Digital Elevation Models: Terminology and Definitions

Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record the interface between the atmosphere and the lithosphere using a discrete two-dimensional grid, with complexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere. The treatment of DEM surfaces, affected by these intervening spheres, depends on their intended use, and the characteristics of the sensors that were used to create them. DEM is a general term, and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) record the treatment of the intermediate surfaces. Several global DEMs generated with optical (visible and near-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars and products of satellite altimetry, share the common characteristic of a georectified, gridded storage structure. Nevertheless, not all DEMs share the same vertical datum, not all use the same convention for the area on the ground represented by each pixel in the DEM, and some of them have variable data spacings depending on the latitude. This paper highlights the importance of knowing, understanding and reflecting on the sensor and DEM characteristics and consolidates terminology and definitions of key concepts to facilitate a common understanding among the growing community of DEM users, who do not necessarily share the same backgroun

A Path Toward the Use of Trail Users’ Tweets to Assess Effectiveness of the Environmental Stewardship Scheme: An Exploratory Analysis of the Pennine Way National Trail

Large and unofficial data sets, for instance those gathered from social media, are increasingly being used in geographical research and explored as decision support tools for policy development. Social media data have the potential to provide new insight into phenomena about which there is little information from conventional sources. Within this context, this paper explores the potential of social media data to evaluate the aesthetic management of landscape. Specifically, this project utilises the perceptions of visitors to the Pennine Way National Trail, which passes through land managed under the Environmental Stewardship Scheme (ESS). The method analyses sentiment in trail users’ public Twitter messages (tweets) with the aim of assessing the extent to which the ESS maintains landscape character within the trail corridor. The method demonstrates the importance of filtering social media data to convert it into useful information. After filtering, the results are based on 161 messages directly related to the trail. Although small, this sample illustrates the potential for social media to be used as a cheap and increasingly abundant source of information. We suggest that social media data in this context should be seen as a resource that can complement, rather than replace, conventional data sources such as questionnaires and interviews. Furthermore, we provide guidance on how social media could be effectively used by conservation bodies, such as Natural England, which are charged with the management of areas of environmental value worldwide

Ecological drivers of plant diversity patterns in remnants coastal sand dune ecosystems along the northern Adriatic coastline

Coastal sand dunes represent one of the most fragile ecosystems in the Mediterranean basin. These habitats naturally suffer the action of several limiting factors such as sand burial, marine aerosol and low soil fertility; on the other hand, they often host species of high conservation value. Over the last decades, they have also experienced a high level of biological invasion. In this study, we sampled psammophilous vegetation in two sites in the northern Adriatic coast belonging to the Natura 2000 network to describe diversity patterns and to identify the main ecological drivers of species diversity. Plant species richness and their abundance were assessed in each plot. Differences in species composition for native and alien species were compared via PERMANOVA analysis. Species complementarity was explored by partitioning beta diversity in its spatial components (richness and replacement). A Generalized Linear Model was also computed to assess the main environmental factors that may promote invasiveness in these ecosystems. For the investigated area, our results highlight the strong differentiation in community composition both in alien and native species: in particular alien species showed on average a lower complementarity among habitats compared to native species. Specifically, communities seem to be more diversified when larger spatial scales were considered. Beta diversity in both groups appears to be more dominated by the richness component with respect to the replacement component. Furthermore, in these habitats, the occurrence of alien species was shown to be related to geomorphological predictors more than climatic variables

Improved Upper Limit on the Neutrino Mass from a Direct Kinematic Method by KATRIN

We report on the neutrino mass measurement result from the first four-week science run of the Karlsruhe Tritium Neutrino experiment KATRIN in spring 2019. Beta-decay electrons from a high-purity gaseous molecular tritium source are energy analyzed by a high-resolution MAC-E filter. A fit of the integrated electron spectrum over a narrow interval around the kinematic end point at 18.57 keV gives an effective neutrino mass square value of $(−1.0^{+0.9}_{−1.1}) eV^2$. From this, we derive an upper limit of 1.1 eV (90% confidence level) on the absolute mass scale of neutrinos. This value coincides with the KATRIN sensitivity. It improves upon previous mass limits from kinematic measurements by almost a factor of 2 and provides model-independent input to cosmological studies of structure formation