Browsing by Author "Schaepman, Michael E."

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  • Corrigendum to ‘A dataset composed of multiangular spectral libraries and auxiliary data at tree, leaf, needle, and bark level for three common European tree species’ [Data in Brief 35 (2021) 106820] (Data in Brief (2021) 35, (S2352340921001049), (10.1016/j.dib.2021.106820))
    (2021-08) Hovi, Aarne; Forsström, Petri R.; Ghielmetti, Giulia; Schaepman, Michael E.; Rautiainen, Miina
     Comment/debate
    The authors regret that Eq. 6 in the article is incorrect. The term GT should be subtracted from the quotient of DNleaf,T/DNWR_leaf,T (not from DNleaf,T in the numerator). The correct equation is: [Formula presented] The error was only in the article text and therefore did not influence the data published. The authors would like to apologise for any inconvenience caused.
  • A dataset composed of multiangular spectral libraries and auxiliary data at tree, leaf, needle, and bark level for three common European tree species
    (2021-04) Hovi, Aarne; Forsström, Petri R.; Ghielmetti, Giulia; Schaepman, Michael E.; Rautiainen, Miina
     Data Article
    This article describes a dataset of multiangular scattering properties of small trees (height = 0.38–0.7 m) at visible, near-infrared, and shortwave-infrared wavelengths (350–2500 nm), and provides supporting auxiliary data that comprise leaf, needle, and bark spectra, and structural characteristics of the trees. Multiangular spectra were measured for 18 trees belonging to three common European tree species: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), and sessile oak (Quercus petraea (Matt.) Liebl.). The measurements were performed in 47 different view angles across a hemisphere, using a laboratory goniometer and a non-imaging spectrometer. Leaf and needle spectra were measured for each tree, using a non-imaging spectrometer coupled to an integrating sphere. Bark spectra were measured for one sample tree per species. In addition, leaf and needle fresh mass, surface area of leaves, needles, and woody parts, silhouette area, and spherically averaged silhouette to total area ratio (STAR) for each tree were measured or derived from the measurements. The data are useful for modeling the shortwave reflectance characteristics of small trees and potentially forests, and thus benefit climate modeling or interpretation of remote sensing data.
  • Empirical validation of photon recollision probability in single crowns of tree seedlings
    (2020-11) Hovi, Aarne; Forsström, Petri; Ghielmetti, Giulia; Schaepman, Michael E.; Rautiainen, Miina
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Physically-based methods in remote sensing provide benefits over statistical approaches in monitoring biophysical characteristics of vegetation. However, physically-based models still demand large computational resources and often require rather detailed informative priors on various aspects of vegetation and atmospheric status. Spectral invariants and photon recollision probability theories provide a solid theoretical framework for developing relatively simple models of forest canopy reflectance. Empirical validation of these theories is, however, scarce. Here we present results of a first empirical validation of a model based on photon recollision probability at the level of individual trees. Multiangular spectra of pine, spruce, and oak tree seedlings (height = 0.38–0.7 m) were measured using a goniometer, and tree hemispherical reflectance was derived from those measurements. We evaluated the agreement between modeled and measured tree reflectance. The model predicted the spectral signatures of the tree seedlings in the wavelength range between 400 and 2300 nm well, with wavelength-specific bias between −0.048 and 0.034 in reflectance units. In relative terms, the model errors were the smallest in the near-infrared (relative RMSE up to 4%, 7%, and 4% for pine, spruce, and oak seedlings, respectively) and the largest in the visible wavelength region (relative RMSE up to 34%, 20%, and 60%). The errors in the visible region could be partly attributed to wavelength-dependent directional scattering properties of the leaves. Including woody parts of tree seedlings in the model improved the results by reducing the relative RMSE by up to 10% depending on species and wavelength. Spectrally invariant model parameters, i.e. total and directional escape probabilities, depended on spherically averaged silhouette to total area ratio (STAR) of the tree seedlings. Overall, the modeled and measured tree reflectance mainly agreed within measurement uncertainties, but the results indicate that the assumption of isotropic scattering by the leaves can result in large errors in the visible wavelength region for some tree species. Our results help increasing the confidence when using photon recollision probability and spectral invariants -based models to interpret satellite images, but they also lead to an improved understanding of the assumptions and limitations of these theories.
  • Multi-angular reflectance spectra of small single trees
    (2021-03-15) Forsström, Petri R.; Hovi, Aarne; Ghielmetti, Giulia; Schaepman, Michael E.; Rautiainen, Miina
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Understanding the reflectance anisotropy of forests and the underlying scattering mechanisms is needed to improve the accuracy of retrievals of fundamental forest characteristics from optical remote sensing data. In this paper, we developed a laboratory measurement set-up for a large goniometer (LAGOS) and measured multi-angular spectra (350–2500 nm) of 18 small trees, composed of three common European tree species: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), sessile oak (Quercus petraea (Matt.) Liebl.). For all trees, we measured tree spectra in 47 view angles in the upper hemisphere. To our knowledge, this is the first study reporting multi-angular reflectance spectra of single trees. We also measured the reflectance and transmittance spectra of needles and leaves, as well as reflectance spectra of bark of the sample trees. We analyzed the spectro-directional characteristics of the trees, and the inter- and intraspecific variations of these characteristics. The anisotropy of trees was shown to be strongly asymmetrical and characteristic to species: while pine and spruce exhibited strong hotspot effects, oak showed a strong specular component. Our results indicate that simultaneous measurements of both spectral and directional characteristics of trees may enhance the discrimination of species and thus, support the retrieval of information of their biophysical properties.
  • Multi-Sensor Aboveground Biomass Estimation in the Broadleaved Hyrcanian Forest of Iran
    (2021-11-02) Ronoud, Ghasem; Fatehi, Parviz; Darvishsefat, Ali A.; Tomppo, Erkki; Praks, Jaan; Schaepman, Michael E.
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    In this study, the capability of Landsat-8 (L8), Sentinel-2 (S2), Sentinel-1 (S1), and their combination was investigated for estimating aboveground biomass (AGB). A pure stand of Fagus Orientalis located in the Hyrcanian forest of Iran was selected as the study area. The performance of a parametric approach, i.e., Multiple Linear Regression (MLR) model and non-parametric approaches, i.e., k-Nearest Neighbor (k-NN), Random Forest (RF), and Support Vector Regression (SVR), were also evaluated for AGB estimations. Our results indicated that among S2 metrics, the FAPAR canopy biophysical index and NDVI index based on the red-edge band (NIR-b8a) have the highest correlation coefficient (r) of 0.420 and 0.417, respectively. The results of AGB estimation showed that a combination of S2 and S1 datasets using the k-NN algorithm had the best accuracy (R 2 of 0.57 and rRMSE of 14.68%). The best rRMSE using L8, S2, and S1 datasets was 18.95, 16.99, and 19.17% using k-NN, k-NN, and MLR algorithms, respectively. The combination of L8 with S1 dataset also improved the rRMSE relative to L8 and S1 separately by 0.96 and 1.18%, respectively. We concluded that the combination of optical data (L8 or S2) with SAR data (S1) improves the broadleaved Hyrcanian AGB estimation.
  • Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data
    (2016-03) Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.