Do drivers of nature visitation vary spatially? The importance of context for understanding visitation of nature areas in Europe and North America

Nature visitation is important, both culturally and economically. Given the contribution of nature recreation to multiple societal goals, comprehending determinants of nature visitation is essential to understand the drivers associated with the popularity of nature areas, for example, to inform land-use planning or site management strategies to maximise benefits. Understanding the factors related to nature, tourism and recreation can support the management of nature areas and thereby, also conservation efforts and biodiversity protection. This study applied a Multiscale Geographically Weighted Regression (MGWR) to quantify the spatially varying influence of different factors associated with nature visitation in Europe and North America. Results indicated that some explanatory variables were stationary for all sites (age 15 to 65, population density (within 25 km), GDP, area, built-up areas, plateaus, and mountains). In contrast, others exhibited significant spatial non-stationarity (locally variable): needle-leaf trees (conifers), trails, travel time, roads, and Red List birds and amphibians. Needle-leaf trees and travel time were found to be negatively significant in Europe. Roads were found to have a significant positive effect in North America. Trails and Red List bird species were found to have a positive effect in both North America and North Europe, with a greater effect in Europe. Red List amphibians was the only spatially variable predictor to have both a positive and negative impact, with selected sites in North America and northern Europe being positive, whereas Iceland and central and southern Europe were negative. The scale of the response-predictor relationship (bandwidth) of these locally variable predictors was smallest for Red List amphibians at 1033 km, with all other spatially variable predictors between 9,558 and 12,285 km. The study demonstrates the contribution that MGWR, a spatially explicit model, can make to support a deeper understanding of processes associated with nature visitation in different geographic contexts

Examining the correlates and drivers of human population distributions across low-and middle-income countries

Geographical factors have influenced the distributions and densities of global human population distributions for centuries. Climatic regimes have made some regions more habitable than others, harsh topography has discouraged human settlement, and transport links have encouraged population growth. A better understanding of these types of relationships enables both improved mapping of population distributions today and modelling of future scenarios. However, few comprehensive studies of the relationships between population spatial distributions and the range of drivers and correlates that exist have been undertaken at all, much less at high spatial resolutions, and particularly across the low-and middle-income countries. Here, we quantify the relative importance of multiple types of drivers and covariates in explaining observed population densities across 32 low-and middle-income countries over four continents using machine-learning approaches. We find that, while relationships between population densities and geographical factors show some variation between regions, theyare generally remarkably consistent,pointing to universal drivers of human population distribution. Here,we find that a set of geographical features relating to the built environment, ecology and topography consistently explain the majority of variability in population distributions at fine spatial scales across the low-and middle-income regions of the world.</p

Green Space and cognitive ageing: a retrospective life course analysis in the Lothian Birth Cohort 1936

International evidence suggests that green space has beneficial effects on general and mental health but little is known about how lifetime exposure to green space influences cognitive ageing. Employing a novel longitudinal life course approach, we examined the association between lifetime availability of public parks and cognitive ageing. Lifetime residential information was gathered from the participants of the Lothian Birth Cohort 1936 using a "life-grid" questionnaire at age 78 years. Parks information from 1949, 1969 and 2009 was used to determine a percentage of parks within a 1500 m buffer zone surrounding residence for childhood, adulthood, and later adulthood periods. Linear regressions were undertaken to test for association with age-standardised, residualised change in cognitive function (Moray House Test score) from age 11 to 70 years, and from age 70 to 76 (n = 281). The most appropriate model was selected using the results of a partial F-test, and then stratified by demographic, genetic and socioeconomic factors. The local provision of park space in childhood and adulthood were both important in explaining the change in cognitive function in later life. The association between childhood and adulthood park availability and change in the Moray House Test Score from age 70 to 76 was strongest for women, those without an APOE e4 allele (a genetic risk factor), and those in the lowest socioeconomic groups. Greater neighbourhood provision of public parks from childhood through to adulthood may help to slow down the rate of cognitive decline in later life, recognising that such environmental associations are always sensitive to individual characteristics

OpenStreetMap data for Australia (osm.pbf)

OpenStreetMap data for Australia (© OpenStreetMap) used for computing travel times to hospitals

GSDR - WeGov Now - Data

A collection of data files for the WeGovNow project. It contains the source data provided by stake holders, OpenStreetMap data (under the OSM data license) and data generated by the IGIS.TK application

Fast Reverse Geocoder using OpenStreetMap data

Data files for the fast reverse geocoder available at https://github.com/kno10/reversegeocode For source code to generate or use the data, see above URL

GSDR - WeGov Now - Data

A collection of data files for the WeGovNow project. It contains the source data provided by stake holders, OpenStreetMap data (under the OSM data license) and data generated by the IGIS.TK application

Technical Guidelines for Small Island Mapping with UAVs

Image acquisition and surveying using unmanned aerial vehicles (UAVs) is a very promising technology for Small Island Developing States (SIDS). UAVs can be a relatively low-cost data collection tool at the surveying scales often needed in small island contexts. Further, UAVs can capture thousands of images in a single flight and provide greater detail than satellites or even manned aircraft. The World Bank and Humanitarian OpenStreetMap Team (HOT) compiled this guidance note to document experience and best practices in the use and operation of UAVs for economic development in SIDS. Many of the lessons presented in this guidance note stem from the UAV4Resilience organized by the World Bank (World Bank 2017b) and from experiences with Pacific Drone Imagery Dashboard (PacDID) deployments in the Pacific islands (HOT 2016). This report is intended for local technological agencies of island nations that work to operationalize UAVs as a standard data collection tool