Occurrence of Dirofilaria repens in wild carnivores in Poland.

Dirofilaria repens is an expanding vector-borne zoonotic parasite of canines and other carnivores. Sub-clinically infected dogs constitute the most important reservoir of the parasite and the source of infection for its mosquito vectors. However, occurrence of D. repens infection in wild animals may contribute to the transmission of the parasite to humans and may explain the endemicity of filariae in newly invaded regions. The aim of the current study was to determine the occurrence of D. repens in 511 blood and spleen samples from seven species of wild carnivores (wolves, red foxes, Eurasian badgers, raccoons, raccoon dogs, stone martens, and pine martens) from different regions of Poland by means of a PCR protocol targeting the 12S rDNA gene. Dirofilaria repens–positive hosts were identified in seven of fourteen voivodeships in four of the seven regions of Poland: Masovia, Lesser Poland, Pomerania and Warmia-Masuria. The highest prevalence was found in Masovia region (8%), coinciding with the highest previously recorded prevalence in dogs in Central Poland. The DNA of Dirofilaria was detected in 16 samples of three species (total prevalence 3.13%). A low and similar percentage of positive samples (1.9%, 4.2% and 4.8%) was recorded among badgers, red foxes, and wolves, respectively. Dirofilaria repens–positive hosts were identified in seven of fourteen voivodships. Based on detection in different voivodeships, D. repens–positive animals were recorded in four out of the seven regions of Poland: in Masovia, Lesser Poland, Pomerania, and Warmia-Masuria. The highest prevalence of filariae was found in Masovia region (8%), reflecting the highest previously recorded prevalence in dogs (12–50%) in Central Poland. In summary, we conducted the first comprehensive study on the epidemiology of D. repens in seven species of wild hosts in all seven regions of Poland and identified the first case of D. repens infection in Eurasian badgers in Poland and the second in Europe

Neurological symptoms in hospitalised patients with COVID-19 and their association with in-hospital mortality

Objectives. To evaluate the spectrum of neurological symptoms in patients with COVID-19 during the first 14 days of hospitalisation and its association with in-hospital mortality. Material and methods. We included 200 patients with RT-PCR-confirmed COVID-19 admitted to University Hospital in Krakow, Poland. In 164 patients, a detailed questionnaire concerning neurological symptoms and signs was performed prospectively within 14 days of hospitalisation. In the remaining 36 patients, such questionnaires were completed retrospectively based on daily observations in the Department of Neurology. Results. During hospitalisation, 169 patients (84.5%) experienced neurological symptoms; the most common were: fatigue (62.5%), decreased mood (45.5%), myalgia (43.5%), and muscle weakness (42.5%). Patients who died during hospitalisation compared to the remainder were older (79 [70.5–88.5] vs. 63.5 [51–77] years, p = 0.001), and more often had decreased level of consciousness (50.0% vs. 9.3%, p < 0.001), delirium (33.3% vs. 4.4%, p < 0.001), arterial hypotension (50.0% vs. 19.6%, p = 0.005) or stroke during (18.8% vs. 3.3%, p = 0.026) or before hospitalisation (50.0% vs. 7.1, p < 0.001), whereas those who survived more often suffered from headache (42.1% vs. 0%, p = 0.012) or decreased mood (51.7% vs. 0%, p = 0.003). Conclusions. Most hospitalised patients with COVID-19 experience neurological symptoms. Decreased level of consciousness, delirium, arterial hypotension, and stroke during or before hospitalisation increase the risk of in-hospital mortality

Using geobia and data fusion approach for land use and land cover mapping

Land Use and Land Cover (LULC) maps play an important role in an environmental modelling, and for many years efforts have been made to improve and streamline the expensive mapping process. The aim of the study was to create LULC maps of three selected water catchment areas in South Poland using a Geographic Object-Based Image Analysis (GEOBIA) in order to highlight the advantages of this innovative, semi-automatic method of image analysis. The classifcation workfow included: multi-stage and multi-scale analyses based on a data fusion approach. Input data consisted mainly of BlackBridge (RapidEye) high resolution satellite imagery, although for distinguishing particular LULC classes, additional satellite images (LANDSAT TM5) and GIS-vector data were used. Accuracy as- sessment of GEOBIA classifcation results varied from 0.83 to 0.87 (Kappa), depending on the specifc catchment area. The main recognized advantages of GEOBIA in the case study were: performing of multi-stage and multi-scale image classifcation using different features for specifc LULC classes and the ability to using knowledge-based classifcation in conjunction with the data fusion approach in an effcient and reliable manner

The analysis of spatial and temporal changes of land cover and land use in the reclaimed areas with the application of airborne orthophotomaps and LANDSAT images

The aim of this study was to investigate the possible use of geoinformatics tools and generally available geodata for mapping land cover/use on the reclaimed areas. The choice of subject was dictated by the growing number of such areas and the related problem of their restoration. Modern technology, including GIS, photogrammetry and remote sensing are relevant in assessing the reclamation effects and monitoring of changes taking place on such sites. The LULC classes mapping, supported with thorough knowledge of the operator, is useful tool for the proper reclamation process evaluation

Geo-Questionnaire for Environmental Planning: The Case of Ecosystem Services Delivered by Trees in Poland

Studies on society and the environment interface are often based on simple questionnaires that do not allow for an in-depth analysis. Research conducted with geo-questionnaires is an increasingly common method. However, even if data collected via a geo-questionnaire are available, the shared databases provide limited information due to personal data protection. In the article, we present open databases that overcome those limitations. They are the result of the iTre-es project concerning public opinion on the benefits provided by trees and shrubs in four different research areas. The databases provide information on the location of trees that are valuable to the residents, the distances from the respondents’ residence place, their attitude toward tree removal, socio-demographic variables, attachment to the place of life, and environmental attitudes. The presentation of all these aspects was possible thanks to the appropriate aggregation of the results. A method to anonymize the respondents is presented. We discuss the collected data and their possible areas of application

Land cover mapping based on obia of RapidEye satellite data

Wraz z rozwojem teledetekcji i wysokorozdzielczych obrazów satelitarnych istotnym wyzwaniem dla współczesnych badań stało się zautomatyzowanie procesu klasyfikacji pozyskiwanych danych. Jedną z bardzo szybko rozwijających się metod automatycznej klasyfikacji jest analiza obiektowa obrazu (OBIA, ang. Object Based Image Analysis). Celem pracy było wykorzystanie metody OBIA w przygotowaniu aktualnej mapy pokrycia terenu będącej ważnym elementem dokumentacji niezbędnej dla studium uwarunkowań budowy nowej hydroelektrowni na środkowym odcinku Wisły. W pracy wykorzystano wysokorozdzielcze zobrazowania satelitarne RapidEye (5 kanałów spektralnych, w tym dwa w zakresie NIR) pokrywające obszar około 5.300 km2 oraz oprogramowanie eCognition (TRIMBLE Geospatial) a także warstwy informacyjne GIS. W wyniku przeprowadzonych analiz uzyskano mapę pokrycia terenu reprezentowaną przez 29 klas. Największą powierzchnię terenu badań zajmują obszary użytkowane rolniczo (59.5%, z czego 35.5% grunty orne) oraz lasy (29.1%, z czego 21.4% drzewostany iglaste), co świadczy o charakterze tej jednostki fizjograficznej. Analiza dokładności uzyskanych wyników wykazała, iż metoda OBIA daje bardzo dobre rezultaty (współczynnik Kappa równy 0.8) w daleko zautomatyzowanym procesie generowania aktualny map pokrycia terenu dla obszarów centralnej Polski na podstawie obrazów satelitarnych RapidEye.Parallel with the development of remote sensing and high resolution satellite images major challenge for modern research has become almost to automate the classification of the data obtained. One of the most rapidly developing methods for automatic classification is object-oriented image analysis (OBIA, Object Based Image Analysis). The aim of the present study was to use the OBIA method to create the current land cover map which is part of the documentation necessary for new water power-station on the middle part of Vistula river. In this paper the RapidEye satellite images (5 spectral bands, two in the NIR range) covering an area of about 5 300 km2 and eCognition Developer (TRIMBLE) software were used. As a result of the analysis and land cover map was obtained, represented by 29 classes. The largest area is covered by agricultural land (59.5%; arable land – 35.52%) and forests (29.1%; mainly coniferous 21.4%), reflecting the rural – forestry character of the area. Analysis of the accuracy of the obtained results has shown that the OBIA method gives quite good results (Kappa coefficient equal to 0.8) for land cover mapping of central part of Poland based on the RapidEye imageries