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Träfflista för sökning "WFRF:(Lange Holger) srt2:(2020-2022)"

Sökning: WFRF:(Lange Holger) > (2020-2022)

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1.
  • Ayyer, Kartik, et al. (författare)
  • 3D diffractive imaging of nanoparticle ensembles using an x-ray laser
  • 2021
  • Ingår i: Optica. - : Optical Society of America. - 2334-2536. ; 8:1, s. 15-23
  • Tidskriftsartikel (refereegranskat)abstract
    • Single particle imaging at x-ray free electron lasers (XFELs) has the potential to determine the structure and dynamics of single biomolecules at room temperature. Two major hurdles have prevented this potential from being reached, namely, the collection of sufficient high-quality diffraction patterns and robust computational purification to overcome structural heterogeneity. We report the breaking of both of these barriers using gold nanoparticle test samples, recording around 10 million diffraction patterns at the European XFEL and structurally and orientationally sorting the patterns to obtain better than 3-nm-resolution 3D reconstructions for each of four samples. With these new developments, integrating advancements in x-ray sources, fast-framing detectors, efficient sample delivery, and data analysis algorithms, we illuminate the path towards sub-nano meter biomolecular imaging. The methods developed here can also be extended to characterize ensembles that are inherently diverse to obtain their full structural landscape. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License.
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2.
  • Dox, Inge, et al. (författare)
  • Wood growth phenology and its relationship with leaf phenology in deciduous forest trees of the temperate zone of Western Europe
  • 2022
  • Ingår i: Agricultural and Forest Meteorology. - : Elsevier. - 0168-1923 .- 1873-2240. ; 327
  • Tidskriftsartikel (refereegranskat)abstract
    • Wood growth phenology of temperate deciduous trees is less studied than leaf phenology, hindering the understanding of their interaction. In order to describe the variability of wood growth and leaf phenology across locations, species and years, we performed phenological observations of both xylem formation and leaf development in three typical temperate forest areas in Western Europe (Northern Spain, Belgium and Southern Norway) for four common deciduous tree species (Fagus sylvatica L., Betula pendula Roth., Populus tremula L. and Quercus robur L.) in 2018, 2019 and 2020, with only beech and birch being studied in the final year. The earliest cambial reactivation in spring occurred at the Belgian stands while the end of cambial activity and wood growth cessation generally occurred first in Norway. Results did not show much consistency across species, sites or years and lacked general patterns, except for the end of cambial activity, which occurred generally first in birch. For all species, the site variation in phenophases (up to three months) was substantially larger than the inter-annual variability (up to six weeks). The timeline of bud-burst and cambium reactivation, as well as of foliar senescence and cessation of wood growth, were variable across species even with the same type of wood porosity. Our results suggest that wood growth and leaf phenology are less well connected than previously thought. Linear models showed that temperature is the dominant driver of wood growth phenology, but with climate zone also having an effect, especially at the start of the growing season. Drought conditions, on the other hand, have a larger effect on the timing of wood growth cessation. Our comprehensive analysis represents the first large regional assessment of wood growth phenology in common European deciduous tree species, providing not only new fundamental insights but also a unique dataset for future modelling applications.
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3.
  • George, Jan Peter, et al. (författare)
  • Method comparison of indirect assessments of understory leaf area index (LAIu) : A case study across the extended network of ICOS forest ecosystem sites in Europe
  • 2021
  • Ingår i: Ecological Indicators. - : Elsevier BV. - 1470-160X .- 1872-7034. ; 128
  • Tidskriftsartikel (refereegranskat)abstract
    • Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimates LAIu at sites with sparse understory vegetation and presence of litter or bare soil. The purely empirical method based on the Beer-Lambert law of light absorption seems to offer a good compromise, since it provides reasonable LAIu values at both low and higher LAI ranges. Surprisingly, LAIu variation among sites seems to be largely decoupled from differences in climate and light permeability of the overstory, but significantly increased with vegetation diversity (expressed as species richness) and hence proposes new applications of LAIu in ecological modelling.
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4.
  • Pisek, Jan, et al. (författare)
  • Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests
  • 2021
  • Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 18:2, s. 621-635
  • Tidskriftsartikel (refereegranskat)abstract
    • Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing.
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5.
  • Zhuang, Yulong, et al. (författare)
  • Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging
  • 2022
  • Ingår i: IUCrJ. - : International Union of Crystallography (IUCr). - 2052-2525. ; 9, s. 204-214
  • Tidskriftsartikel (refereegranskat)abstract
    • One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand-maximizecompress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.
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