deposition. Traditional methods for measuring snow depth do not accurately capture such heterogeneity at catchment scales. In this study we address the use of high-resolution, spatially distributed, snow depth data for Arctic environments through the application of unmanned aerial systems (UASs). We apply Structure-from-Motion photogrammetry to images collected using a fixed-wing UAS to produce a 1 m resolution snow depth product across seven areas of interest (AOIs) within the Trail Valley Creek Research Watershed, Northwest Territories, Canada. We evaluated these snow depth products with in situ measurements of both the snow surface elevation (n = 8434) and snow depth (n = 7191). When all AOIs were averaged, the RMSE of the snow surface elevation models was 0.16 m (<0.01 m bias), similar to the snow depth product (UASSD) RMSE of 0.15 m (+0.04 m bias). The distribution of snow depth between in situ measurements and UASSD was similar along the transects where in situ snow depth was collected, although similarity varies by AOI. Finally, we provide a discussion of factors that may influence the accuracy of the snow depth products including vegetation, environmental conditions, and study design.

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