ORCID Profile
0000-0002-1271-8103
Current Organisation
University of Bonn
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Photogrammetry and Remote Sensing | Geomatic Engineering |
Expanding Knowledge in Technology | Expanding Knowledge in the Environmental Sciences | Ecosystem Assessment and Management at Regional or Larger Scales | Expanding Knowledge in the Biological Sciences | Flora, Fauna and Biodiversity at Regional or Larger Scales
Publisher: Springer Science and Business Media LLC
Date: 06-2018
Publisher: Elsevier BV
Date: 08-2011
Publisher: Wiley
Date: 27-03-2014
DOI: 10.1002/ROB.21508
Publisher: Elsevier BV
Date: 09-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Publisher: Elsevier BV
Date: 05-2007
Publisher: IEEE
Date: 07-2018
Publisher: Elsevier BV
Date: 02-2012
Publisher: IEEE
Date: 07-2018
Publisher: Elsevier BV
Date: 11-2021
Publisher: MDPI AG
Date: 23-12-2021
DOI: 10.3390/RS14010056
Abstract: Current rapid technological improvement in optical radiometric instrumentation provides an opportunity to develop innovative measurements protocols where the remote quantification of the plant physiological status can be determined with higher accuracy. In this study, the leaf and canopy reflectance variability in the PRI spectral region (i.e., 500–600 nm) is quantified using different laboratory protocols that consider both instrumental and experimental set-up aspects, as well as canopy structural effects and vegetation photoprotection dynamics. First, we studied how an incorrect characterization of the at-target incoming radiance translated into an erroneous vegetation reflectance spectrum and consequently in an incorrect quantification of reflectance indices such as PRI. The erroneous characterization of the at-target incoming radiance translated into a 2% overestimation and a 31% underestimation of estimated chlorophyll content and PRI-related vegetation indexes, respectively. Second, we investigated the dynamic xanthophyll pool and intrinsic Chl vs. Car long-term pool changes affecting the entire 500–600 nm spectral region. Consistent spectral behaviors were observed for leaf and canopy experiments. Sun-adapted plants showed a larger optical change in the PRI range and a higher capacity for photoprotection during the light transient time when compared to shade-adapted plants. Outcomes of this work highlight the importance of well-established spectroscopy s ling protocols to detect the subtle photochemical features which need to be disentangled from the structural and biological effects.
Publisher: Oxford University Press (OUP)
Date: 04-2013
DOI: 10.1093/JXB/ERT069
Abstract: A dedicated field experiment was conducted to investigate the response of a green reflectance continuum removal-based optical index, called area under the curve normalized to maximal band depth between 511 nm and 557 nm (ANMB511-557), to light-induced transformations in xanthophyll cycle pigments of Norway spruce [Picea abies (L.) Karst] needles. The performance of ANMB511-557 was compared with the photochemical reflectance index (PRI) computed from the same leaf reflectance measurements. Needles of four crown whorls (fifth, eighth, 10th, and 15th counted from the top) were s led from a 27-year-old spruce tree throughout a cloudy and a sunny day. Needle optical properties were measured together with the composition of the photosynthetic pigments to investigate their influence on both optical indices. Analyses of pigments showed that the needles of the examined whorls varied significantly in chlorophyll content and also in related pigment characteristics, such as the chlorophyll/carotenoid ratio. The investigation of the ANMB511-557 diurnal behaviour revealed that the index is able to follow the dynamic changes in the xanthophyll cycle independently of the actual content of foliar pigments. Nevertheless, ANMB511-557 lost the ability to predict the xanthophyll cycle behaviour during noon on the sunny day, when the needles were exposed to irradiance exceeding 1000 µmol m(-2) s(-1). Despite this, ANMB511-557 rendered a better performance for tracking xanthophyll cycle reactions than PRI. Although declining PRI values generally responded to excessive solar irradiance, they were not able to predict the actual de-epoxidation state in the needles examined.
Publisher: Springer Science and Business Media LLC
Date: 20-09-2019
DOI: 10.1007/S11120-019-00664-3
Abstract: Regulated heat dissipation under excessive light comprises a complexity of mechanisms, whereby the supramolecular light-harvesting pigment–protein complex (LHC) shifts state from light harvesting towards heat dissipation, quenching the excess of photo-induced excitation energy in a non-photochemical way. Based on whole-leaf spectroscopy measuring upward and downward spectral radiance fluxes, we studied spectrally contiguous (hyperspectral) transient time series of absorbance A ( λ , t ) and passively induced chlorophyll fluorescence F ( λ , t ) dynamics of intact leaves in the visible and near-infrared wavelengths (VIS–NIR, 400–800 nm) after sudden strong natural-like illumination exposure. Besides light avoidance mechanism, we observed on absorbance signatures, calculated from simultaneous reflectance R ( λ , t ) and transmittance T ( λ , t ) measurements as A ( λ , t ) = 1 − R ( λ , t ) − T( λ , t ), major dynamic events with specific onsets and kinetical behaviour. A consistent well-known fast carotenoid absorbance feature (500–570 nm) appears within the first seconds to minutes, seen from both the reflected (backscattered) and transmitted (forward scattered) radiance differences. Simultaneous fast Chl features are observed, either as an increased or decreased scattering behaviour during quick light adjustment consistent with re-organizations of the membrane. The carotenoid absorbance feature shows up simultaneously with a major F decrease and corresponds to the xanthophyll conversion, as quick response to the proton gradient build-up. After xanthophyll conversion ( t = 3 min), a kinetically slower but major and smooth absorbance increase was occasionally observed from the transmitted radiance measurements as wide peaks in the green (~ 550 nm) and the near-infrared (~ 750 nm) wavelengths, involving no further F quenching. Surprisingly, in relation to the response to high light, this broad and consistent VIS–NIR feature indicates a slowly induced absorbance increase with a sigmoid kinetical behaviour. In analogy to sub-leaf-level observations, we suggest that this mechanism can be explained by a structure-induced low-energy-shifted energy redistribution involving both Car and Chl. These findings might pave the way towards a further non-invasive spectral investigation of antenna conformations and their relations with energy quenching at the intact leaf level, which is, in combination with F measurements, of a high importance for assessing plant photosynthesis in vivo and in addition from remote observations.
Publisher: Springer Science and Business Media LLC
Date: 05-2019
Publisher: MDPI AG
Date: 02-05-2014
DOI: 10.3390/RS6054003
Publisher: IEEE
Date: 2007
Publisher: Wiley
Date: 17-06-2015
DOI: 10.1111/NPH.13524
Abstract: The health of several East Antarctic moss‐beds is declining as liquid water availability is reduced due to recent environmental changes. Consequently, a noninvasive and spatially explicit method is needed to assess the vigour of mosses spread throughout rocky Antarctic landscapes. Here, we explore the possibility of using near‐distance imaging spectroscopy for spatial assessment of moss‐bed health. Turf chlorophyll a and b , water content and leaf density were selected as quantitative stress indicators. Reflectance of three dominant Antarctic mosses Bryum pseudotriquetrum , Ceratodon purpureus and Schistidium antarctici was measured during a drought‐stress and recovery laboratory experiment and also with an imaging spectrometer outdoors on water‐deficient (stressed) and well‐watered (unstressed) moss test sites. The stress‐indicating moss traits were derived from visible and near infrared turf reflectance using a nonlinear support vector regression. Laboratory estimates of chlorophyll content and leaf density were achieved with the lowest systematic/unsystematic root mean square errors of 38.0/235.2 nmol g −1 DW and 0.8/1.6 leaves mm −1 , respectively. Subsequent combination of these indicators retrieved from field hyperspectral images produced small‐scale maps indicating relative moss vigour. Once applied and validated on remotely sensed airborne spectral images, this methodology could provide quantitative maps suitable for long‐term monitoring of Antarctic moss‐bed health.
Publisher: MDPI AG
Date: 26-03-2013
DOI: 10.3390/F10030292
Abstract: Advances in high-performance computer resources and exploitation of high-density terrestrial laser scanning (TLS) data allow for reconstruction of close-to-reality 3D forest scenes for use in canopy radiative transfer models. Consequently, our main objectives were (i) to reconstruct 3D representation of Norway spruce (Picea abies) trees by deriving distribution of woody and foliage elements from TLS and field structure data and (ii) to use the reconstructed 3D spruce representations for evaluation of the effects of canopy structure on forest reflectance simulated in the Discrete Anisotropic Radiative Transfer (DART) model. Data for this study were combined from two spruce research sites located in the mountainous areas of the Czech Republic. The canopy structure effects on simulated top-of-canopy reflectance were evaluated for four scenarios (10 × 10 m scenes with 10 trees), ranging from geometrically simple to highly detailed architectures. First scenario A used predefined simple tree crown shapes filled with a turbid medium with simplified trunks and branches. Other three scenarios used the reconstructed 3D spruce representations with B detailed needle shoots transformed into turbid medium, C with simplified shoots retained as facets, and D with detailed needle shoots retained as facets D. For the first time, we demonstrated the capability of the DART model to simulate reflectance of complex coniferous forest scenes up to the level of a single needle (scenario D). Simulated bidirectional reflectance factors extracted for each scenario were compared with actual airborne hyperspectral and space-borne Sentinel-2 MSI reflectance data. Scenario A yielded the largest differences from the remote sensing observations, mainly in the visible and NIR regions, whereas scenarios B, C, and D produced similar results revealing a good agreement with the remote sensing data. When judging the computational requirements for reflectance simulations in DART, scenario B can be considered as most operational spruce forest representation, because the transformation of 3D shoots in turbid medium reduces considerably the simulation time and hardware requirements.
Publisher: Elsevier BV
Date: 10-2008
DOI: 10.1016/J.SCITOTENV.2007.11.006
Abstract: Dissolved organic matter in soils can be predicted from forest floor C:N ratio, which in turn is related to foliar chemistry. Little is known about the linkages between foliar constituents such as chlorophylls, lignin, and cellulose and the concentrations of water-extractable forest floor dissolved organic carbon and dissolved organic nitrogen. Lignin and cellulose are not mobile in foliage and thus may be indicative of growing conditions during prior years, while chlorophylls respond more rapidly to the current physiological status of a tree and reflect nutrient availability. The aim of this study was to examine potential links among spectral foliar data, and the organic C and N of forest soils. Two coniferous species (red spruce and balsam fir) were studied in the White Mountains of New H shire, USA. Six trees of each species were s led at 5 watersheds (2 in the Hubbard Brook Experimental Forest, 3 in the Bartlett Experimental Forest). We hypothesized that in a coniferous forest, chemistry of old foliage would better predict the chemical composition of the forest floor litter layer than younger foliage, which is the more physiologically active and the most likely to be captured by remote sensing of the canopy. Contrary to our expectations, chlorophyll concentration of young needles proved to be most tightly linked to soil properties, in particular water-extractable dissolved organic carbon. Spectral indices related to the chlorophyll content of needles could be used to predict variation in forest floor dissolved organic carbon and dissolved organic nitrogen. Strong correlations were found between optical spectral indices based on chlorophyll absorption and forest floor dissolved organic carbon, with higher foliage chlorophyll content corresponding to lower forest floor dissolved organic carbon. The mechanisms behind these correlations are uncertain and need further investigation. However, the direction of the linkage from soil to tree via nutrient availability is hypothesized based on negative correlations found between foliar N and forest floor dissolved organic carbon.
Publisher: IEEE
Date: 07-2017
Publisher: Elsevier BV
Date: 06-2018
Publisher: Elsevier BV
Date: 06-2018
Publisher: IEEE
Date: 07-2018
Publisher: MDPI AG
Date: 05-02-2015
DOI: 10.3390/RS70201667
Publisher: Elsevier BV
Date: 09-2019
Publisher: MDPI AG
Date: 15-10-2018
DOI: 10.3390/S18103465
Abstract: We investigate footprint geolocation uncertainties of a spectroradiometer mounted on an unmanned aircraft system (UAS). Two microelectromechanical systems-based inertial measurement units (IMUs) and global navigation satellite system (GNSS) receivers were used to determine the footprint location and extent of the spectroradiometer. Errors originating from the on-board GNSS/IMU sensors were propagated through an aerial data georeferencing model, taking into account a range of values for the spectroradiometer field of view (FOV), integration time, UAS flight speed, above ground level (AGL) flying height, and IMU grade. The spectroradiometer under nominal operating conditions (8 ∘ FOV, 10 m AGL height, 0.6 s integration time, and 3 m/s flying speed) resulted in footprint extent of 140 cm across-track and 320 cm along-track, and a geolocation uncertainty of 11 cm. Flying height and orientation measurement accuracy had the largest influence on the geolocation uncertainty, whereas the FOV, integration time, and flying speed had the biggest impact on the size of the footprint. Furthermore, with an increase in flying height, the rate of increase in geolocation uncertainty was found highest for a low-grade IMU. To increase the footprint geolocation accuracy, we recommend reducing flying height while increasing the FOV which compensates the footprint area loss and increases the signal strength. The disadvantage of a lower flying height and a larger FOV is a higher sensitivity of the footprint size to changing distance from the target. To assist in matching the footprint size to uncertainty ratio with an appropriate spatial scale, we list the expected ratio for a range of IMU grades, FOVs and AGL heights.
Publisher: Elsevier BV
Date: 11-2015
Publisher: Elsevier BV
Date: 15-03-2010
Publisher: MDPI AG
Date: 07-03-2016
DOI: 10.3390/F7030062
Publisher: Springer Science and Business Media LLC
Date: 21-09-2012
Publisher: CSIRO Publishing
Date: 2012
DOI: 10.1071/FP12107
Abstract: This laboratory experiment tested the ability of the spectral index called ‘area under curve normalised to maximal band depth’ (ANMB) to track dynamic changes in the xanthophyll cycle of Norway spruce (Picea abies (L.) Karsten) needles. Four-year-old spruce seedlings were gradually acclimated to different photosynthetic photon flux densities (PPFDs) and air temperature regimes. The measurements were conducted at the end of each acclimation period lasting for 11 days. A significant decline in the chlorophylls to carotenoids ratio and the increase of the amount of xanthophyll cycle pigments indicated a higher need for carotenoid-mediated photoprotection in spruce leaves acclimated to high PPFD conditions. Similarly, the photochemical reflectance index (PRI) changed from positive to negative values after changing light conditions from low to high intensity as a consequence of the increase in carotenoid content. Systematic responses of PRI to the de-epoxidation state of xanthophyll cycle pigments (DEPS) were, however, observed only during high temperature treatments and after the exposition of needles to high irradiance. The ANMB index computed from needle reflectance between 507 and 556 nm was able to track dynamic changes in DEPS without any influence induced by changing the content of leaf photosynthetic pigments (chlorophylls, carotenoids).
Publisher: MDPI AG
Date: 30-08-2022
DOI: 10.3390/RS14174287
Abstract: Remotely sensed morphological traits have been used to assess functional ersity of forests. This approach is potentially spatial-scale-independent. Lidar data collected from the ground or by drone at a high point density provide an opportunity to consider multiple ecologically meaningful traits at fine-scale ecological units such as in idual trees. However, high-spatial-resolution and multi-trait datasets used to calculate functional ersity can produce large volumes of data that can be computationally resource demanding. Functional ersity can be derived through a trait probability density (TPD) approach. Computing TPD in a high-dimensional trait space is computationally intensive. Reductions of the number of dimensions through trait selection and principal component analysis (PCA) may reduce the computational load. Trait selection can facilitate identification of ecologically meaningful traits and reduce inter-trait correlation. This study investigates whether kernel density estimator (KDE) or one-class support vector machine (SVM) may be computationally more efficient in calculating TPD. Four traits were selected for input into the TPD: canopy height, effective number of layers, plant to ground ratio, and box dimensions. When simulating a high-dimensional trait space, we found that TPD derived from KDE was more efficient than using SVM when the number of input traits was high. For five or more traits, applying dimension reduction techniques (e.g., PCA) are recommended. Furthermore, the kernel size for TPD needs to be appropriate for the ecological target unit and should be appropriate for the number of traits. The kernel size determines the required number of data points within the trait space. Therefore, 3–5 traits require a kernel size of at least 7×7pixels. This study contributes to improving the quality of TPD calculations based on traits derived from remote sensing data. We provide a set of recommendations based on our findings. This has the potential to improve reliability in identifying bio ersity hotspots.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Elsevier BV
Date: 10-2015
Publisher: Elsevier BV
Date: 09-2021
Publisher: Springer Science and Business Media LLC
Date: 09-08-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2017
Publisher: Wiley
Date: 20-05-2016
DOI: 10.1002/EJHF.592
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 10-2019
Publisher: MDPI AG
Date: 25-01-2022
DOI: 10.3390/RS14030567
Abstract: Leaf biochemical traits indicating early symptoms of plant stress can be assessed using imaging spectroscopy combined with radiative transfer modelling (RTM). In this study, we assessed the potential applicability of the leaf radiative transfer model Fluspect-Cx to simulate optical properties and estimate leaf biochemical traits through inversion of two native Australian eucalypt species: Eucalyptus dalrympleana and E. delegetensis. The comparison of measured and simulated optical properties revealed the necessity to recalibrate the refractive index and specific absorption coefficients of the eucalypt leaves’ biochemical constituents. Subsequent validation of the modified Fluspect-Cx showed a closer agreement with the spectral measurements. The average root mean square error (RMSE) of reflectance, transmittance and absorptance values within the wavelength interval of 450–1600 nm was smaller than 1%. We compared the performance of both the original and recalibrated Fluspect-Cx versions through inversions aiming to simultaneously retrieve all model inputs from leaf optical properties with and without prior information. The inversion of recalibrated Fluspect-Cx constrained by laboratory-based measurements produced a superior accuracy in estimations of leaf water content (RMSE = 0.0013 cm, NRMSE = 6.55%) and dry matter content (RMSE = 0.0036 g·cm−2, NRMSE = 21.28%). The estimation accuracies of chlorophyll content (RMSE = 8.46 µg·cm−2, NRMSE = 24.73%), carotenoid content (RMSE = 3.83 µg·cm−2, NRMSE = 30.82%) and anthocyanin content (RMSE = 1.69 µg·cm−2, NRMSE = 37.12%) were only marginally better than for the inversion without any constraints. Additionally, we investigated the possibility to substitute the prior information derived in the laboratory by non-destructive reflectance-based spectral indices sensitive to the retrieved biochemical traits, resulting in the most accurate estimation of carotenoid content (RMSE = 3.65 µg·cm−2, NRMSE = 29%). Future coupling of the recalibrated Fluspect with a forest canopy RTM is expected to facilitate retrieval of biophysical traits from spectral air/space-borne image data, allowing for assessing the actual physiological status and health of eucalypt forest canopies.
Publisher: MDPI AG
Date: 22-04-2019
DOI: 10.3390/RS11080956
Abstract: Satellite gravimetry allows for determining large scale mass transport in the system Earth and to quantify ice mass change in polar regions. We provide, evaluate and compare a long time-series of monthly gravity field solutions derived either by satellite laser ranging (SLR) to geodetic satellites, by GPS and K-band observations of the GRACE mission, or by GPS observations of the three Swarm satellites. While GRACE provides gravity signal at the highest spatial resolution, SLR sheds light on mass transport in polar regions at larger scales also in the pre- and post-GRACE era. To bridge the gap between GRACE and GRACE Follow-On, we also derive monthly gravity fields using Swarm data and perform a combination with SLR. To correctly take all correlations into account, this combination is performed on the normal equation level. Validating the Swarm/SLR combination against GRACE during the overlapping period January 2015 to June 2016, the best fit is achieved when down-weighting Swarm compared to the weights determined by variance component estimation. While between 2014 and 2017 SLR alone slightly overestimates mass loss in Greenland compared to GRACE, the combined gravity fields match significantly better in the overlapping time period and the RMS of the differences is reduced by almost 100 Gt. After 2017, both SLR and Swarm indicate moderate mass gain in Greenland.
Publisher: Elsevier BV
Date: 04-2007
Publisher: Elsevier BV
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2014
Publisher: Oxford University Press (OUP)
Date: 12-06-2014
Abstract: The photosynthesis of various species or even a single plant varies dramatically in time and space, creating great spatial heterogeneity within a plant canopy. Continuous and spatially explicit monitoring is, therefore, required to assess the dynamic response of plant photosynthesis to the changing environment. This is a very challenging task when using the existing portable field instrumentation. This paper reports on the application of a technique, laser-induced fluorescence transient (LIFT), developed for ground remote measurement of photosynthetic efficiency at a distance of up to 50 m. The LIFT technique was used to monitor the seasonal dynamics of selected leaf groups within inaccessible canopies of deciduous and evergreen tree species. Electron transport rates computed from LIFT measurements varied over the growth period between the different species studied. The LIFT canopy data and light-use efficiency measured under field conditions correlated reasonably well with the single-leaf pulse litude-modulated measurements of broadleaf species, but differed significantly in the case of conifer tree species. The LIFT method has proven to be applicable for a remote sensing assessment of photosynthetic parameters on a diurnal and seasonal scale further investigation is, however, needed to evaluate the influence of complex heterogeneous canopy structures on LIFT-measured chlorophyll fluorescence parameters.
Publisher: Elsevier BV
Date: 12-2022
Publisher: Elsevier BV
Date: 05-2012
Publisher: Elsevier BV
Date: 2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2014
Publisher: Informa UK Limited
Date: 12-2006
Publisher: Elsevier BV
Date: 04-2013
Publisher: Oxford University Press (OUP)
Date: 07-2021
DOI: 10.1093/INSILICOPLANTS/DIAB026
Abstract: This study presents a method for three-dimensional (3D) reconstruction of forest tree species that are, for instance, required for simulations of 3D canopies in radiative transfer modelling. We selected three forest species of different architecture: Norway spruce (Picea abies) and European beech (Fagus sylvatica), representatives of European production forests, and white peppermint (Eucalyptus pulchella), a common forest species of Tasmania. Each species has a specific crown structure and foliage distribution. Our algorithm for 3D model construction of a single tree is based on terrestrial laser scanning (TLS) and ancillary field measurements of leaf angle distribution, percentage of current-year and older leaves, and other parameters that could not be derived from TLS data. The algorithm comprises four main steps: (i) segmentation of a TLS tree point cloud separating wooden parts from foliage, (ii) reconstruction of wooden parts (trunks and branches) from TLS data, (iii) biologically genuine distribution of foliage within the tree crown and (iv) separation of foliage into two age categories (for spruce trees only). The reconstructed 3D models of the tree species were used to build virtual forest scenes in the Discrete Anisotropic Radiative Transfer model and to simulate canopy optical signals, specifically: angularly anisotropic top-of-canopy reflectance (for retrieval of leaf biochemical compounds from nadir canopy reflectance signatures captured in airborne imaging spectroscopy data) and solar-induced chlorophyll fluorescence signal (for experimentally unfeasible sensitivity analyses).
Publisher: Springer Science and Business Media LLC
Date: 15-02-2019
Publisher: The Royal Society
Date: 07-2014
Abstract: Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.
Publisher: Elsevier BV
Date: 09-2019
Publisher: Wiley
Date: 14-07-2017
Publisher: Copernicus GmbH
Date: 22-06-2016
DOI: 10.5194/ISPRSARCHIVES-XLI-B7-961-2016
Abstract: In this study we evaluated various spectral inputs for retrieval of forest chlorophyll content (Cab) and leaf area index (LAI) from high spectral and spatial resolution airborne imaging spectroscopy data collected for two forest study sites in the Czech Republic (beech forest at Štítná nad Vláří and spruce forest at Bílý Kříž). The retrieval algorithm was based on a machine learning method – support vector regression (SVR). Performance of the four spectral inputs used to train SVR was evaluated: a) all available hyperspectral bands, b) continuum removal (CR) 645 – 710 nm, c) CR 705 – 780 nm, and d) CR 680 – 800 nm. Spectral inputs and corresponding SVR models were first assessed at the level of spectral databases simulated by combined leaf-canopy radiative transfer models PROSPECT and DART. At this stage, SVR models using all spectral inputs provided good performance (RMSE for Cab & 10 μg cm& sup& & minus & /sup& and for LAI & 1.5), with consistently better performance for beech over spruce site. Since application of trained SVRs on airborne hyperspectral images of the spruce site produced unacceptably overestimated values, only the beech site results were analysed. The best performance for the Cab estimation was found for CR bands in range of 645 – 710 nm, whereas CR bands in range of 680 – 800 nm were the most suitable for LAI retrieval. The CR transformation reduced the across-track bidirectional reflectance effect present in airborne images due to large sensor field of view.
Publisher: Elsevier BV
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: IEEE
Date: 2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Location: Czechia
Location: United States of America
Start Date: 2019
End Date: 2021
Funder: Australian Antarctic Division
View Funded ActivityStart Date: 2017
End Date: 2021
Funder: Australian Research Council
View Funded ActivityStart Date: 09-2017
End Date: 05-2021
Amount: $652,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2018
End Date: 12-2019
Amount: $159,450.00
Funder: Australian Research Council
View Funded Activity