Remote sensing and spectroscopy of lichens.

Lichens are combinations of two symbiotic organisms, a green alga or cyanobacterium and a fungus. They grow in nearly all terrestrial ecosystems and survive in habitats, which are very dry or cold, or too poor in nutrients to maintain vegetation growth. Because lichens grow on visible surfaces and exhibit spectral properties, which are clearly different from, for example, vegetation, it is possible to distinguish them in remote sensing data. In this first systematic review article on remote sensing of lichens, we analyze and summarize which lichen species or genera, and in which habitats and geographical regions, have been remotely sensed, and which remote sensing or spectroscopic technologies have been used. We found that laboratory or in situ measured spectra of over 70 lichen species have been reported to date. We show that studies on remote sensing of lichens fall under seven broad themes: (1) collection of lichen spectra for quantification of lichen species or characteristics, (2) pollution monitoring with lichens as ecological indicators, (3) geological and lithological mapping, (4) desert and dryland monitoring, (5) animal habitat monitoring, (6) land cover or vegetation mapping, and (7) surface energy budget modeling.

Intra- and interspecific variation in spectral properties of dominant Sphagnum moss species in boreal peatlands.

Boreal peatlands store ~25 % of global soil organic carbon and host many endangered species; however, they face degradation due to climate change and anthropogenic drainage. In boreal peatlands, vegetation indicates ecohydrological conditions of the ecosystem. Applying remote sensing would enable spatially and temporally continuous monitoring of peatland vegetation. New multi- and hyperspectral satellite data offer promising approaches for understanding the spectral properties of peatland vegetation at high temporal and spectral resolutions. However, using spectral satellite data to their fullest potential requires detailed spectral analyses of dominant species in peatlands. A dominant feature of peatland vegetation is the genus Sphagnum mosses. We investigated how the reflectance spectra of common boreal Sphagnum mosses, collected from waterlogged natural conditions after snowmelt, change when the mosses are desiccated. We conducted a laboratory experiment where the reflectance spectra (350-2500 nm) and the mass of 90 moss samples (representing nine species) were measured repetitively. Furthermore, we examined (i) their inter- and intraspecific spectral differences and (ii) whether the species or their respective habitats could be identified based on their spectral signatures in varying states of drying. Our findings show that the most informative spectral regions to retrieve information about the Sphagnum species and their state of desiccation are in the shortwave infrared region. Furthermore, the visible and near-infrared spectral regions contain less information on species and moisture content. Our results also indicate that hyperspectral data can, to a limited extent, be used to separate mosses belonging to meso- and ombrotrophic habitats. Overall, this study demonstrates the importance of including data especially from the shortwave infrared region (1100-2500 nm) in remote sensing applications of boreal peatlands. The spectral library of Sphagnum mosses collected in this study is available as open data and can be used to develop new methods for remote monitoring of boreal peatlands.

A spectral analysis of stem bark for boreal and temperate tree species.

The woody material of forest canopies has a significant effect on the total forest reflectance and on the interpretation of remotely sensed data, yet research on the spectral properties of bark has been limited. We developed a novel measurement setup for acquiring stem bark reflectance spectra in field conditions, using a mobile hyperspectral camera. The setup was used for stem bark reflectance measurements of ten boreal and temperate tree species in the visible (VIS) to near-infrared (NIR) (400-1000 nm) wavelength region. Twenty trees of each species were measured, constituting a total of 200 hyperspectral reflectance images. The mean bark spectra of species were similar in the VIS region, and the interspecific variation was largest in the NIR region. The intraspecific variation of bark spectra was high for all studied species from the VIS to the NIR region. The spectral similarity of our study species did not correspond to the general phylogenetic lineages. The hyperspectral reflectance images revealed that the distributions of per-pixel reflectance values within images were species-specific. The spectral library collected in this study contributes toward building a comprehensive understanding of the spectral diversity of forests needed not only in remote sensing applications but also in, for example, biodiversity or land surface modeling studies.

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].

[This corrects the article DOI: 10.1016/j.dib.2021.106820.].

A dataset composed of multiangular spectral libraries and auxiliary data at tree, leaf, needle, and bark level for three common European tree species.

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.

Representation of tree cover in global land cover products: Finland as a case study area.

Forest extent mapping is required for climate modeling and monitoring changes in ecosystem state. Different global land cover (LC) products employ simple tree cover (referred also as "forest cover" or even "vegetation cover") definitions to differentiate forests from non-forests. Since 1990, a large number of forest extent maps have become available. Although many studies have compared forest extent data, they often use old data (i.e., around the year 2000). In this study, we assessed tree cover representations of three different annual, global LC products (MODIS VCF (MOD44B, Collection 6 (C6)), MCD12Q1 (C6), and CCI LC (v.2.1.1)) using the Finnish Multi-Source National Forest Inventory (MS-NFI) data for the year 2017. In addition, we present an intercomparison approach for analyzing spatial representations of coniferous and deciduous species. Intercomparison of different LC products is often overlooked due to challenges involved in non-standard and overlapping LC class definitions. Global LC products are used for monitoring changes in land use and land cover and modeling of surface fluxes. Given that LC is a major driver of global change through modifiers such as land surface albedo, more attention should be paid to spatial mapping of coniferous and deciduous species. Our results show that tree cover was either overestimated or underestimated depending on the LC product, and classification accuracy varied between 42 and 75%. Intercomparison of the LC products showed large differences in conifer and deciduous species spatial distributions. Spatial mapping of coniferous and deciduous tree covers was the best represented by the CCI LC product as compared with the reference MS-NFI data.

Empirical validation of photon recollision probability in single crowns of tree seedlings.

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.

A spectral analysis of common boreal ground lichen species.

Lichens dominate a significant part of the Earth's land surface, and are valuable bioindicators of various environmental changes. In the northern hemisphere, the largest lichen biomass is in the woodlands and heathlands of the boreal zone and in tundra. Despite the global coverage of lichens, there has been only limited research on their spectral properties in the context of remote sensing of the environment. In this paper, we report spectral properties of 12 common boreal lichen species. Measurements of reflectance spectra were made in laboratory conditions with a standard spectrometer (350-2500 nm) and a novel mobile hyperspectral camera (400-1000 nm) which was used in a multiangular setting. Our results show that interspecific differences in reflectance spectra were the most pronounced in the ultraviolet and visible spectral range, and that dry samples always had higher reflectance than fresh (moist) samples in the shortwave infrared region. All study species had higher reflectance in the backward scattering direction compared to nadir or forward scattering directions. Our results also reveal, for the first time, that there is large intraspecific variation in reflectance of lichen species. This emphasizes the importance of measuring several replicates of each species when analyzing lichen spectra. In addition, we used the data in a spectral clustering analysis to study the spectral similarity between samples and species, and how these similarities could be linked to different physical traits or phylogenetic closeness of the species. Overall, our results suggest that spectra of some lichen species with large ground coverage can be used for species identification from high spatial resolution remote sensing imagery. On the other hand, for lichen species growing as small assemblages, mobile hyperspectral cameras may offer a solution for in-situ species identification. The spectral library collected in this study is available in the SPECCHIO Spectral Information System.

The impact of tree canopy structure on understory variation in a boreal forest.

Information on understory composition and its relationships with the overstory tree canopy, especially leaf area index (LAI), is crucially needed in, e.g., modeling land-atmosphere interactions and productivity of forests. There are also several global LAI products produced from satellite data which need to be validated with ground reference data. However, to date, only scarce field data on simultaneous structural properties of under- and overstory vegetation, and tree canopy LAI, have been available in boreal forests. This paper shows how understory composition and fractional cover of different species types varies in a boreal forest site, and how it is linked to structural properties of the tree layer. The study is based on 301 understory plots collected in an area of ∼16 km2 around Hyytiälä forestry field station, Finland (61°50'N, 24°17'E) in a southern boreal forest site. Forest understory plot data was accompanied with measurements of both standard forest inventory variables and optically-based canopy light transmittance data. Clear differences in average species composition between different site fertility types were observed, but also large variation within each site fertility type was noted. Forest understory composition was better correlated with structural forest canopy measures (e.g., tree canopy LAI, canopy cover, canopy openness) than with traditional forest inventory variables such as tree height or diameter. Forest canopy LAI and the fractional cover of understory were strongly related, especially in more fertile sites. Our results highlight the role of tree canopy structural metrics as modifiers of the understory light climate and growing conditions, also, in boreal forests.

Dataset of tree canopy structure and variation in understory composition in a boreal forest site.

A field data set from 301 forest plots was collected during peak-growing season (June 24 - July 17, 2013) around Hyytiälä forestry field station in Southern Finland (61° 50' N, 24° 17' E). For all plots, forest variables were collected following local forest inventory practice, and understory cover fractions were estimated using a traditional sampling quadrat. The understory layer in each plot was classified into four site fertility types: herb-rich, mesic, sub-xeric, and xeric. The upper understory layer fractional covers were estimated for: (1) dwarf shrubs, (2) pteridophytes and herbaceous species, and (3) graminoids, and the lower ground layer fractional covers for: (1) mosses, (2) lichens, and (3) litter (including all non-photosynthetic material). Canopy transmittance data were collected using two LAI-2000 device. The transmittance data were used to calculate effective leaf area index, true leaf area index, canopy openness and canopy cover for all plots. The data can be used to parameterize tree canopy and understory compositions in e.g., physically-based reflectance models, land surface models, and regional carbon cycle models. Interpretations of the results are provided in the related article [1].

Temporal dynamics of albedo and climate in the sparse forests of Zagros.

Land surface albedo is an important parameter affecting the climate locally and globally. A synthesis of current studies urgently calls for a better understanding of the impact of climate change on the surface albedo. The Middle East is expected to experience major climatic changes during the coming decades and has already undergone major losses in its vegetation cover. This study explores how climate change related disturbances, such as severe drought and fire events, influence albedo trends in the largest remaining forest area of the Middle East, the Zagros Mountains. We analyzed time series of albedo, Leaf Area Index (LAI), burn severity (dNBR), and the number of fire events all obtained from MODIS satellite images between 2000 and 2016, together with climatic data from 1950 to 2016. The Zagros area is continuously suffering from low precipitation, high temperatures, and evermore-frequent wildfire events. Our large-scale analysis revealed that albedo is linked to precipitation, number of fire events, dNBR, and LAI with the average correlation coefficients of -0.26, -0.50, 0.17, and -0.72, respectively. Using four study sites located in different parts of the Zagros area, we showed disturbances influence albedo differently. Drought condition resulted in a marginal increasing trend in albedo, whereas fire events resulted in a decreasing trend. This article is the first report linking climate change with albedo in Iran.

Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis.

This paper presents the theoretical basis of the algorithm designed for the generation of leaf area index and diurnal course of its sunlit portion from NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR). The Look-up-Table (LUT) approach implemented in the MODIS operational LAI/FPAR algorithm is adopted. The LUT, which is the heart of the approach, has been significantly modified. First, its parameterization incorporates the canopy hot spot phenomenon and recent advances in the theory of canopy spectral invariants. This allows more accurate decoupling of the structural and radiometric components of the measured Bidirectional Reflectance Factor (BRF), improves scaling properties of the LUT and consequently simplifies adjustments of the algorithm for data spatial resolution and spectral band compositions. Second, the stochastic radiative transfer equations are used to generate the LUT for all biome types. The equations naturally account for radiative effects of the three-dimensional canopy structure on the BRF and allow for an accurate discrimination between sunlit and shaded leaf areas. Third, the LUT entries are measurable, i.e., they can be independently derived from both below canopy measurements of the transmitted and above canopy measurements of reflected radiation fields. This feature makes possible direct validation of the LUT, facilitates identification of its deficiencies and development of refinements. Analyses of field data on canopy structure and leaf optics collected at 18 sites in the Hyytiälä forest in southern boreal zone in Finland and hyperspectral images acquired by the EO-1 Hyperion sensor support the theoretical basis.

Theoretical algorithm and application of a double-integrating sphere system for measuring leaf transmittance and reflectance spectra.

We present the theoretical background and analytical equations for calculating spectral reflectance and transmittance factors for plant leaves from data collected by a field spectroradiometer attached to a double-integrating sphere. The sphere constants required for the calculations are derived from measurements of an empty sample port and a diffuse reflectance panel. The new method is applied in measuring the spectra of leaves belonging to 13 tree species. The greatest advantages of a double-sphere system compared with the conventional single-sphere substitution method is the speed of measurements, ease of operation, and increased portability and field-ruggedness.

Analyses of Impact of Needle Surface Properties on Estimation of Needle Absorption Spectrum: Case Study with Coniferous Needle and Shoot Samples.

Leaf scattering spectrum is the key optical variable that conveys information about leaf absorbing constituents from remote sensing. It cannot be directly measured from space because the radiation scattered from leaves is affected by the 3D canopy structure. In addition, some radiation is specularly reflected at the surface of leaves. This portion of reflected radiation is partly polarized, does not interact with pigments inside the leaf and therefore contains no information about its interior. Very little empirical data are available on the spectral and angular scattering properties of leaf surfaces. Whereas canopy-structure effects are well understood, the impact of the leaf surface reflectance on estimation of leaf absorption spectra remains uncertain. This paper presents empirical and theoretical analyses of angular, spectral, and polarimetric measurements of light reflected by needles and shoots of Pinus koraiensis and Picea koraiensis species. Our results suggest that ignoring the leaf surface reflected radiation can result in an inaccurate estimation of the leaf absorption spectrum. Polarization measurements may be useful to account for leaf surface effects because radiation reflected from the leaf surface is partly polarized, whereas that from the leaf interior is not.

Quantitative characterization of clumping in Scots pine crowns.

BACKGROUND AND AIMS: Proper characterization of the clumped structure of forests is needed for calculation of the absorbed radiation and photosynthetic production by a canopy. This study examined the dependency of crown-level clumping on tree size and growth conditions in Scots pine (Pinus sylvestris), and determined the ability of statistical canopy radiation models to quantify the degree of self-shading within crowns as a result of the clumping effect. METHODS: Twelve 3-D Scots pine trees were generated using an application of the LIGNUM model, and the crown-level clumping as quantified by the crown silhouette to total needle area ratio (STAR(crown)) was calculated. The results were compared with those produced by the stochastic approach of modelling tree crowns as geometric shapes filled with a random medium. KEY RESULTS: Crown clumping was independent of tree height, needle area and growth conditions. The results supported the capability of the stochastic approach in characterizing clumping in crowns given that the outer shell of the tree crown is well represented. CONCLUSIONS: Variation in the whole-stand clumping index is induced by differences in the spatial pattern of trees as a function of, for example, stand age rather than by changes in the degree of self-shading within individual crowns as they grow bigger.

Hyperspectral remote sensing of foliar nitrogen content.

A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact--it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

Backscattering measurements from individual Scots pine needles.

We present ground reference measurements of the directional scattering properties of conifer needles. As the development of multiangular remote sensing instruments sets a growing need for reliable ground reference measurement techniques and databases, there is an increasing demand for data on the spectral properties of conifer needles in forest reflectance modeling and the inversion of physically based models. These data are scarce due to technical and conceptual problems related to measuring thin needles, and the needle directional spectral properties are currently nonexistent even for single wavelengths. We present results from measuring the monochromatic backscattering of Scots pine needles in a controlled laboratory environment; we feel these results of the hot spot signatures of individual conifer needles are unique. The experiment was conducted at 1,064 nm with an instrument constructed specifically for backscatter measurement, based on techniques commonly used for laser backscattering measurements and CCD photometry. Strong backscattering peaks near 0 degrees were observed for the needles, the amplitude of the brightening being up to approximately 40%.