Vegetation indices are calculated from reflectance data of discrete spectral bands. The reflectance signal in the visible spectral range is dominated by the optical properties of photosynthetic pigments in plant leaves. Numerous spectral indices have been proposed for the estimation of leaf pigment contents, but the efficacy of different indices for prediction of pigment content and composition for species-rich communities is unknown. Assessing the ability of different vegetation indices to predict leaf pigment content we identify the most suitable spectral indices from an experimental dataset consisting of field-grown high light exposed leaves of 33 angiosperm species collected in two sites in Mallorca (Spain) with contrasting leaf anatomy and pigment composition. Leaf-level reflectance spectra were recorded over the wavelength range of 400 – 900 nm and contents of chlorophyll a, chlorophyll b, total carotenoids, and anthocyanins were measured in 33 species from different plant functional types, covering a wide range of leaf structures and pigment content, five-fold to more than 10-fold for different traits. The best spectral region for estimation of leaf total chlorophyll content with least interference from carotenoids and anthocyanins was the beginning of near-infrared plateau well beyond 700 nm. Leaves of parallel-veined monocots and pinnate-veined dicots had different relationships between vegetation indices and pigments. We suggest that the nature and role of “far-red” chlorophylls which absorb light at longer wavelengths than 700 nm constitute a promising target for future remote sensing studies.

This study present the results of airborne top-of-canopy measurements of reflectance spectra in the spectral domain of 350–1050 nm over the hemiboreal mixed forest. We investigated spectral transformations that were originally designed for utilization at very different spectral resolutions. We found that the estimates of red edge inflection point by two methods—the linear four-point interpolation approach (S2REP) and searching the maximum of the first derivative spectrum ( $D_{max}$ ) according to the mathematical definition of red edge inflection point—were well related to each other but S2REP produced a continuously shifting location of red edge inflection point while $D_{max}$ resulted in a discrete variable with peak jumps between fixed locations around 717 nm and 727 nm for forest canopy (the third maximum at 700 nm appeared only in clearcut areas). We found that, with medium high spectral resolution (bandwidth 10 nm, spectral step 3.3 nm), the in-filling of the O ${}_2$ -A Fraunhofer line ( $F_{area}$ ) was very strongly related to single band reflectance factor in NIR spectral region ( $\rho$ = 0.91, p < 0.001) and not related to Photochemical Reflectance Index (PRI). Stemwood volume, basal area and tree height of dominant layer were negatively correlated with reflectance factors at both visible and NIR spectral region due to the increase in roughness of canopy surface and the amount of shade. Forest age was best related to single band reflectance at NIR region ( $\rho$ = −0.48, p < 0.001) and the best predictor for allometric LAI was the single band reflectance at red spectral region ( $\rho$ = −0.52, p < 0.001) outperforming all studied vegetation indices. It suggests that Sentinel-2 MSI bands with higher spatial resolution (10 m pixel size) could be more beneficial than increased spectral resolution for monitoring forest LAI and age. The new index R ${}_{751}$ /R ${}_{736}$ originally developed for leaf chlorophyll content estimation, also performed well at the canopy level and was mainly influenced by the location of red edge inflection point ( $\rho$ = 0.99, p < 0.001) providing similar info in a simpler mathematical form and using a narrow spectral region very close to the O ${}_2$ -A Fraunhofer line.

The gap fractions of three mature hemi-boreal forest stands in Estonia were estimated using the LAI-2000 plant canopy analyzer ( LI-COR Biosciences, Lincoln, NE, USA), the TRAC instrument (Edgewall, Miami, FL, USA), Cajanus’ tube, hemispherical photos, as well as terrestrial (TLS) and airborne (ALS) laser scanners. ALS measurements with an 8-year interval confirmed that changes in the structure of mature forest stands are slow, and that measurements in the same season of different years should be well comparable. Gap fraction estimates varied considerably depending on the instruments and methods used. None of the methods considered for the estimation of gap fraction of forest canopies proved superior to others. The increasing spatial resolution of new ALS devices allows the canopy structure to be analyzed in more detail than was possible before. The high vertical resolution of point clouds improves the possibility of estimating the stand height, crown length, and clumping of foliage in the canopy. The clumping/regularity of the foliage in a forest canopy is correlated with tree height, crown length, and basal area. The method suggested herein for the estimation of foliage clumping allows the leaf area estimates of forest canopies to be improved.

The paper estimates equations for regional income convergence in selected EU countries and their NUTS 3 level regions during the European Union pre-enlargement period (1995-2002), using both spatial and non-spatial approaches. There has been absolute income convergence between regions in both the groups of countries looked at, the countries of the EU15, or the old member states, and the new member states or NMS. When national effects are included in convergence equations using country dummies, no evidence of regional income convergence can be observed. The results of the analysis assert the importance of regional policies in inhibiting the increase of regional income disparities and improving conditions for income growth, particularly within the new member states.

We examined the seasonal changes in biophysical, anatomical, and optical traits of young leaves, formed throughout the vegetative season due to sylleptic growth, and mature leaves formed by proleptic growth in spring. Leaf developmental categories contribute to the top-of-canopy reflectance and should be considered when taking ground truth for remote sensing studies (RS). Deciduous tree species, Betula pendula, Populus tremula, and Alnus incana, were sampled from May to October 2018 in an Estonian hemiboreal forest. Chlorophyll and carotenoid content were detected biochemically; leaf anatomical traits (leaf, palisade, and spongy mesophyll thickness) were measured on leaf cross-sections; leaf reflectance was measured by a spectroradiometer with an integrating sphere (350–2500 nm). Biophysical and anatomical leaf traits were related to 64 vegetation indices (VIs). Linear models based on VIs for all tested leaf traits were more robust if both juvenile and mature leaves were included. This study provides information on which VIs are interchangeable or independent. Pigment and leaf thickness sensitive indices formed PC1; water and structural trait related VIs formed an independent group associated with PC3. Type of growth and leaf age could affect the validation of biophysical and anatomical leaf trait retrieval from the optical signal. It is, therefore, necessary to sample both leaf developmental categories—young and mature—in RS, especially if sampling is only once within the vegetation season.

Clumping effect denotes the nonrandomness of foliage. It deviates from the random distribution assumption of Beer's law which is usually applied to leaf area index (LAI) retrieval from large-footprint full-waveform light detection and ranging (LiDAR). Some studies correct for large gaps-induced between-crown clumping, yet ignore the within-crown clumping. The error of LAI caused by these clumping effects and the influence of the forest structure parameters on them have not been quantitatively studied. This study quantified the between-crown, within-crown, and total clumping indices through a theoretical derivation, clarifying the mechanism of clumping; we used airborne LiDAR point clouds data in 11 290 footprints (diameter = 25 m) to estimate these indices in real forests. We found that: 1) the underestimation of LAI caused by directly applying Beer's law could be up to 93%, and it decreases with fractional crown coverage but increases with crown length and leaf area density; 2) the method of correcting between-crown clumping improves LAI retrieval for cylindrical canopies effectively; however, 3) considerable underestimation (up to 58%) exists if we neglect the within-crown clumping for other canopies, which has not been realized before; and 4) both the between-crown and the within-crown clumping can be the dominant contributor, and the within-crown clumping was greater than the between-crown clumping in 47% of the studied footprints. In the two physically based LAI retrieval methods, Beer's law has been commonly used due to its simplicity. Pathways to improve future LAI retrieval would be instrument improvement to capture the between-crown gaps and method study to correct the within-crown clumping further.