Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests

Global Ecosystem Dynamics Investigation (GEDI) satellite mission is expanding the spatial bounds and temporal resolution of large-scale mapping applications. Integrating the recent GEDI data into Airborne Laser Scanning (ALS)-derived estimations represents a global opportunity to update and extend forest models based on area based approaches (ABA) considering temporal and spatial dynamics. This study evaluates the effect of combining ALS-based aboveground biomass (AGB) estimates with GEDI-derived models by using temporally coincident datasets. A gradient of forest ecosystems, distributed through 21,766 km2 in the province of Badajoz (Spain), with different species and structural complexity, was used to: (i) assess the accuracy of GEDI canopy height in five Mediterranean Ecosystems and (ii) develop GEDI-based AGB models when using ALS-derived AGB estimates at GEDI footprint level. In terms of Pearson’s correlation (r) and rRMSE, the agreement between ALS and GEDI statistics on canopy height was stronger in the denser and homogeneous coniferous forest of P. pinaster and P. pinea than in sparse Quercus-dominated forests. The GEDI-derived AGB models using relative height and vertical canopy metrics yielded a model efficiency (Mef) ranging from 0.31 to 0.46, with a RMSE ranging from 14.13 to 32.16 Mg/ha and rRMSE from 38.17 to 84.74%, at GEDI footprint level by forest type. The impact of forest structure confirmed previous studies achievements, since GEDI data showed higher uncertainty in highly multilayered forests. In general, GEDI-derived models (GEDI-like Level4A) underestimated AGB over lower and higher ALS-derived AGB intervals. The proposed models could also be used to monitor biomass stocks at large-scale by using GEDI footprint level in Mediterranean areas, especially in remote and hard-to-reach areas for forest inventory. The findings from this study serve to provide an initial evaluation of GEDI data for estimating AGB in Mediterranean forest.

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Large-scale prediction of aboveground biomass in heterogeneous mountain forests by means of airborne laser scanning

Canadian Journal of Forest Research ◽

10.1139/cjfr-2016-0086 ◽

2016 ◽

Vol 46 (9) ◽

pp. 1138-1144 ◽

Cited By ~ 13

Author(s):

M. Maltamo ◽

O.M. Bollandsås ◽

T. Gobakken ◽

E. Næsset

Keyword(s):

Aboveground Biomass ◽

Laser Scanning ◽

Large Scale ◽

Airborne Laser Scanning ◽

Mountain Forests ◽

Airborne Laser ◽

Model Predictions ◽

Growing Conditions ◽

Southern Norway ◽

Forest Conditions

This study considered airborne laser scanning (ALS) based aboveground biomass (AGB) prediction in mountain forests. The study area consisted of a long transect from southern Norway to northern parts of the country with wide ranges of elevation along a long latitudinal gradient (58°N–69°N). This transect was covered by ALS data and field data from 238 plots. AGB was modeled using different types of predictor variables, namely ALS metrics, variables related to growing conditions (elevation, latitude, and climatic variables), and tree species information. Modelling of AGB in the long transect covering diverse mountainous forest conditions was challenging: the RMSE values were rather large (37%–70%). The effects of growing conditions on model predictions were minor. However, species information was essential to improve accuracy. The analysis revealed that when doing inventories of spruce-dominated areas, all plots should be pooled together when the models are developed, whereas if pine or deciduous species dominate the area in question, separate dominant species-wise models should be constructed.

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A geomorphometric approach to estimate soil volumes stored in agricultural terrace systems

10.5194/egusphere-egu21-1772 ◽

2021 ◽

Author(s):

Sara Cucchiaro ◽

Guido Paliaga ◽

Daniel J. Fallu ◽

Ben R. Pears ◽

Kevin Walsh ◽

...

Keyword(s):

High Resolution ◽

Laser Scanning ◽

Large Scale ◽

Multiple Scales ◽

Anthropogenic Activities ◽

New Technology ◽

Agricultural Systems ◽

Soil Thickness ◽

The Impact ◽

Geomorphological Features

Geomorphometric information can be exploited to study the most extensive and common landforms that humans have ever produced: agricultural terraces. An understanding of these historical ecosystems can only be determined through in-depth knowledge of their origin, evolution, and current state in the landscape. These factors can ultimately assist in the future preservation of such landforms in a world increasingly affected by anthropogenic activities. High-resolution topographic (HRT) techniques allow the mapping and characterization of geomorphological features with wide-ranging perspectives at multiple scales. From HRT surveys, it is possible to produce high-resolution Digital Terrain Models (DTMs) to extract important geomorphometric parameters such as topographic curvature, to identify terrace edges, even if abandoned or covered by uncontrolled vegetation. By using riser bases as well as terrace edges (riser tops) and through the computation of minimum curvature, it is possible to obtain environmentally useful information on these agricultural systems such as terrace soil thickness and volumes. The quantification of terrace volumes can provide new benchmarks for soil erosion models, new perspectives for land and stakeholders for terrace management in terms of natural hazard and offer a measure of the effect of these agricultural systems on soil organic carbon (SOC) sequestration. This work aims to realize and test an innovative and rapid methodological workflow to estimate the minimum anthropogenic reworked and moved soil of terrace systems in different landscapes. This aspect of new technology and its application to terrace soil-systems has not been fully explored in the literature. We start with remote terrace mapping at a large scale (using Airborne Laser Scanning) and then utilize more detailed HRT surveys (i.e., Structure from Motion and Terrestrial Laser Scanning) to extract geomorphological features, from which the original theoretical slope-surface of terrace systems were derived. These last elements were compared with in-field sedimentological recording obtained from the excavations across the study sites to assess the nature of sub-surface topographies. The results of this work have produced accurate DTMs of Difference (DoD) for three terrace sites in central Europe in Italy and Belgium. The utilization of ground-truthing through field excavation and sampling has confirmed the reliability of the methodology used across a range of sites with very specific terrace morphologies, and in each case has confirmed the nature of the reconstructed, theoretical original slope. Differences between actual and theoretical terraces from DTM and excavation evidence have been used to estimate the minimum soil volumes and masses used to remould slopes. Moreover, geomorphometric analysis through indices such as sediment connectivity permitted also to quantify the volume of sediment transported downstream, with the associated and mobilized C, after a collapsed terrace. The quantification of terrace soil volumes provides extremely useful standards for further multi-disciplinary analysis on the terrace sediments themselves, aiding physical geographers, geoarchaeologists, palaeo-environmentalists, and landscape historians in the understanding of terrace systems and the impact of agricultural processes on the landscape.

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Accuracy Assessment of GEDI Terrain Elevation and Canopy Height Estimates in European Temperate Forests: Influence of Environmental and Acquisition Parameters

Remote Sensing ◽

10.3390/rs12233948 ◽

2020 ◽

Vol 12 (23) ◽

pp. 3948

Author(s):

Markus Adam ◽

Mikhail Urbazaev ◽

Clémence Dubois ◽

Christiane Schmullius

Keyword(s):

Laser Scanning ◽

Temperate Forests ◽

Accuracy Assessment ◽

Canopy Cover ◽

Global Scale ◽

Canopy Height ◽

Ecosystem Dynamics ◽

Vegetation Height ◽

Height Estimates ◽

Terrain Elevation

Lidar remote sensing has proven to be a powerful tool for estimating ground elevation, canopy height, and additional vegetation parameters, which in turn are valuable information for the investigation of ecosystems. Spaceborne lidar systems, like the Global Ecosystem Dynamics Investigation (GEDI), can deliver these height estimates on a near global scale. This paper analyzes the accuracy of the first version of GEDI ground elevation and canopy height estimates in two study areas with temperate forests in the Free State of Thuringia, central Germany. Digital terrain and canopy height models derived from airborne laser scanning data are used as reference heights. The influence of various environmental and acquisition parameters (e.g., canopy cover, terrain slope, beam type) on GEDI height metrics is assessed. The results show a consistently high accuracy of GEDI ground elevation estimates under most conditions, except for areas with steep slopes. GEDI canopy height estimates are less accurate and show a bigger influence of some of the included parameters, specifically slope, vegetation height, and beam sensitivity. A number of relatively high outliers (around 9–13% of the measurements) is present in both ground elevation and canopy height estimates, reducing the estimation precision. Still, it can be concluded that GEDI height metrics show promising results and have potential to be used as a basis for further investigations.

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Reconstruction of GRACE Total Water Storage Through Automated Machine Learning

10.5194/gstm2020-53 ◽

2020 ◽

Author(s):

Alex Sun ◽

Bridget Scanlon ◽

Himanshu Save ◽

Ashraf Rateb

Keyword(s):

Machine Learning ◽

Spatial Variability ◽

Large Scale ◽

Water Storage ◽

Total Water ◽

New Paradigm ◽

Satellite Mission ◽

Automated Machine Learning ◽

The Mean ◽

The Impact

The GRACE satellite mission and its follow-on, GRACE-FO, have provided unprecedented opportunities to quantify the impact of climate extremes and human activities on total water storage at large scales. The approximately one-year data gap between the two GRACE missions needs to be filled to maintain data continuity and maximize mission benefits. There is strong interest in using machine learning (ML) algorithms to reconstruct GRACE-like data to fill this gap. So far, most studies attempted to train and select a single ML algorithm to work for global basins. However, hydrometeorological predictors may exhibit strong spatial variability which, in turn, may affect the performance of ML models. Existing studies have already shown that no single algorithm consistently outperformed others over all global basins. In this study, we applied an automated machine learning (AutoML) workflow to perform GRACE data reconstruction. AutoML represents a new paradigm for optimal model structure selection, hyperparameter tuning, and model ensemble stacking, addressing some of the most challenging issues related to ML applications. We demonstrated the AutoML workflow over the conterminous U.S. (CONUS) using six types of ML algorithms and multiple groups of meteorological and climatic variables as predictors. Results indicate that the AutoML-assisted gap filling achieved satisfactory performance over the CONUS. For the testing period (2014/06&#8211;2017/06), the mean gridwise Nash-Sutcliffe efficiency is around 0.85, the mean correlation coefficient is around 0.95, and the mean normalized root-mean square error is about 0.09. Trained models maintain good performance when extrapolating to the mission gap and to GRACE-FO periods (after 2017/06). Results further suggest that no single algorithm provides the best predictive performance over the entire CONUS, stressing the importance of using an end-to-end workflow to train, optimize, and combine multiple machine learning models to deliver robust performance, especially when building large-scale hydrological prediction systems and when predictor importance exhibits strong spatial variability.

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Geophysical Challenges for Future Satellite Gravity Missions: Assessing the Impact of MOCASS Mission

Pure and Applied Geophysics ◽

10.1007/s00024-021-02774-3 ◽

2021 ◽

Author(s):

T. Pivetta ◽

C. Braitenberg ◽

D. F. Barbolla

Keyword(s):

Spatial Resolution ◽

Large Scale ◽

Cold Atom ◽

Mountain Range ◽

Cumulative Number ◽

Mass Detection ◽

Satellite Mission ◽

Satellite Gravity ◽

The Impact ◽

Satellite Gravity Missions

AbstractThe GRACE/GRACE-FO satellites have observed large scale mass changes, contributing to the mass budget calculation of the hydro-and cryosphere. The scale of the observable mass changes must be in the order of 300 km or bigger to be resolved. Smaller scale glaciers and hydrologic basins significantly contribute to the closure of the water mass balance, but are not detected with the present spatial resolution of the satellite. The challenge of future satellite gravity missions is to fill this gap, providing higher temporal and spatial resolution. We assess the impact of a geodetic satellite mission carrying on board a cold atom interferometric gradiometer (MOCASS: Mass Observation with Cold Atom Sensors in Space) on the resolution of simulated geophysical phenomena, considering mass changes in the hydrosphere and cryosphere. Moreover, we consider mass redistributions due to seamounts and tectonic movements, belonging to the solid earth processes. The MOCASS type satellite is able to recover 50% smaller deglaciation rates over a mountain range as the High Mountains of Asia compared to GRACE, and to detect the mass of 60% of the cumulative number of glaciers, an improvement respect to GRACE which detects less than 20% in the same area. For seamounts a significantly smaller mass eruption could be detected with respect to GRACE, reaching a level of mass detection of a submarine basalt eruption of 1.6 109 m3. This mass corresponds to the eruption of Mount Saint Helens. The simulations demonstrate that a MOCASS type mission would significantly improve the resolution of mass changes respect to existing geodetic satellite missions.

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A simple model to estimate exchange rates of nitrogen dioxide between the atmosphere and forests

Biogeosciences Discussions ◽

10.5194/bgd-2-1033-2005 ◽

2005 ◽

Vol 2 (4) ◽

pp. 1033-1065 ◽

Cited By ~ 3

Author(s):

J. Duyzer ◽

K. Pilegaard ◽

D. Simpson ◽

H. Weststrate ◽

S. Walton

Keyword(s):

Simple Model ◽

Large Scale ◽

Deciduous Forest ◽

Dispersion Model ◽

Coniferous Forest ◽

Model Calculations ◽

Exchange Processes ◽

Reactive Gases ◽

Trunk Space ◽

The Impact

Abstract. A simple model (2layer) was constructed that describes the exchange of the reactive gases NO, NO2 and O3 between forest and the atmosphere. The model uses standard equations to describe exchange processes and uptake of gases. It also takes into account reactions taking place in the trunk space between NO and O3 and photolysis of NO2. All equations are solved analytically leading to a scheme efficient enough to allow implementation in a large scale dispersion model such as the EMEP model. The model is tested on two comprehensive datasets obtained in a coniferous forest and a deciduous forest. The model calculations of NO2 and O3 fluxes to the forest were compared with observations of these fluxes. Although the comparison is often not perfect some of the striking features of the observed fluxes i.e. upward fluxes of NO2 were simulated quite well. The impact of chemical reactions between O3, NO and NO2 in the trunk space appear to have a significant effect on the deposition rate of O2. This is especially true during the night and more so for forests emitting large amounts of NO.

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Deforestation Processes in the Polish Mountains in the Context of Terrain Topography

Forests ◽

10.3390/f10111027 ◽

2019 ◽

Vol 10 (11) ◽

pp. 1027 ◽

Cited By ~ 1

Author(s):

Bałazy ◽

Ciesielski ◽

Waraksa ◽

Zasada ◽

Zawiła-Niedźwiecki

Keyword(s):

Laser Scanning ◽

Large Scale ◽

Airborne Lidar ◽

Aerial Images ◽

Forest Dieback ◽

The Past ◽

Hazardous Chemical ◽

Sudety Mountains ◽

Landsat Satellite ◽

The Impact

In the 1980s, the Western Sudety Mountains were affected by a forest dieback process, resulting in large-scale deforestation covering an area of about 15,000 ha. A similar phenomenon is presently being observed in the Western Beskidy and Eastern Sudety Mountains, where the course of the process and the final effects are similar. The presented study analyzed the relationships between forest dieback processes today and in the past. Among others, the impact of the following factors was examined: exposure, slope, altitude, and topographic index, which was generated based on the airborne LIDAR (also airborne laser scanning abbreviated as ALS) data. The identification of forest dieback areas in the past was carried out based on the archived Landsat satellite imagery, as well as data obtained from the Polish State Forests. The identification of forest dieback areas at present was carried out based on the ALS data (single-tree detection approach) and color infrared aerial images. In the study, inter-dependencies between forest dieback today and in the past were compared. The performed analyses show significant differences between forests’ dieback specifics in all three areas. The process first occurred at 800–900 m a.s.l., and afterwards at over 900 m. Mortality was especially intensive on the western and southwestern slopes. Below 700 m a.s.l., forests survived quite well. In the 1980s, significantly higher concentrations of hazardous chemical compounds were noted, which resulted in respectively greater deforestations on aspects open to the operation of prevailing winds (mainly west). Nowadays, a proportionately higher number of trees die on the southern aspects, which is particularly visible in the Western Sudety Mountains.

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Towards synergy of GNSS and InSAR mining deformation monitoring with Sentinel-1 data

10.5194/egusphere-egu21-11416 ◽

2021 ◽

Author(s):

Damian Tondaś ◽

Maya Ilieva ◽

Witold Rohm ◽

Jan Kapłon

Keyword(s):

Time Series ◽

Real Time ◽

Laser Scanning ◽

Large Scale ◽

Ground Deformation ◽

Dimensional Space ◽

Satellite Navigation ◽

Deformation Monitoring ◽

North East ◽

The Impact

The determination of ground deformation may be carried out by applying various measurement methods such as levelling, laser scanning, satellite navigation systems, Synthetic Aperture Radar (SAR) and many others. In this work, we focus on the comparison of the deformation effects measured by Global Navigation Satellite Systems (GNSS) and satellite Interferometric SAR (InSAR) methods in the Upper-Silesian coal mining region (SW Poland).An unquestionable advantage of GNSS technology is the possibility of continuous monitoring of deformations in three-dimensional space. Moreover, the evolution of real-time (RT) techniques such as: near real-time (NRT), ultra-fast NRT or RT allows to obtain a high precise position determination with a relatively slight latency (ranging from a few seconds to less than one hour). The limitation of the satellite navigation technology is the spatial range of the measurements. The deformation can only be observed at the point where the GNSS antenna is located. Furthermore, the acquisition, installation and maintenance of the equipment may also involve high costs.In contrast to the GNSS technique, the InSAR methods enable measurement of the large-scale subsidence areas with possibility to use free products and software (e.g. Sentinel-1 and SNAP). The large-scale InSAR investigations provide a better overview of local terrain changes. Unfortunately, InSAR methods also have some limitations related to data acquisition technology: &#160;<ul><li>a few days latency in acquiring a new image,</li> <li>insensitivity to changes in the northern component,</li> <li>acquiring deformation only in the LOS direction.</li> </ul>The main goal of this research is to analyse the deformation results obtained using GNSS and InSAR methods with respect to the capabilities and limitations of these two techniques. We investigated the level of agreement of eight GNSS and InSAR time series in areas with no subsidence, together with results acquired on seven regions of mining deformation where the maximum subsidence velocity exceeds 50 cm/year. The mean RMS time series fitting error obtained in subsidence basin is more than 5 cm and in non-deformed areas is equal to 2 cm. The study also investigated the effect of coherence threshold levels (0.3 &#247; 0.6) with introduction of the northern GNSS component on the InSAR decomposition process. Assuming the same GNSS deformation value in each directions (north, east, and up), the impact of the northern component was estimated as 10% of the total LOS subsidence.

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Unraveling the hydrological budget of isolated and seasonally contrasted subtropical lakes

Hydrology and Earth System Sciences ◽

10.5194/hess-23-1705-2019 ◽

2019 ◽

Vol 23 (3) ◽

pp. 1705-1724 ◽

Cited By ~ 3

Author(s):

Chloé Poulin ◽

Bruno Hamelin ◽

Christine Vallet-Coulomb ◽

Guinbe Amngar ◽

Bichara Loukman ◽

...

Keyword(s):

Surface Water ◽

Isotopic Composition ◽

Mass Balance ◽

Water Budget ◽

Large Scale ◽

Satellite Mission ◽

Simple Method ◽

Lake Chad ◽

Aquifer Systems ◽

The Impact

Abstract. Complete understanding of the hydrological functioning of large-scale intertropical watersheds such as the Lake Chad basin is becoming a high priority in the context of climate change in the near future and increasing demographic pressure. This requires integrated studies of all surface water and groundwater bodies and of their quite-complex interconnections. We present here a simple method for estimating the annual mean water balance of sub-Sahelian lakes subject to high seasonal contrast and located in isolated regions with no road access during the rainy season, a situation which precludes continuous monitoring of in situ hydrological data. Our study focuses for the first time on two lakes, Iro and Fitri, located in the eastern basin of Lake Chad. We also test the approach on Lake Ihotry in Madagascar, used as a benchmark site that has previously been extensively studied by our group. We combine the δ18O and δ2H data that we measured during the dry season with altimetry data from the SARAL satellite mission in order to model the seasonal variation of lake volume and isotopic composition. The annual water budget is then estimated from mass balance equations using the Craig–Gordon model for evaporation. We first show that the closed-system behavior of Lake Ihotry (i.e., precipitation equal to evaporation) is well simulated by the model. For lakes Iro and Fitri, we calculate evaporation to influx ratios (E∕I) of 0.6±0.3 and 0.4±0.2, respectively. In the case of the endorheic Lake Fitri, the estimated output flux corresponds to the infiltration of surface water toward the surface aquifer that regulates the chemistry of the lake. These results constitute a first-order assessment of the water budget of these lakes, in regions where direct hydrological and meteorological observations are very scarce or altogether lacking. Finally, we discuss the implications of our data on the hydro-climatic budget at the scale of the catchment basins. We observe that the local evaporation lines (LELs) obtained on both lake and aquifer systems are slightly offset from the average rainfall isotopic composition monitored by IAEA at N'Djamena (Chad), and we show that this difference may reflect the impact of vegetation transpiration on the basin water budget. Based on the discussion of the mass balance budget we conclude that, while being broadly consistent with the idea that transpiration is on the same order of magnitude as evaporation in those basins, we cannot derive a more precise estimate of the partition between these two fluxes, owing to the large uncertainties of the different end-members in the budget equations.

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Parameter Localization of Greenhouse Gas Value Model and Greenhouse Gas Storage Simulation for Forest Ecosystems in China

Forests ◽

10.3390/f11111150 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1150

Author(s):

Mengdi Li ◽

Yaoping Cui ◽

Yaochen Qin ◽

Oliva Gabriel Chubwa ◽

Yiming Fu ◽

...

Keyword(s):

Greenhouse Gas ◽

Large Scale ◽

Forest Ecosystems ◽

Low Cost ◽

Coniferous Forest ◽

Mixed Forest ◽

Historical Analysis ◽

Wide Distribution ◽

Forest Change ◽

The Impact

Quantifying the greenhouse gas (GHG) storage in forest ecosystems can support global change directly, from a biogeochemical perspective. However, accurately assessing the amount of GHG storage in forest ecosystems still faces challenges in China because of their wide distribution, varying types, and the changing definitions and areas of forests. We used land-use data with 5-year intervals during 1990–2015 to investigate the spatiotemporal variations of forest ecosystems in China. As three major greenhouse gases in forest ecosystems, the potential storage of carbon dioxide, methane, and nitrous oxide can be calculated by a greenhouse gas value (GHGV) model. The results showed that the total area of forest ecosystems decreased by 15 × 105 ha during the study period. The area of forest ecosystems reached its highest level in 1995 and then declined. For various forest ecosystem types, shrubbery (Sh) increased by 0.82% but the broad-leaved forest, evergreen coniferous forest (ECF), and mixed forest (MF) all showed a downward trend. Correspondingly, the potential GHG storage of forest ecosystems declined from 156.97 Pg CO2-equivalent (CO2-eq) to 155.56 Pg CO2-eq, a decrease of 1.41 Pg CO2-eq. Compared with previous research results, the GHGV model proved to be an important supplementary method for estimating the potential storage of GHGs in forest ecosystems, especially in highly fragmented landscapes at a large scale. Our study indicated that the impact of forest ecosystems changes on potential GHG storage was serious during the study period. Our findings highlight that the GHGV model can be an effective and low-cost strategy to simulate the forest change and corresponding GHG storage. And considering the efficiency of the model and the historical analysis results of many periods, some of the results can also be used to inform the future afforestation programs and assess the expected GHG storage in China.

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