Interlaboratory comparison of sample preparation methods, database expansions, and cutoff values for identification of yeasts by matrix-assisted laser desorption ionization-time of flight mass spectrometry using a yeast test panel

An interlaboratory study using matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) to determine the identification of clinically important yeasts (n35) was performed at 11 clinical centers, one company, and one reference center using the Bruker Daltonics MALDI Biotyper system. The optimal cutoff for the MALDI-TOF MS score was investigated using receiver operating characteristic (ROC) curve analyses. The percentages of correct identifications were compared for different sample preparation methods and different databases. Logistic regression analysis was performed to analyze the association between the number of spectra in the database and the percentage of strains that were correctly identified. A total of 5,460 MALDI-TOF MS results were obtained. Using all results, the area under the ROC curve was 0.95 (95% confidence interval [CI], 0.94 to 0.96). With a sensitivity of 0.84 and a specificity of 0.97, a cutoff value of 1.7 was considered optimal. The overall percentage of correct identifications (formic acid-ethanol extraction method, score>1.7) was 61.5% when the commercial Bruker Daltonics database (BDAL) was used, and it increased to 86.8% by using an extended BDAL supplemented with a Centraalbureau voor Schimmelcultures (CBS)-KNAW Fungal Biodiversity Centre in-house database (BDALCBS in-house). A greater number of main spectra (MSP) in the database was associated with a higher percentage of correct identifications (odds ratio [OR], 1.10; 95% CI, 1.05 to 1.15; P<0.01). The results from the direct transfer method ranged from 0% to 82.9% correct identifications, with the results of the top four centers ranging from 71.4% to 82.9% correct identifications. This study supports the use of a cutoff value of 1.7 for the identification of yeasts using MALDI-TOF MS. The inclusion of enough isolates of the same species in the database can enhance the proportion of correctly identified strains. Further optimization of the preparation methods, especially of the direct transfer method, may contribute to improved diagnosis of yeast-related infections

Folic Acid Exposure Rescues Spina Bifida Aperta Phenotypes in Human Induced Pluripotent Stem Cell Model

Neural tube defects (NTDs) are severe congenital abnormalities, caused by failed closure of neural tube during early embryonic development. Periconceptional folic acid (FA) supplementation greatly reduces the risk of NTDs. However, the molecular mechanisms behind NTDs and the preventive role of FA remain unclear. Here, we use human induced pluripotent stem cells (iPSCs) derived from fetuses with spina bifida aperta (SBA) to study the pathophysiology of NTDs and explore the effects of FA exposure. We report that FA exposure in SBA model is necessary for the proper formation and maturation of neural tube structures and robust differentiation of mesodermal derivatives. Additionally, we show that the folate antagonist methotrexate dramatically affects the formation of neural tube structures and FA partially reverts this aberrant phenotype. In conclusion, we present a novel model for human NTDs and provide evidence that it is a powerful tool to investigate the molecular mechanisms underlying NTDs, test drugs for therapeutic approaches

Coupled, Physics-Based Modeling Reveals Earthquake Displacements are Critical to the 2018 Palu, Sulawesi Tsunami

The September 2018, Mw 7.5 Sulawesi earthquake occurring on the Palu-Koro strike-slip fault system was followed by an unexpected localized tsunami. We show that direct earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay. To this end, we use a physics-based, coupled earthquake–tsunami modeling framework tightly constrained by observations. The model combines rupture dynamics, seismic wave propagation, tsunami propagation and inundation. The earthquake scenario, featuring sustained supershear rupture propagation, matches key observed earthquake characteristics, including the moment magnitude, rupture duration, fault plane solution, teleseismic waveforms and inferred horizontal ground displacements. The remote stress regime reflecting regional transtension applied in the model produces a combination of up to 6 m left-lateral slip and up to 2 m normal slip on the straight fault segment dipping 65∘ East beneath Palu Bay. The time-dependent, 3D seafloor displacements are translated into bathymetry perturbations with a mean vertical offset of 1.5 m across the submarine fault segment. This sources a tsunami with wave amplitudes and periods that match those measured at the Pantoloan wave gauge and inundation that reproduces observations from field surveys. We conclude that a source related to earthquake displacements is probable and that landsliding may not have been the primary source of the tsunami. These results have important implications for submarine strike-slip fault systems worldwide. Physics-based modeling offers rapid response specifically in tectonic settings that are currently underrepresented in operational tsunami hazard assessment

Intraneuronal Aβ immunoreactivity is not a predictor of brain amyloidosis-β or neurofibrillary degeneration

Amyloid β (Aβ) immunoreactivity in neurons was examined in brains of 32 control subjects, 31 people with Down syndrome, and 36 patients with sporadic Alzheimer’s disease to determine if intraneuronal Aβ immunoreactivity is an early manifestation of Alzheimer-type pathology leading to fibrillar plaque formation and/or neurofibrillary degeneration. The appearance of Aβ immunoreactivity in neurons in infants and stable neuron-type specific Aβ immunoreactivity in a majority of brain structures during late childhood, adulthood, and normal aging does not support this hypothesis. The absence or detection of only traces of reaction with antibodies against 4–13 aa and 8–17 aa of Aβ in neurons indicated that intraneuronal Aβ was mainly a product of α- and γ-secretases (Aβ(17–40/42)). The presence of N-terminally truncated Aβ(17–40) and Aβ(17–42) in the control brains was confirmed by Western blotting and the identity of Aβ(17–40) was confirmed by mass spectrometry. The prevalence of products of α- and γ -secretases in neurons and β- and γ-secretases in plaques argues against major contribution of Aβ-immunopositive material detected in neuronal soma to amyloid deposit in plaques. The strongest intraneuronal Aβ(17–42) immunoreactivity was observed in structures with low susceptibility to fibrillar Aβ deposition, neurofibrillary degeneration, and neuronal loss compared to areas more vulnerable to Alzheimer-type pathology. These observations indicate that the intraneuronal Aβ immunoreactivity detected in this study is not a predictor of brain amyloidosis or neurofibrillary degeneration. The constant level of Aβ immunoreactivity in structures free from neuronal pathology during essentially the entire life span suggests that intraneuronal amino-terminally truncated Aβ represents a product of normal neuronal metabolism

Abnormal Intracellular Accumulation and Extracellular Aβ Deposition in Idiopathic and Dup15q11.2-q13 Autism Spectrum Disorders

<div><h3>Background</h3><p>It has been shown that amyloid ß (Aβ), a product of proteolytic cleavage of the amyloid β precursor protein (APP), accumulates in neuronal cytoplasm in non-affected individuals in a cell type–specific amount.</p> <h3>Methodology/Principal Findings</h3><p>In the present study, we found that the percentage of amyloid-positive neurons increases in subjects diagnosed with idiopathic autism and subjects diagnosed with duplication 15q11.2-q13 (dup15) and autism spectrum disorder (ASD). In spite of interindividual differences within each examined group, levels of intraneuronal Aβ load were significantly greater in the dup(15) autism group than in either the control or the idiopathic autism group in 11 of 12 examined regions (p<0.0001 for all comparisons; Kruskall-Wallis test). In eight regions, intraneuronal Aβ load differed significantly between idiopathic autism and control groups (p<0.0001). The intraneuronal Aβ was mainly N-terminally truncated. Increased intraneuronal accumulation of Aβ_17–40/42 in children and adults suggests a life-long enhancement of APP processing with α-secretase in autistic subjects. Aβ accumulation in neuronal endosomes, autophagic vacuoles, Lamp1-positive lysosomes and lipofuscin, as revealed by confocal microscopy, indicates that products of enhanced α-secretase processing accumulate in organelles involved in proteolysis and storage of metabolic remnants. Diffuse plaques containing Aβ_1–40/42 detected in three subjects with ASD, 39 to 52 years of age, suggest that there is an age-associated risk of alterations of APP processing with an intraneuronal accumulation of a short form of Aβ and an extracellular deposition of full-length Aβ in nonfibrillar plaques.</p> <h3>Conclusions/Significance</h3><p>The higher prevalence of excessive Aβ accumulation in neurons in individuals with early onset of intractable seizures, and with a high risk of sudden unexpected death in epilepsy in autistic subjects with dup(15) compared to subjects with idiopathic ASD, supports the concept of mechanistic and functional links between autism, epilepsy and alterations of APP processing leading to neuronal and astrocytic Aβ accumulation and diffuse plaque formation.</p> </div

Fungal Planet description sheets: 1478-1549

Novel species of fungi described in this study include those from various countries as follows: Australia, Aschersonia mackerrasiae on whitefly, Cladosporium corticola on bark of Melaleuca quinquenervia, Penicillium nudgee from soil under Melaleuca quinquenervia, Pseudocercospora blackwoodiae on leaf spot of Persoonia falcata, and Pseudocercospora dalyelliae on leaf spot of Senna alata. Bolivia, Aspicilia lutzoniana on fully submersed siliceous schist in high-mountain streams, and Niesslia parviseta on the lower part and apothecial discs of Erioderma barbellatum onatwig. Brazil, Cyathus bonsai on decaying wood, Geastrum albofibrosum from moist soil with leaf litter, Laetiporus pratigiensis on a trunk of a living unknown hardwood tree species, and Scytalidium synnematicum on dead twigs of unidentified plant. Bulgaria, Amanita abscondita on sandy soil in a plantation of Quercus suber. Canada, Penicillium acericola on dead bark of Acer saccharum, and Penicillium corticola on dead bark of Acer saccharum. China, Colletotrichum qingyuanense on fruit lesion of Capsicum annuum. Denmark, Helminthosphaeria leptospora on corticioid Neohypochnicium cremicolor. Ecuador (Galapagos), Phaeosphaeria scalesiae on Scalesia sp. Finland, Inocybe jacobssonii on calcareouss oils in dry forests and park habitats. France, Cortinarius rufomyrrheus on sandy soil under Pinus pinaster, and Periconia neominutissima on leaves of Poaceae. India, Coprinopsis fragilis on decaying bark of logs, Filoboletus keralensis on unidentified woody substrate, Penicillium sankaranii from soil, Physisporinus tamilnaduensis on the trunk of Azadirachta indica, and Poronia nagaraholensis on elephant dung. Iran, Neosetophoma fic on infected leaves of Ficus elastica. Israel, Cnidariophoma eilatica (incl. Cnidariophoma gen. nov.) from Stylophora pistillata. Italy, Lyophyllum obscurum on acidic soil. Namibia, Aureobasidium faidherbiae on dead leaf of Faidherbia albida, and Aureobasidium welwitschiae on dead leaves of Welwitschia mirabilis. Netherlands, Gaeumannomycella caricigena on dead culms of Carex elongata, Houtenomyces caricicola (incl. Houtenomyces gen. nov.) on culms of Carex disticha, Neodacampia ulmea (incl. Neodacampia gen. nov.) on branch of Ulmus laevis, Niesslia phragmiticola on dead standing culms of Phragmites australis, Pseudopyricularia caricicola on culms of Carex disticha, and Rhodoveronaea nieuwwulvenica on dead bamboo sticks. Norway, Arrhenia similis half-buried and moss-covered pieces of rotting wood in grass-grownpath. Pakistan, Mallocybe ahmadii on soil. Poland, Beskidomyces laricis (incl. Beskidomyces gen. nov.) from resin of Larix decidua ssp. polonica, Lapidomyces epipinicola from sooty mould community on Pinus nigra, and Leptographium granulatum from a gallery of Dendroctonus micans on Picea abies. Portugal, Geoglossum azoricum on mossy areas of laurel forest areas planted with Cryptomeria japonica, and Lunasporangiospora lusitanica from a biofilm covering a bio deteriorated limestone wall. Qatar, Alternaria halotolerans from hypersaline sea water, and Alternaria qatarensis from water sample collected from hypersaline lagoon. South Africa, Alfaria thamnochorti on culm of Thamnochortus fraternus, Knufia aloeicola on Aloe gariepensis, Muriseptatomyces restionacearum (incl.Muriseptatomyces gen. nov.) on culms of Restionaceae, Neocladosporium arctotis on nest of cases of bagworm moths(Lepidoptera, Psychidae) on Arctotis auriculata, Neodevriesia scadoxi on leaves of Scadoxus puniceus, Paraloratospora schoenoplecti on stems of Schoenoplectus lacustris, Tulasnella epidendrea from the roots of Epidendrum × obrienianum, and Xenoidriella cinnamomi (incl. Xenoidriella gen. nov.) on leaf of Cinnamomum camphora. South Korea, Lemonniera fraxinea on decaying leaves of Fraxinus sp. frompond. Spain, Atheniella lauri on the bark of fallen trees of Laurus nobilis, Halocryptovalsa endophytica from surface-sterilised, asymptomatic roots of Salicornia patula, Inocybe amygdaliolens on soil in mixed forest, Inocybe pityusarum on calcareous soil in mixed forest, Inocybe roseobulbipes on acidic soils, Neonectria borealis from roots of Vitis berlandieri × Vitis rupestris, Sympoventuria eucalyptorum on leaves of Eucalyptus sp., and Tuber conchae fromsoil. Sweden, Inocybe bidumensis on calcareous soil. Thailand, Cordyceps sandindaengensis on Lepidoptera pupa, buried in soil, Ophiocordyceps kuchinaraiensis on Coleoptera larva, buried in soil, and Samsoniella winandae on Lepidoptera pupa, buriedinsoil. Taiwan region (China), Neophaeosphaeria livistonae on dead leaf of Livistona rotundifolia. Türkiye, Melanogaster anatolicus on clay loamy soils. UK, Basingstokeomyces allii (incl. Basingstokeomyces gen. nov.) on leaves of Allium schoenoprasum. Ukraine, Xenosphaeropsis corni on recently dead stem of Cornus alba. USA, Nothotrichosporon aquaticum (incl. Nothotrichosporon gen. nov.) from water, and Periconia philadelphiana from swab of coil surface. Morphological and culture characteristics for these new taxa are supported by DNA barcodes.The work of P.W. Crous and colleagues benefitted from funding by the European Union’s Horizon 2020 research and innovation program (RISE) under the Marie Skłodowska-Curie grant agreement No. 101008129, project acronym ‘Mycobiomics’, and the Dutch NWO Roadmap grant agreement No. 2020/ENW/00901156, project ‘Netherlands Infrastructure for Ecosystem and Biodiversity Analysis – Authoritative and Rapid Identification System for Essential biodiversity information’(acronym NIEBAARISE). G. Gulden, B. Rian and I. Saar thank K. Bendiksen at the fungarium and G. Marthinsen at NorBol, both Natural History Museum, University of Oslo for valuable help with the collections, and the sequencing of our finds of A. similis from 2022. Sincere thanks to A. Voitk for assistance with the colour plate and review of the manuscript. I. Saar was supported by the Estonian Research Council (grant PRG1170). P. Rodriguez-Flakus and co-authors are greatly indebted to their colleagues and all staff of the Herbario Nacional de Bolivia, Instituto de Ecología, Universidad Mayor de SanAndrés, La Paz, for their generous long-term cooperation. Their research was financially supported by the National Science Centre (NCN) in Poland (grants numbers 2018/02/X/NZ8/02362 and 2021/43/B/NZ8/02902). Y.P. Tan and colleagues thank M.K. Schutze (Department of Agriculture and Fisheries, Queensland, Australia) for determining the identity of the insect hosts for Aschersonia mackerrasiae. The Australian Biological Resources Study funded the project that led to the discovery of Aschersonia mackerrasiae. K.G.G. Ganga acknowledges support from the University Grants Commission (UGC), India, in the form of a UGC research fellowship (Ref No. 20/12/2015(ii) EU-V), and the authorities of the University of Calicut for providing facilities to conduct this study. S. Mahadevakumar acknowledges the Director, KSCSTE - Kerala Forest Research Institute and Head of Office, Botanical Survey of India,Andaman and Nicobar Regional Centre, Port Blair for the necessary support and M. Madappa, Department of Studies in Botany, University of Mysore for technical assistance. A.R. Podile thanks the Department of Science and Technology, Govt. of India for the JC Bose Fellowship (Grant No. JCB/2017/000053) & MoE and IOE-Directorate-UOH for project (Grant No.UOH-IOE-RC3-21-065). Financial support was provided to R. de L. Oliveira and K.D. Barbosa by the Coordenação deAperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) – Finance code 001, and to I.G. Baseia and M.P. Martín by the National Council for Scientific and Technological Development (CNPq) under CNPq-Universal 2016 (409960/2016-0) and CNPq-visiting researcher (407474/2013-7). E. Larsson acknowledges the Swedish Taxonomy Initiative, SLU Artdatabanken, Uppsala, Sweden. H.Y. Mun and J. Goh were supported by a grant from the Nakdonggang National Institute of Biological Resources (NNIBR), funded by the Ministry of Environment (MOE) of the Republic of Korea (NNIBR202301106). J. Trovão and colleagues were financed by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), and by Portuguese funds through FCT- Fundação para a Ciência e a Tecnologia in the framework of the project POCI-01-0145-FEDER-PTDC/EPH-PAT/3345/ 2014. Their research was carried out at the R & D Unit Centre for Functional Ecology – Science for People and the Planet (CFE), with reference UIDB/04004/2020, financed by FCT/MCTES through national funds (PIDDAC). João Trovão was supported by POCH - Programa Operacional Capital Humano (co-funding by the European Social Fund and national funding by MCTES), through a ‘FCT- Fundação para a Ciência e Tecnologia’ PhD research grant (SFRH/ BD/132523/2017). O. Kaygusuz and colleagues thank the Research Fund of the Isparta University ofApplied Sciences for their financial support under the project number 2021-ILK1-0155. They also thank N. Sánchez Biezma of the Department of Drawing and Scientific Photography at the Alcalá University for his help in the digital preparation of the photographs. The research of M. Spetik and co-authors was supported by project No. IGAZF/2021-SI1003. V. Darmostuk and colleagues acknowledge our colleagues and all staff of the Herbario Nacional de Bolivia, Instituto de Ecología, Universidad Mayor de San Andrés, La Paz, for their generous long-term cooperation. They would also like to thank the SERNAP (http://sernap.gob.bo), and all protected areas staff, for providing permits for scientific studies, as well as their assistance and logistical support during the field works. This research was financially supported by the National Science Centre (NCN) in Poland (grant number DEC-2013/11/D/NZ8/ 03274). M. Kaliyaperumal and co-authors thank the Centre of Advanced Studies in Botany, University of Madras for the laboratory facilities. M. Kaliyaperumal thanks the Extramural Research-SERB, DST (EMR/2016/003078), Government of India, for financial assistance. M. Kaliyaperumal and K. Kezo thanks RUSA 2.0 (Theme-1, Group-1/2021/49) for providing a grant. M. Shivannegowda and colleagues thank C.R. Santhosh, Department of Studies in Microbiology, University of Mysore, Manasagangotri, Mysuru for technical support. They also thank K.R. Sridhar, Mangalore University, Karnataka, India and S.S.N. Maharachchikumbura, University of Electronic Science and Technology of China, Chengdu for their support and helping with technical inputs. The study of G.G. Barreto and co-authors was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES - Finance Code 001), and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - Proc. 131503/2019-7; Proc. 312984/2018-9); the authors also thank to Programa de Pós-Graduação em Botânica – PPGBOT. L.F.P. Gusmão thanks to Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for a research grant. T. Nkomo and colleagues thank the National Research Foundation of SouthAfrica for funding this study, with additional funding from the Forestry and Agricultural Biotechnology Institute and the University of Pretoria. G. Delgado is grateful to W. Colbert and S. Ward (Eurofins Built Environment) for continual encouragement and provision of laboratory facilities. J.G. Maciá-Vicente acknowledges support from the Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz (LOEWE) of the state of Hesse within the framework of the Cluster for Integrative Fungal Research (IPF) of Goethe University Frankfurt. F. Esteve-Raventós and colleagues acknowledge P. Juste and J.C. Campos for the loan of some collections for study and N. Subervielle and L. Hugot (Conservatoire Botanique National de Corse, Office de l’Environnement de la Corse, Corti) for their assistance. They also acknowledge the Balearic Mycology Group (FCB) for their permanent help in the search for collections in the Balearic Islands, and Y. Turégano for obtaining some of the sequences presented here, and L. Parra for his suggestions and help on nomenclatural issues. S. Mongkolsamrit and colleagues were financially supported by the Platform Technology Management Section, National Centre for Genetic Engineering and Biotechnology (BIOTEC), Project Grant No. P19-50231. S. De la Peña-Lastra and colleagues thank the Atlantic Islands National Maritime-Terrestrial Park authorities and guards. A. Mateos and co-authors would like to thank Secretaria Regional doAmbiente eAlterações Climáticas Açores for the permission granted for the sampling (Licença nº 16/2021/ DRAAC). To the ECOTOX group for co-funding the trip. J. Mack & D.P. Overy were funded byAgriculture &Agri-Food Canada (Project ID#002272: Fungal and Bacterial Biosystematics-bridging taxonomy and “omics” technology in agricultural research and regulation) and are grateful for molecular sequencing support from the Molecular Technologies Laboratory (MTL) at the Ottawa Research & Development Centre of Agriculture & Agri-Food Canada. The study of P. Czachura was funded by the National Science Centre, Poland, under the project 2019/35/N/NZ9/04173. The study of M. Piątek and coauthors was funded by the National Science Centre, Poland, under the project 2017/27/B/NZ9/02902. O. Yarden and L. Granit were funded by the Israel Science Foundation (grant number 888/19). H. Taşkın and colleagues received support from the BulgarianAcademy of Sciences and the Scientific and Technological Research Council of Türkiye (Bilateral grant agreement between BAS and TÜBİTAK, project number 118Z640). The authors would also like to thank S. Şahin (İzmir, Türkiye) for conveying one of the localities of A. abscondita. Andrew Miller would like to thank the Roy J. Carver Biotechnology Center at the University of Illinois for Sanger sequencing. E.R. Osieck thanks Staatsbosbeheer for permission to collect fungi in Nieuw Wulven, in the Netherlands. P. van ‘t Hof and co-authors thank the Galapagos Genetic Barcode project supported by UK Research and Innovation, Global Challenges Research Fund, Newton Fund, University of Exeter, Galapagos Science Center, Universidad San Francisco de Quito, Galapagos Conservation Trust, and Biosecurity Agency of Galapagos (ABG).Peer reviewe

Terrestrial photography as possible data source for geographic information systems

Praca przedstawia metodę pozwalającą na wykorzystanie pojedynczej fotografii naziemnej o nieznanych elementach orientacji wewnętrznej i zewnętrznej, jako źródła informacji geograficznej. Idea oparta jest na tworzeniu ortofotomapy ze zdjęć naziemnych, za pomocą zasad obowiązujących w fotogrametrii i widzeniu komputerowym. Danymi wejściowymi są: obraz cyfrowy, fotopunkty oraz numeryczny model terenu w formacie rastrowym. Fotopunkty służą do określenia orientacji kamery poprzez bezpośrednią transformację liniową (Direct Linear Transformation). Wykorzystanie niemetrycznej kamery wymaga użycia dużej liczby fotopunktów, aby można było osiągnąć zadowalającą dokładność. Kolejnym etapem jest eliminacja niewidocznych z danej pozycji fragmentów terenu, do czego wykorzystano analizę widoczności (viewshed). Ostatnim etapem jest ortorektyfikacja zdjęcia przy użyciu widocznych punktów modelu terenu. Produktem powstałym w wyniku działania procedury jest ortoobraz w przyjętym układzie odniesienia przestrzennego. Kompletny algorytm został napisany w języku MATLAB. Metodę przetestowano na współczesnych zdjęciach cyfrowych wykonanych niemetryczną lustrzanką cyfrową Nikon D80, wyposażoną w obiektyw Nikon Nikkor 28–80 mm f/3.3–5.6, a także na archiwalnych pocztówkach z lat 1928–1930. Przedmiotem fotografii w przypadku obu zbiorów danych były Tatry Polskie. Porównanie efektów z tradycyjną ortofotomapą dało zadowalające rezultaty, szczególnie dla obszarów silnie zacienionych.The paper describes a method, that allows to use a single terrestrial photograph, with unknown exterior and interior orientation parameters, as a source of geographic information. The idea is based on creating the orthoimage from a terrestrial photograph by means of photogrammetric and computer vision rules. The inputs are a digital image, Ground Control Points and a digital elevation model in raster format. GCPs are necessary to determine the camera orientation by means of Direct Linear Transformation. For non-calibrated cameras a large number of GCPs is necessary to obtain more accurate results. The next step is to eliminate invisible parts of terrain by applying the viewshed analysis. Finally, the terrestrial photograph is orthorectified using the extracted part of the digital elevation model. Output from this procedure is a georeferenced orthophotograph. The complete, ready to use algorithm is written in MATLAB. The method was tested using present-day digital images taken with a not-calibrated Nikon D80 and old postcards – both from the Polish Tatra Mountains. Comparison with an existing orthophotomap from aerial imagery gave satisfactory results, especially for deeply shaded areas

Determination of snow depth using terrestrial photogrammetric images

Określanie grubości pokrywy śnieżnej w terenie górskim ma duże znaczenie dla modelowania zagrożenia lawinowego, a także w analizach przyrodniczych, m.in. hydrologicznych. W niniejszym artykule przedstawiono prace mające na celu ocenę możliwości automatycznego generowania chmur punktów na podstawie naziemnych zdjęć fotogrametrycznych stoków górskich pokrytych śniegiem, w celu określenia przestrzennego rozkładu grubości pokrywy śnieżnej. Obszar badań znajduje się w Dolinie Pięciu Stawów Polskich w Tatrach Wysokich, na stokach pomiędzy Gładką Przełęczą a Walentkowym Wierchem. Zdjęcia wykonano w sezonie zimowym, przy zalegającej pokrywie śnieżnej, a następnie powtórzono w sezonie letnim. W tym celu wykorzystano lustrzankę cyfrową Nikon D5100 z obiektywem stałoogniskowym 85 mm, wyposażoną w matrycę 16 Mpix. Na podstawie zdjęć w programie PhotoModeler Scanner wygenerowane zostały automatycznie chmury punktów reprezentujące odpowiednio powierzchnię śniegu i powierzchnię terenu. Chmury poddano triangulacji, przy czym chmura pochodząca ze zdjęć wykonanych w porze letniej posłużyła do budowy referencyjnej powierzchni terenu, i do niej odniesiono wysokości powierzchni utworzonej z chmury punktów wygenerowanej ze zdjęć wykonanych zimą. Różnice wysokości pomiędzy nimi stanowiły miarę grubości pokrywy śnieżnej. Na badanym obszarze maksymalna grubość pokrywy śnieżnej wynosiła 8.7 m, a średnia grubość była równa 2.9 m Uzyskane wyniki pozwalają twierdzić, że naziemna fotogrametria cyfrowa może stanowić skuteczną metodę pozyskiwania informacji o grubości pokrywy śnieżnej dla niewielkich obszarów obejmujących górskie stoki i zbocza dolin.Determination of snow cover depth in mountainous terrain is of major importance for avalanche monitoring systems. Besides it is needed as an input information for environmental analysis, especially in hydrology. The aim of researches addressed in this paper was to evaluate the feasibility of using terrestrial photogrammetric images of mountain slopes for point cloud generation for snow cover mapping. The test area was located in the Pięć Stawów Valley in High Tatra in Poland. The image acquisition was carried out for slopes between Gładka Pass and Walentkowy Wierch. The first set of images was acquired during the winter season, when the deep snow cover reaches its highest annual values. Subsequently the second set of images was taken in summer, after the snow cover melted. The terrestrial image network was formed from all the images. The bundle adjustment was calculated and the winter and summer point clouds were generated using the dense matching algorithm. The mesh was built using the adjusted summer images. Created mesh was treated as a reference surface for measuring height of winter points. Calculated heights were used as a measures of snow depth. For some parts of test area the automatic generation of point clouds failed due to lowcontrast snow texture. In the rest of the test area the calculated snow depth is highest for the concave terrain formations. The results show that the terrestrial photogrammetry may by an attractive approach for acquiring the information about the snow depth distribution at small areas comprising slopes of mountains and valleys

MAPPING SECONDARY FOREST SUCCESSION ON ABANDONED AGRICULTURAL LAND IN THE POLISH CARPATHIANS

Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling