Search

It is well known that forests serve as carbon sinks. However, the balancing effect of afforestation and increased forest density on global warming due to carbon storage may be lost by low albedo (thus high absorption) of the forests. In the last 30 years, there has been a steady increase in the growing stock of Finnish forests by nearly a quarter while the area of the forests has remained virtually unchanged. Such increase in forest density together with the availability of detailed forest inventories provided by the Multi-Source National Forest Inventory (MS-NFI) in high spatial resolution makes Finland an ideal candidate for exploring the effects of increased forest density on satellite derived estimates of bio-geochemical products e.g. albedo (directional-hemispherical reflectance, DHR), fraction of photosynthetically active radiation absorbed by canopies (fAPAR), leaf area index (LAI) and normalized difference vegetation index (NDVI) in both current and long-term perspective. In this study, we first used MODIS-based vegetation satellite products for Finnish forests to study their seasonal patterns and interrelations. Next, the peak growing season observations are linked to the MS-NFI database to yield the generic relationships between forest density and the satellite-derived vegetation indicators. Finally, long-term GIMMS3g datasets between 1982 and 2011 (2008 for DHR) are analyzed and interpreted using forest inventory data. The vegetation peak growing season NIR DHR and VIS DHR showed weak to moderate negative correlation with fAPAR, whereas there was no correlation between NIR DHR and fAPAR. Next, we show that the spectral albedos in the near-infrared region (NIR DHR) showed weak negative correlation with forest biomass, basal area or canopy cover whereas, as expected, the spectral albedo in the visible region (VIS DHR) correlated negatively with these measures of forest density. Interestingly, the increase in forest density (biomass per ha) of Finnish forests during the last 30 years was not accompanied by trends in the indicators of vegetation ‘greenness’ and photosynthetic productivity (fAPAR, LAI and NDVI) or in forest albedo (DHR). Even though there were small increases in both DHR, fAPAR, LAI and NDVI and from the start to the end of the study period (1982–2011), the pattern and magnitude of change in these variables did not follow the development of forest biomass in the different NFI inventories. [ABSTRACT FROM AUTHOR]

Abstract: A recent method based on the spectral invariants theory to retrieve physically-based information on forest properties from remotely sensed hyperspectral imagery was tested in a southern boreal setting in central Finland. An atmospherically corrected Hyperion image and ground measurements from 66 forest stands were used. First, the novel concept of transformed green leaf single scattering spectral albedos was tested against leaf (needle) albedo measurements on Scots pine, Norway spruce and Silver birch from the study area. We found the transformed Beaked hazel albedo applied in previous studies could be used as reference also for the boreal tree species. Second, we derived a newly suggested spectrally invariant variable, the directional area scattering factor (DASF), to estimate the broadleaf fraction of forest stands. Based on our results, DASF seems highly promising as a potential new hyperspectral satellite product for change monitoring of broadleaf fraction over different vegetation zones. Finally, we plotted our results in the spectral invariants space, and suggest a new interpretation for the reference-dependent structural parameter p R . We propose this parameter is an indicator of canopy cover and suffers less from saturation problems than vegetation indices. [Copyright &y& Elsevier]

Abstract: Medium resolution leaf area index (LAI) products have usually been validated only at the peak of the growing season for boreal forest areas. In this study, we evaluated seasonal variations in MODIS Collection 5 (C5) LAI products for an evergreen coniferous forest area in southern Finland. A time series of field measurements of LAI and nine fine resolution satellite images (SPOT4 HRVIR, EO-1 Hyperion) for the snow free period in 2010 were used for developing empirical regression models for LAI estimation. We used two different reference LAI: the first one corresponded to an effective overstory LAI, and the second one was a clumping-corrected LAI that included both over- and understory vegetation. According to the results, MODIS LAI retrievals were closer to the effective LAI in the spring and autumn, when saturation of MODIS LAI main algorithm did not occur. On the other hand, in the summer, when saturation occurred, MODIS LAI was closer to the total LAI. Therefore, as a result of high LAI retrieved under the condition of saturation, the seasonal course of LAI was exaggerated in comparison to the reference LAI time series. Furthermore, MODIS LAI retrievals were unrealistically small before the leaf burst if considering the large proportion of evergreen coniferous forest in the study area. The results emphasize the need for multi-seasonal validation data sets in order to better understand the performance of LAI retrieval algorithms for evergreen coniferous forests throughout the snow free period. [Copyright &y& Elsevier]

The Arctic region is predicted to experience considerable climatic and environmental changes as the global atmospheric CO2 increases. Growing awareness of the role of tundra and taiga ecosystems and their transition zone in the climate change process has resulted in a recent increase in remote sensing studies focusing on the Arctic latitudes. Remote sensing of biophysical properties of the canopy layer in the forested part of the region is often, however, challenged by the dominating role of the understory in the spectral signal. In this paper, we examine the influence of understory vegetation on forest reflectance in the Arctic region of Finland during no-snow conditions. The study is based on SPOT HRVIR images, field goniospectrometry, 300 ground reference plots and a physically-based forest reflectance model (PARAS). The results indicate that lichen-dominated forest site types can be distinguished from sites dominated by dwarf shrubs. The paper also contains results from applying an analytical method for calculating photon recollision probability from canopy transmittance data for forest stands, and then using it to simulate the reflectance of the same stands. [Copyright &y& Elsevier]

Abstract: Crown profiles of 260 Scots pines in central Finland were measured using a new method developed in the study, and a simple model for crown shape, belonging to the Lamé curve family, was derived using these data. Relatively accurate estimates of the crown maximum radius and its height, parameters needed for application of the model, were obtained using breast height diameter (dbh) and tree height. Results suggest that the model could potentially be used to generate the crown shape directly from routine stand data. [Copyright &y& Elsevier]

• Understory composition was the best correlated with structural forest canopy measures. • Tree canopy LAI and the fractional cover of understory were strongly related. 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. [ABSTRACT FROM AUTHOR]

• Understory spectra (350-2300 nm) and fractional cover from 36 boreal forest stands. • Spectral characteristics of understory linked to fractional cover and site fertility. • Spectra beyond the conventional VIS-NIR region may improve understory monitoring. Modern satellite and airborne optical images have increasingly higher resolutions and enable the study of all layers of forests, not just the forest canopy. To understand the contribution of different types of understory on the overall spectral reflectance signal, ground reference data are needed from different types of forests. In this paper, we present the analysis of spectral reflectance factors (350-2300 nm) and fractional covers of understory from 36 boreal forest stands. The data were collected during peak growing season in a southern boreal forest area in Finland. The study stands represent four different forest site fertility types. We used a spectrometer to measure understory spectra in nadir and vegetation quadrats to estimate fractional cover. We showed that the understory has specific spectral features related to the site fertility type and fractional cover. Our results suggest that remote sensing can be used to differentiate forest site fertility types and estimate understory green fractional cover in northern European boreal forests. The collected data are openly available in an open data repository. [Display omitted] [ABSTRACT FROM AUTHOR]

Clumping is critical for quantifying the radiation regime of forest canopies, but challenging to measure. We developed a method to measure clumping index (CI) of forest stands using voxel-based estimates of leaf area density from terrestrial lidar data. Our method uses the principle of the silhouette to total area ratio (STAR), a commonly used shoot clumping correction approach. We adapted the concept to forest stands, and derived that STAR at canopy scale (STAR f) is no longer simply a clumping index, but a summary variable for forest structure in general. CI can be calculated from STAR f when leaf area index is known. We measured CI and STAR f of 38 forest stands in Finland, Estonia, and Czechia to study the natural range of these variables, their relationships to other forest variables, and to Landsat 8 OLI surface reflectance. CI did not include clumping below voxel scale (20 cm), and ranged from 0.6 to 0.9, with the lowest values (i.e., the most clumped canopies) in conifer forests and temperate oak forests, and the highest CI values (i.e., the most random canopies) in boreal broadleaved forests. CI was closely correlated with surface reflectance in conifer forests, which may be explained by contradicting influence of clumping that decreases canopy reflectance, but increases visibility of the forest floor. From the viewpoint of forest reflectance modeling, STAR is a useful variable due to its close relationship with the photon recollision probability, i.e., the probability that a photon will interact with a canopy element after being scattered from another canopy element. The photon recollision probability is used to model the influence of forest structure on reflectance. Our method provides a physically-based means of measuring STAR f , and thus the photon recollision probability, hence contributing to the development of new methods for interpreting forest canopy structure from optical remote sensing data. • We quantified clumping in 38 forest stands comprising ∼ 2100 trees in Europe. • Clumping obtained from TLS data using the silhouette to total area ratio of stands. • Conifer and temperate floodplain forests had the highest degrees of clumping. • Clumping correlated with L8 OLI surface reflectance, especially in conifer forests. • Clumping at stand level is best measured by TLS, indirect estimates are insufficient. [ABSTRACT FROM AUTHOR]

Understanding the influence of forest structure on forest albedo, and thus on the energy exchange between the forest and the atmosphere, is urgently needed in areas with large forest cover and active forest management. Fine resolution albedo retrievals enable quantifying the relationships between forest variables and albedo also in patchy landscapes, such as in the managed forests in Fennoscandia. In this study, field plot data, airborne laser scanning (ALS) data and high resolution satellite albedo retrievals from Landsat were used to investigate the main factors influencing forest albedo in Central Finland in midsummer. Tree species, forest structure and understory (ground) vegetation composition all influenced forest albedo. The tree species-specific models were estimated on a subpixel scale by utilizing information on the proportions of each species within a plot. Tree species considerably improved the albedo prediction when added to a model containing only a structural variable, whereas a further addition of the site fertility class as a proxy of understory vegetation composition only slightly improved the model. Albedo decreased with increasing volume of growing stock, but the decrease leveled off at high volumes. The albedo of plots with high volume was instead mainly governed by tree species and was the lowest for Norway spruce, intermediate for Scots pine and highest for broadleaved species. Norway spruce albedo decreased almost linearly with increasing mean tree height. ALS-derived canopy cover explained fairly well the variation in albedo in the visible region, but the total shortwave albedo was better predicted by ALS-derived tree height. [ABSTRACT FROM AUTHOR]

Abstract: The spectral and directional reflection properties of pine forest understory in Suonenjoki, Finland were measured using a newly developed transportable field goniospectrometer under direct sunlight or plant lamp. The samples represent the most typical types in Finnish forests. Large differences between species were found. Wax-leaved shrubs such as lingonberry and blueberry proved to be strong forward scatterers, whereas lichen and soft-leaved dwarf shrubs such as heather were strong backscatterers. The measured moss showed both forward and backscattering features. There were variations among the samples of the same species, but many typical features appeared consistent and reproducible. Both “pure” and mixed samples were measured, the latter showing smoother behavior than the former, that is, the strongest forward and backward features are downscaled. The results provide a starting point for an empirical understory model and a basis for development and validation of a theoretical model. [Copyright &y& Elsevier]

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.