Spatial determinants of local government action on climate change: an analysis of local authorities in England

The engagement of UK local authorities is vital if national government is to meet its climate change commitments. However, with no mandatory targets at local government level, other drivers must explain engagement. Using a Geographic Information System, this study compares the spatial distribution of action on climate change based on past actions and stated intentions to a suite of relevant independent variables. The Action Index created is among the first to quantify climate change engagement beyond a simple binary measure and provides a useful comparative study to recent work in the US. The Index enables investigation of both mitigation and adaptation, which show different trends in relation to some variables. The study shows that action is strongest where the voting habits of the local population suggest environmental concern and where neighbouring local authorities are also engaging in action on climate change. Physical vulnerability to the effects of climate change is a motivator for action only where the dangers are obvious. Action is less likely where other resource intensive issues such as crime and housing exist within a local authority area

IL GEOMARKETING: TEORIE, TECNICHE E STRUMENTI

2002/2003XVI Ciclo1974Versione digitalizzata della tesi di dottorato cartacea

Georeferencing historical telephone directories to understand innovation diffusion and social change

This paper explores how historical archives of British telephone directories, recently made available, can be used to revisit historical and geographical questions using a modern, quantitative approach. By geolocating telephone subscribers throughout history, we seek to retrace spatial and temporal changes in demography and the spread of the fixed line telephone network in Britain. We develop a prototypical pipeline for capturing and processing these data using archives from 1881 and demonstrate that, if extended and applied to directories from the subsequent 100 years, this research can provide new insights into wide-ranging aspects of British social and economic history

Generating the CFP indicators sampling frame for FAO area 27 (Northeast Atlantic)

For the analysis of the CFP indicators it is necessary to generate the sampling frame. The sampling frame is the collection of species in EU Fisheries Managment Zones (FMZ) for which the CFP is at least partially responsible for their management. This document describes the generation of the sampling frame. Embedded R code is executed to generate the sampling frame.JRC.D.2-Water and Marine Resource

Mapping Fishing Effort through AIS Data

Several research initiatives have been undertaken to map fishing effort at high spatial resolution using the Vessel Monitoring System (VMS). An alternative to the VMS is represented by the Automatic Identification System (AIS), which in the EU became compulsory in May 2014 for all fishing vessels of length above 15 meters. The aim of this paper is to assess the uptake of the AIS in the EU fishing fleet and the feasibility of producing a map of fishing effort with high spatial and temporal resolution at European scale. After analysing a large AIS dataset for the period January-August 2014 and covering most of the EU waters, we show that AIS was adopted by around 75% of EU fishing vessels above 15 meters of length. Using the Swedish fleet as a case study, we developed a method to identify fishing activity based on the analysis of individual vessels’ speed profiles and produce a high resolution map of fishing effort based on AIS data. The method was validated using detailed logbook data and proved to be sufficiently accurate and computationally efficient to identify fishing grounds and effort in the case of trawlers, which represent the largest portion of the EU fishing fleet above 15 meters of length. Issues still to be addressed before extending the exercise to the entire EU fleet are the assessment of coverage levels of the AIS data for all EU waters and the identification of fishing activity in the case of vessels other than trawlers.JRC.G.3-Maritime affair

The NCRM wayfinder guide to moving to secondary data analysis

Research work in all forms and across all fields can benefit from making use of both primary and secondary data analysis. While primary data commonly refers to the data collected and used for a specific targeted research study, secondary data is the re-use or re-analysis of primary data collected elsewhere for new purposes – potentially in addition to or extending beyond the original scope of the data. The importance of secondary data has been highlighted by COVID-19 and related research work. For example, administrative Test and Trace records are used not only for counting the number of positive cases and prevalence of COVID-19 infections, but have further been used in conjunction with other data to study the broader dynamics of the pandemic and help improve insights. We can extend the value of these data through linking and matching different secondary data sources to other external datasets such as local characteristics of neighbourhood demographics, socio-economic conditions, deprivation, or accessibility to key public amenities and health infrastructure. As we move into the territory of including secondary data to the analysis, it is important to understand the benefits, limitations and best practices associated with it. Learning to effectively incorporate secondary data and analysis into a research project can be an important way in which to build up a robust and comprehensive study

The Mediterranean and Black Sea STECF Stock Assessment Database

Since 2007, the Scientific Technical Economic Committee for Fisheries (STECF), for which Joint Research Centre (JRC) runs the Secretariat and all the data collection process, started collecting and organizing information on Mediterranean and Black Sea fisheries, and since 2009 performing standardized stock assessments on these fisheries during STECF expert working groups (EWGs). The stock assessment results have been documented in more than 30 reports STECF EWGs (https://stecf.jrc.ec.europa.eu/reports/medbs). Stock assessments performed during the STECF EWGs employ different approaches and tools, however, models implemented in the Fisheries Libraries in R (FLR, http://www.flr-project.org) were the most used. After almost 10 years of stock assessments in the Mediterranean and Black Sea, JRC extracted available stock assessment data from digital repositories of EWGs and compiled a STECF reference database. From each assessment contained in the STECF reports yearly time series of stock variables such as:Total Catch (total weight of all fish in the stock), Recruitment (total number of individuals entering yearly in the population), Spawning Stock Biomass (total weight of all sexually mature fish in the stock) and Fishing Mortality were extracted. The assessments data are made available through an online interactive dashboard under the STECF Data dissemination web page (https://stecf.jrc.ec.europa.eu/dd/medbs/ram) that allow readers to compare and contrast several stock assessments variables. Each stock assessment is linked via an URL to the original source of the stock assessment. According to EU CFP - Common Fisheries Policy (Reg. EU 1380/2013 and Reg. EU812/2015) all EU commercial fish stocks should be fished at a maximum sustainable yield (Fmsy). Biological reference points, Fref (Fmsy or a proxy as F 0.1 ) and were subsequently used to assess if the level of exploitation (F/Fmsy) is in line with the CFP objectives (F/Fmsy≤1) or not (F/Fmsy >1). The STECF database is the reference database for the computation of the Common Fisheries Policy monitoring indicators for the Mediterranean and Black Sea (https://stecf.jrc.ec.europa.eu/documents/43805/2092142/STECF+18-01+adhoc+-+CFP+Monitoring+2018.pdf) To ensure traceability and foster reproducible scientific research, all the data, code and references part of the compilation process are hosted on GitHub, a well-known version control software platform. The target audience of the dashboard ranges from governments, fisheries institutes, stakeholders, NGO’s and common citizens that want to check the status of marine fisheries resources evaluated. A copy of the Mediterranean and Black Sea STECF stock assessment results will be included, for the first time, in the next release of the RAM legacy database: a voluntary contributed worldwide stock assessments database, RAM legacy, (http://ramlegacy.org/). The RAM Legacy database includes fish stock assessments from all around the world’s oceans, and provides a unique source of information to make comparisons between fisheries and to perform global analysis of stock status.JRC.D.2-Water and Marine Resource

Local Data Spaces: Leveraging trusted research environments for secure location-based policy research in the age of coronavirus disease-2019

This work explores the use of Trusted Research Environments for the secure analysis of sensitive, record-level data on local coronavirus disease-2019 (COVID-19) inequalities and economic vulnerabilities. The Local Data Spaces (LDS) project was a targeted rapid response and cross-disciplinary collaborative initiative using the Office for National Statistics’ Secure Research Service for localized comparison and analysis of health and economic outcomes over the course of the COVID-19 pandemic. Embedded researchers worked on co-producing a range of locally focused insights and reports built on secure secondary data and made appropriately open and available to the public and all local stakeholders for wider use. With secure infrastructure and overall data governance practices in place, accredited researchers were able to access a wealth of detailed data and resources to facilitate more targeted local policy analysis. Working with data within such infrastructure as part of a larger research project involved advanced planning and coordination to be efficient. As new and novel granular data resources become securely available (e.g., record-level administrative digital health records or consumer data), a range of local policy insights can be gained across issues of public health or local economic vitality. Many of these new forms of data however often come with a large degree of sensitivity around issues of personal identifiability and how the data is used for public-facing research and require secure and responsible use. Learning to work appropriately with secure data and research environments can open up many avenues for collaboration and analysis

Identifying and interpreting spatiotemporal variation in diagnoses of infectious syphilis among men, England: 2009 to 2013.

OBJECTIVES: Spatial clusters and variations in the trajectory of local epidemics were explored in relation to sexual orientation, demographic factors, stage of syphilis infection and HIV serostatus. METHODS: Kulldorff's scan statistics (SaTScan) was used to distinguish endemic and temporary clusters using a two-stage analysis. RESULTS: Endemic areas were found in London, Manchester, Brighton and Blackpool. Up to 40% of diagnoses were found within an 11 km radius of central London. Of men diagnosed with syphilis in London, 80% were men who have sex with men (MSM). Annual incidence in London increased from 24 cases (95% CI 23 to 26) per 100 000 male population in 2009 to 36 cases (95% CI 34 to38) in 2013. In comparison with clusters, endemic areas were characterised by a significantly higher (p<0.05) proportion of MSM (83% compared with 73%), increased HIV positivity (41% vs 15%), age 35 to 44 years (34% vs 23%), a lower proportion of patients born in the UK (50% vs 79%) and a lower proportion of primary stage infection (40% vs 47%). Space-time clusters outside endemic areas occurred in urban and rural areas and diagnoses fluctuated below 10 per month. Exponential increases in diagnoses resembling point source outbreaks were seen at two locations. CONCLUSION: Control of syphilis in endemic areas has proved elusive and clusters present unique intervention opportunities. Investigating the diversity of local epidemics provides information that can be used to predict outbreak structure, plan and evaluate sexual health services and guide public health investigation, hypothesis generation and research