Ordnance Survey

We tested the hypothesis that road safety improves at junctions between minor roads and major roads if the minor roads are modally filtered to remove through traffic. We did this by using police-reported casualty data (2012–2024) to examine the effects of 113 Low Traffic Neighbourhoods (LTNs) implemented in London between 2015 and 2024. Our findings supported our hypothesis: LTN implementation was associated with a 14% reduction in total numbers of casualties at junctions between newly filtered minor roads and surrounding major roads (95% CI: -21% to -8%). This effect was generally consistent across casualty injury severity, casualty travel mode, and the presence of traffic-light controlled signals.

Globally peatlands are laterally extensive and represent important stores and sinks of atmospheric carbon. The cold humid island hypothesis proposes that damaged peatlands can be distinguished from functioning peatlands by their relatively dark, bare, dry soils with resulting relatively high daytime and low night-time land surface temperatures. Contrasts in bare soil, vegetation cover and land surface temperature can be readily observed by satellite and so we propose that Earth observation, and the cold humid island hypothesis, can be used to survey, manage and monitor peatlands. Using the NASA MODIS Earth Observation (EO) products allowed the study to directly assess both status and trajectory of peatlands over multi-decadal time at a national scale. The predictions of the cold humid island hypothesis means EO products (albedo, enhanced vegetation index - EVI, daytime land surface temperature, night-time land surface temperature, and the diurnal amplitude in the land surface temperature) can be used to directly assess peatlands without further calibration or correlation to other ecosystem variables. Knowledge of specific sites within a target region means it is possible to use controls to assess absolute and relative status. By considering the state and expected trajectory of the five EO products over British peatlands it was possible to combine the five EO products into a peat health index. When compared to control locations the majority (69%) of British peatlands showed that they were on a downward trajectory. This downward trajectory was primarily driven by changes in Land Surface Temperature (LST) and, crucially, by deviations from expected trends, as indicated by control variables.

The paper analyzes the tools used in public administration in the field of road safety using the concept of "soft power", analyzes its components.

Creating routes across open areas is challenging due to the absence of a defined routing network and the complexity of the environment, in which multiple criteria may affect route choice. In the context of urban environments, research has found Visibility and Spider-Grid subgraphs to be effective approaches that generate realistic routes. However, the case studies presented typically focus on plazas or parks with defined entry and exit points; little work has been carried out to date on creating routes across open areas in rural settings, which are complex environments with varying terrain and obstacles and undefined entry or exit points. To address this gap, this study proposes a method for routing across open areas based on a Spider-Grid subgraph using queen contiguity. The method leverages a Weighted Sum–Dijkstra’s algorithm to allow multiple criteria such as surface condition, total time, and gradient to be considered when creating routes. The method is tested on the problem of routing across two areas of Dartmoor National Park, United Kingdom. The generated routes are compared with benchmark algorithms and real paths created by users of the Ordnance Survey’s Maps App. The generated routes are found to be more realistic than those of the benchmark methods and closer to the real paths. Furthermore, the routes are able to bypass hazards and obstacles while still providing realistic and flexible routes to the user.

Abstract This paper explores cognitive place associations; conceptualised as a place‐based mental model that derives subconscious links between geographic locations. Utilising a large corpus of online discussion data from the social media website Reddit, we experiment on the extraction of such geographic knowledge from unstructured text. First we construct a system to identify place names found in Reddit comments, disambiguating each to a set of coordinates where possible. Following this, we build a collective picture of cognitive place associations in the United Kingdom, linking locations that co‐occur in user comments and evaluating the effect of distance on the strength of these associations. Exploring these geographies nationally, associations were shown to be typically weaker over greater distances. This distance decay is also highly regional, rural areas typically have greater levels of distance decay, particularly in Wales and Scotland. When comparing major cities across the UK, we observe distinct distance decay patterns, influenced primarily by proximity to other cities.

Wszystko zaczęło się od Floriana Znanieckiego 1 . Najpierw w Ameryce, dokąd Znaniecki trafił na zaproszenie Williama Thomasa z University of Chicago, z którym przygotował fundamentalne dzieło The Polish Peasant in Europe and America (Chłop polski w Europie i w Ameryce), pięć dużych tomów wydanych w Bostonie w latach 1918-1920. Pracę tę obaj autorzy oparli na analizie 764 listów chłopów (za ich pozyskanie płacili niewielką sumę) oraz zamówionej przez Znanieckiego autobiografii Władysława Wiśniewskiego (Władka z Lubotynia), polskiego chłopa, który na początku XX wieku wyemigrował do Stanów Zjednoczonych 2 . Tak rodziła się metoda biograficzna 1 W pierwszych trzech częściach tego tekstu wykorzystuję fragmenty mojego artykułu Fenomen pisania o własnym życiu. Konkursy pamiętnikarskie w Polsce w XX wieku ("Kultura i Społeczeństwo" 2022, nr 2). Tam też obszerniej przedstawiam kwestie tu poruszone.

ABSTRACT Spatial prepositions have been studied in some detail from multiple disciplinary perspectives. However, neither the semantic similarity of these prepositions, nor the relationships between the multiple senses of different spatial prepositions, are well understood. In an empirical study of 24 spatial prepositions, we identify the degree and nature of semantic similarity and extract senses for three semantically similar groups of prepositions using t-SNE, DBSCAN clustering, and Venn diagrams. We validate the work by manual annotation with another data set. We find nuances in meaning among proximity and adjacency prepositions, such as the use of close to instead of near for pairs of lines, and the importance of proximity over contact for the next to preposition, in contrast to other adjacency prepositions.

Three water, sanitation and hygiene (WASH) support tools were applied to Kampala city, Uganda, to evaluate areas with the highest health hazard due to poor wastewater and faecal sludge management and to develop interventions to improve sanitation and reduce exposure. The Pathogen Flow and Mapping Tool (PFMT) assessed how different sanitation management interventions influence pathogen emissions to surface water using rotavirus as the indicator pathogen, while the HyCRISTAL health hazard tool evaluated how flooding and drainage infrastructure influence the presence of human excreta in the environment. The SaniPath tool identified common high-risk pathways of exposure to faecal contamination in food, open drains and floodwater. An overlap in high health hazard hotspot areas was identified by the PFMT and the HyCRISTAL tools. Across the city, the most important hazard sources were the indiscriminate disposal of faecal waste into open stormwater drains from onsite sanitation technologies, open defecation and the insufficient treatment of wastewater. The SaniPath tool identified drain water, floodwater, street food and uncooked produce as the dominant faecal exposure pathways for selected parishes in the city, demonstrating the presence of excreta in the environment. Together, the tools provide collective evidence guiding household, community, and city-wide sanitation, hygiene and infrastructure management interventions from a richer assessment than when a single tool is applied. For areas with high spatial risks, those practising open defecation, and for low-lying areas, these interventions include the provision of watertight pit latrines or septic tanks that are safely managed and regularly emptied. Faecal sludge should be emptied before flood events, direct connections of latrines to open storm drains should be prevented, and the safe handling of food and water promoted. The tools enhance decision making for local authorities, and the assessments can be replicated in other cities.

Urban environments are regions of complex and diverse architecture. Their reconstruction and representation as three-dimensional city models have attracted the attention of many researchers and industry specialists, as they increasingly recognise the potential for new applications requiring detailed building models. Nevertheless, despite being investigated for a few decades, the comprehensive reconstruction of buildings remains a challenging task. While there is a considerable body of literature on this topic, including several systematic reviews summarising ways of acquiring and reconstructing coarse building structures, there is a paucity of in-depth research on the detection and reconstruction of façade openings (i.e., windows and doors). In this review, we provide an overview of emerging applications, data acquisition and processing techniques for building façade reconstruction, emphasising building opening detection. The use of traditional technologies from terrestrial and aerial platforms, along with emerging approaches, such as mobile phones and volunteered geography information, is discussed. The current status of approaches for opening detection is then examined in detail, separated into methods for three-dimensional and two-dimensional data. Based on the review, it is clear that a key limitation associated with façade reconstruction is process automation and the need for user intervention. Another limitation is the incompleteness of the data due to occlusion, which can be reduced by data fusion. In addition, the lack of available diverse benchmark datasets and further investigation into deep-learning methods for façade openings extraction present crucial opportunities for future research.