New Methodologies for Grasslands Monitoring

Monitoring grassland areas to assess changes in their condition over time has been the subject of a lot of research at different scales. Initially the techniques focused on field-based measurements, and modelling. However, several obtained data were site specific. Based on the increase in availability of remote sensing data and products, there is an expectation that remote sensing can provide rapid and definite answers to the challenges of detecting and monitoring grassland conditions and associated changes in productivity. At the time of European Copernicus Programme, the new possibilities of satellite data from the group of Sentinel satellites give the new perspective for grasslands monitoring. The Finegrass Polish – Norwegian Project have been set to detect the biomass and its changes for grasslands in Poland and Norway applying different approaches due to different specific of the area. The results have been verified by ground measurements

Tight versus standard blood pressure control on the incidence of myocardial infarction and stroke: an observational retrospective cohort study in the general ambulatory setting

BACKGROUND: The 2017 American College of Cardiology and American Heart Association guideline defined hypertension as blood pressure (BP) ≥ 130/80 mmHg compared to the traditional definition of ≥140/90 mmHg. This change raised much controversy. We conducted this study to compare the impact of tight (TBPC) versus standard BP control (SBPC) on the incidence of myocardial infarction (MI) and stroke. METHODS: We retrospectively identified all hypertensive patients in an ambulatory setting based on the diagnostic code for 1 year at our institution who were classified by the range of BP across 3 years into 2 groups of TBPC (\u3c 130 mmHg) and SBPC (130-139 mmHg). We compared the incidence of new MI and stroke between the 2 groups across a 2-year follow-up. Multivariate analysis was done to identify independent predictors for the incidence of new MI and stroke. RESULTS: Of 5640 study patients, the TBPC group showed significantly less incidence of stroke compared to the SBPC group (1.5% vs. 2.7%, P \u3c 0.010). No differences were found in MI incidence between the 2 groups (0.6% vs. 0.8%, P = 0.476). Multivariate analysis showed that increased age independently increased the incidence of both MI (OR 1.518, 95% CI 1.038-2.219) and stroke (OR 1.876, 95% CI 1.474-2.387), and TBPC independently decreased the incidence of stroke (OR 0.583, 95% CI 0.374-0.910) but not of MI. CONCLUSIONS: Our observational study suggests that TBPC may be beneficial in less stroke incidence compared to SBPC but it didn\u27t seem to affect the incidence of MI. Our study is limited by its retrospective design with potential confounders

Warsaw Argumentation Week (Waw 2018) Organised by the Polish School of Argumentation and Our Colleagues from Germany and the UK, 6th-16th September 2018

In September 2018, the ArgDiaP association, along with colleagues from Germany and the UK, organised one of the longest and most interdisciplinary series of events ever dedicated to argumentation - Warsaw Argumentation Week, WAW 2018. The eleven-day ‘week’ featured a five day graduate school on computational and linguistic perspectives on argumentation (3rd SSA school); five workshops: on systems and algorithms for formal argumentation (2nd SAFA), argumentation in relation to society (1st ArgSoc), philosophical approaches to argumentation (1st ArgPhil), legal argumentation (2ndMET-ARG) and argumentation in rhetoric (1st MET-RhET); and two conferences: on computational models of argumentation (7th COMMA conference) and on argumentation and corpus linguistics (16th ArgDiaP conference). WAW hosted twelve tutorials and eight invited talks as well as welcoming over 130 participants. All the conferences and workshops publish pre- or post-proceedings in the top journals and book series in the field

Assessment of Carbon Flux and Soil Moisture in Wetlands Applying Sentinel-1 Data

The objectives of the study were to determine the spatial rate of CO2 flux (Net Ecosystem Exchange) and soil moisture in a wetland ecosystem applying Sentinel-1 IW (Interferometric Wide) data of VH (Vertical Transmit/Horizontal Receive—cross polarization) and VV (Vertical Transmit/Vertical Receive—like polarization) polarization. In-situ measurements of carbon flux, soil moisture, and LAI (Leaf Area Index) were carried out over the Biebrza Wetland in north-eastern Poland. The impact of soil moisture and LAI on backscattering coefficient (σ°) calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when soil moisture is low. The models for soil moisture have been derived for wetland vegetation habitat types applying VH polarization (R2 = 0.70 to 0.76). The vegetation habitats: reeds, sedge-moss, sedges, grass-herbs, and grass were classified using combined one Landsat 8 OLI (Operational Land Imager) and three TerraSAR-X (TSX) ScanSAR VV data. The model for the assessment of Net Ecosystem Exchange (NEE) has been developed based on the assumption that soil moisture and biomass represented by LAI have an influence on it. The σ° VH and σ° VV describe soil moisture and LAI, and have been the input to the NEE model. The model, created for classified habitats, is as follows: NEE = f (σ° Sentinel-1 VH, σ° Sentinel-1 VV). Reasonably good predictions of NEE have been achieved for classified habitats (R2 = 0.51 to 0.58). The developed model has been used for mapping spatial and temporal distribution of NEE over Biebrza wetland habitat types. Eventually, emissions of CO2 to the atmosphere (NEE positive) has been noted when soil moisture (SM) and biomass were low. This study demonstrates the importance of the capability of Sentinel-1 microwave data to calculate soil moisture and estimate NEE with all-weather acquisition conditions, offering an important advantage for frequent wetlands monitoring

Soil Moisture in the Biebrza Wetlands Retrieved from Sentinel-1 Imagery

The objective of the study was to estimate soil moisture (SM) from Sentinel-1 (S-1) satellite images acquired over wetlands. The study was carried out during the years 2015⁻2017 in the Biebrza Wetlands, situated in north-eastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to SM retrieval for a broad range of vegetation and soil moisture conditions. The methodology is based on research into the effect of vegetation on backscatter (σ°) changes under different soil moisture and Normalized Difference Vegetation Index (NDVI) values. The NDVI was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. It was found that the state of the vegetation expressed by NDVI can be described by the indices such as the difference between σ° VH and VV, or the ratio of σ° VV/VH, as calculated from the Sentinel-1 images in the logarithmic domain. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the newly developed models using Water Cloud Model (WCM) that includes the derived indices based on S-1, allowed the estimation of SM for wetlands with reasonable accuracy (10 vol. %). The developed soil moisture retrieval algorithms based on S-1 data are suited for wetland ecosystems, where soil moisture values are several times higher than in agricultural areas

Monitoring Wetlands Ecosystems Using ALOS PALSAR (L-Band, HV) Supplemented by Optical Data: A Case Study of Biebrza Wetlands in Northeast Poland

The aim of the study was to elaborate the remote sensing methods for monitoring wetlands ecosystems. The investigation was carried out during the years 2002–2010 in the Biebrza Wetlands. The meteorological conditions at the test site varied from extremely dry to very wet. The authors propose applying satellite remote sensing data acquired in the optical and microwave spectrums to classify wetlands vegetation habitats for the assessment of vegetation changes and estimation of wetlands’ biophysical properties to improve monitoring of these unique, very often physically impenetrable, areas. The backscattering coefficients (σ°) calculated from ALOS PALSAR FBD (Advanced Land Observing Satellite, Phased Array type L-band Synthetic Aperture Radar, Fine Beam Dual Mode) images registered at cross polarization HV on 12 May 2008 were used to classify the main wetland communities using ground truth observations and the visual interpretation method. As a result, the σ° values were distributed among the six wetlands’ vegetation classes: scrubs, sedges-scrubs, sedges, reeds, sedges-reeds, rushes, and the areas of each community and changes were assessed. Also, the change in the biophysical variable as Leaf Area Index (LAI) is described using the information from PALSAR data. Strong linear relationships have been found between LAI and σ° derived for particular wetland classes, which then were applied to elaborate the maps of LAI distribution. The other variables used to characterize the changing environmental conditions are: surface temperature (Ts) calculated from NOAA AVHRR (National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer) and Normalized Difference Vegetation Index (NDVI) from ENVISAT MERIS (ENVIronmental SATellite MEdium Resolution Imaging Spectrometer). Differences of almost double Ts between “dry” and “wet” years were noticed that reflect observed weather conditions. The highest values of NDVI occurred in years with a sufficient amount of precipitation with the lowest in “dry” years. NDVI values variances within the same wetlands class resulted mainly from the differences in soil moisture. The results of this study show that the satellite data from microwave and optical spectrum gave the repetitive spatial information about vegetation growth conditions and could be used for monitoring wetland ecosystems