Key message
Leaf area index and species composition influence red-to-near-infrared and red-to-shortwave-infrared transmittance ratios of boreal and temperate forest canopies.
In this short ...communication paper, we present how the spectral composition of transmitted shortwave radiation (350–2200 nm) varies in boreal and temperate forests based on a detailed set of measurements conducted in Finland and Czechia. Our results show that within-stand variation in canopy transmittance is wavelength dependent, and is the largest for sparse forest stands. Increasing leaf area index (LAI) reduces the overall level of transmittance as well as red-to-near-infrared and red-to-shortwave-infrared transmittance ratios. Given the same LAI, these ratios are lower for broadleaved than for coniferous forests. These results demonstrate the importance of both LAI and forest type (broadleaved vs. coniferous) in determining light quality under forest canopies.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Lichens are sensitive to competition from vascular plants, intensive silviculture, pollution and reindeer and caribou grazing, and can therefore serve as indicators of environmental changes. ...Hyperspectral remote sensing data has been proved promising for estimation of plant diversity, but its potential for forest floor lichen cover estimation has not yet been studied. In this study, we investigated the use of hyperspectral data in estimating ground lichen cover in boreal forest stands in Finland. We acquired airborne and in situ hyperspectral data of lichen-covered forest plots, and applied multiple endmember spectral mixture analysis to estimate the fractional cover of ground lichens in these plots. Estimation of lichen cover based on in situ spectral data was very accurate (coefficient of determination (r2) 0.95, root mean square error (RMSE) 6.2). Estimation of lichen cover based on airborne data, on the other hand, was fairly good (r2 0.77, RMSE 11.7), but depended on the choice of spectral bands. When the hyperspectral data were resampled to the spectral resolution of Sentinel-2, slightly weaker results were obtained. Tree canopy cover near the flight plots was weakly related to the difference between estimated and measured lichen cover. The results also implied that the presence of dwarf shrubs could influence the lichen cover estimates.
Understory trees in multilayered stands are often ignored in forest inventories. Information about them would benefit silviculture, wood procurement, and biodiversity management. Cost-efficient ...inventory methods are needed and airborne LiDAR is a promising addition to fieldwork. The overstory, however, obstructs wall-to-wall sampling of the understory using LiDAR, because transmission losses affect echo-triggering probabilities and intensity (peak amplitude) observations. We examined the potential of LiDAR in mapping of understory trees in pine (Pinus sylvestris L.) stands (62°N, 24°E), using careful experimentation. We formulated a conceptual model for the transmission losses and illustrated that loss normalization is highly ill-posed, especially for vegetation. The losses skew the population of targets that produce a subsequent echo. Losses up to 10–15% can occur even if an overstory echo is not triggered. In LiDAR sensors, quantized intensity values start from binary zero, but actually should include an offset, the noise level. We estimated these empirically. Constraining to low-loss pulses and ground data, we estimated parameters for compensation models that were based on the radar equation and employed the geometry of the pulse, as well as the overstory intensity observations as predictors. Intensity variation of second-return data was reduced, but, the intensity data were deemed of low value in species discrimination. Our results highlight differences between sensors in near-ground echo-triggering and height data. Area-based LiDAR height metrics from the understory had reasonable correlation with the density and mean height of the understory trees, whereas tree species seemed out of reach even if the transmission losses were compensated for. We conclude that transmission losses are a general impediment for radiometric analysis of multi-echo pulses in discrete-return and waveform LiDAR data.
► Detailed analyses of pulse–target interactions for understory trees. ► Intensity data compensation for transmission losses. ► Explanation to the inherent dissimilarity of multiple echo data. ► Between-sensor differences in near-ground LiDAR data were revealed. ► Results on tree species discrimination in the understory.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Automatization of tree species identification in the field is crucial in improving forest-based bioeconomy, supporting forest management, and facilitating in situ data collection for remote sensing ...applications. However, tree species recognition has never been addressed with hyperspectral reflectance images of stem bark before. We investigated how stem bark texture differs between tree species using a hyperspectral camera set-up and gray level co-occurrence matrices and assessed the potential of using reflectance spectra and texture features of stem bark to identify tree species. The analyses were based on 200 hyperspectral reflectance data cubes (415-925 nm) representing ten tree species. There were subtle interspecific differences in bark texture. Using average spectral features in linear discriminant analysis classifier resulted in classification accuracy of 92-96.5%. Using spectral and texture features together resulted in accuracy of 93-97.5%. With a convolutional neural network, we obtained an accuracy of 94%. Our study showed that the spectral features of stem bark were robust for classifying tree species, but importantly, bark texture is beneficial when combined with spectral data. Our results suggest that in situ imaging spectroscopy is a promising sensor technology for developing accurate tree species identification applications to support remote sensing.
Spectral mixture analysis was used to estimate the contribution of woody elements to tree level reflectance from airborne hyperspectral data in boreal forest stands in Finland. Knowledge of the ...contribution of woody elements to tree or forest reflectance is important in the context of lea area index (LAI) estimation and, e.g., in the estimation of defoliation due to insect outbreaks, from remote sensing data. Field measurements from four Scots pine ( L.), five Norway spruce ( (L.) Karst.) and four birch ( Roth and Ehrh.) dominated plots, spectral measurements of needles, leaves, bark, and forest floor, airborne hyperspectral as well as airborne laser scanning data were used together with a physically-based forest reflectance model. We compared the results based on simple linear combinations of measured bark and needle/leaf spectra to those obtained by accounting for multiple scattering of radiation within the canopy using a physically-based forest reflectance model. The contribution of forest floor to reflectance was additionally considered. The resulted mean woody element contribution estimates varied from 0.140 to 0.186 for Scots pine, from 0.116 to 0.196 for birches and from 0.090 to 0.095 for Norway spruce, depending on the model used. The contribution of woody elements to tree reflectance had a weak connection to plot level forest variables.
Pinus sylvestris
Picea abies
Betula pendula
Betula pubescens
Coniferous species are present in almost all major vegetation biomes on Earth, though they are the most abundant in the northern hemisphere, where they form the northern tree and forest lines close ...to the Arctic Circle. Monitoring coniferous forests with satellite and airborne remote sensing is active, due to the forests’ great ecological and economic importance. We review the current understanding of spectral behavior of different components forming coniferous forests. We look at the spatial, directional, and seasonal variations in needle, shoot, woody element, and understory spectra in coniferous forests, based on measurements. Through selected case studies, we also demonstrate how coniferous canopy spectra vary at different spatial scales, and in different viewing angles and seasons. Finally, we provide a synthesis of gaps in the current knowledge on spectra of elements forming coniferous forests that could also serve as a recommendation for planning scientific efforts in the future.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating ...leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beamsâ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our methodâs output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.
Leaf reflectance and transmittance spectra are urgently needed in interpretation of remote sensing data and modeling energy budgets of vegetation. The measurement methods should be fast to operate ...and preferably portable to enable quick collection of spectral databases and in situ measurements. At the same time, the collected spectra must be comparable across measurement campaigns. We compared three different methods for acquiring leaf reflectance and transmittance spectra. These were a single integrating sphere (ASD RTS-3ZC), a small double integrating sphere (Ocean Optics SpectroClip-TR), and a leaf clip (PP Systems UNI501 Mini Leaf Clip). With all methods, an ASD FieldSpec 4 spectrometer was used to measure white paper and tree leaves. Single and double integrating spheres showed comparable within-method variability in the measurements. Variability with leaf clip was slightly higher. The systematic difference in mean reflectance spectra between single and double integrating spheres was only minor (average relative difference of 1%), whereas a large difference (14%) was observed in transmittance. Reflectance measured with leaf clip was on average 14% higher compared to single integrating sphere. The differences between methods influenced also spectral vegetation indices calculated from the spectra, particularly those that were designed to track small changes in spectra. Measurements with double integrating sphere were four, and with leaf clip six times as fast as with single integrating sphere, if slightly reduced signal level (integration time reduced from optimum) was allowed for the double integrating sphere. Thus, these methods are fast alternatives to a conventional single integrating sphere. However, because the differences between methods depended on the measured target and wavelength, care must be taken when comparing the leaf spectra acquired with different methods.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Foliage spectra form an important input to physically-based forest reflectance models. However, little is known about geographical variability of coniferous needle spectra. In this research note, we ...present an assessment of the geographical variability of Norway spruce ( (L.) H. Karst.) needle albedo, reflectance, and transmittance spectra across three study sites covering latitudes of 49â62°N in Europe. All spectra were measured and processed using exactly the same methodology and parameters, which guarantees reliable conclusions about geographical variability. Small geographical variability in Norway spruce needle spectra was observed, when compared to variability observed between previous measurement campaigns (employing slightly varying measurement and processing parameters), or to variability between plant functional types (broadleaved vs. coniferous). Our results suggest that variability of needle spectra is not a major factor introducing geographical variability to forest reflectance. The results also highlight the importance of harmonizing measurement protocols when collecting needle spectral libraries. Furthermore, the data collected for this study can be useful in studies where accurate information on spectral differences between broadleaved and coniferous tree foliage is needed.
Picea abies
Leaf reflectance and transmittance spectra are essential information in many applications such as developing remote sensing methods, computing shortwave energy balance (albedo) of forest canopies, ...and monitoring health or stress of trees. Measurement of coniferous needle spectra has usually been carried out with single integrating spheres, which has involved a lot of tedious manual work. A small double integrating sphere would make the measurements considerably faster, because of its ease of operation and small sample sizes required. Here we applied a compact double integrating sphere setup, used previously for measurement of broad leaves, for measurement of coniferous needles. Test measurements with the double integrating sphere showed relative underestimation of needle albedo by 5â39% compared to a well-established single integrating sphere setup. A small part of the bias can be explained by the bias of the single sphere. Yet the observed bias is quite significant if absolute accuracy of measurements is required. For relative measurements, e.g. for monitoring development of needle spectra over time, the double sphere system provides notable improvement. Furthermore, it might be possible to reduce the bias by building an optimized measurement setup that minimizes absorption losses in the sample port. Our study indicates that double spheres, after some technical improvement, may provide a new and fast way to collect extensive spectral libraries of tree species.
PDF
