Members’ Publication

This paper shares the findings of an active transportation (AT) study conducted in the context of a city in a developing country. First, a list of AT indicators was developed based on the literature review and expert opinion survey. Second, a face-to-face survey was conducted to collect information on individuals' socio-demographic characteristics, travel behavior, AT mode choice, and their perceptions regarding the AT conditions in their neighborhoods. Analysis of the survey results suggests that several socio-demographic characteristics are associated with AT use. For example, young adults and individuals with low income are the primary users of AT. Also, results suggest that students are mainly active commuters. The ratio of AT use increases with the number of bicycles in the household. Individuals tend to walk more when travel duration is less than 10 minutes. Educational areas are perceived as safer and convenient areas for using active modes of transport compared to other land-use types. Also, a higher proportion of active commuters perceive local roads to be safer from vehicular traffic compared to main roads. Many sectors such as planning, transportation, health, and education as well as non-government organizations will be benefited from this study.

This article examines youth participation the school climate strikes of 2018 and 2019 (also known as #Fridays4Future), through an exploratory study conducted in seven diverse cities. Despite the international nature of the climate strikes, we know little about the factors that influenced youth participation in these protests beyond the global North. This matters because youth of the global South are disproportionately impacted by climate change and there is growing concern that the climate movement is dominated by narratives that marginalize the voices and priorities of Indigenous communities and people of color. In this context, the exploratory research reported here aimed to compare the attitudes of climate protesters (n
314) and their non-protester peers (n
1,217), in diverse city samples drawn from a wider study of children and youth aged 12–24 years, living in Christchurch (New Zealand); Dhaka (Bangladesh); Lambeth, London (United Kingdom); Makhanda (South Africa); New Delhi (India); São Paulo (Brazil); and Yokohama (Japan). Using crosssectional data (N
1,531) and binary logistic regression models, researchers examined three common explanations for youth participation in protest: availability (biographical and structural), political engagement (reported individual and collective efficacy of strikers and non-strikers), and self-reported biospheric values amongst participants. Results indicate that even in diverse city samples, structural availability (civic skills and organizational membership) predicted strike participation across city samples, but not political engagement (self-efficacy and collective efficacy). Youth who reported that ‘living in harmony with nature and animals’ was important for their wellbeing, were also more likely to strike than their peers. Descriptive statistics indicated that the majority (85 percent) of all protestors in this study agreed climate change was a serious issue and a startling 65 percent said that they think about climate change “all the time”. Reported rates of youth climate protest participation varied across city samples as did the extent to which participants reported having friends take part or expecting climate change to have a personal impact. While the study is exploratory, it points to the need for more extensive research to understand the diversity of youth participation in ‘global climate strikes’.

New data platforms have made satellite data freely available and farmers can now produce variable rate application (VRA) maps for nitrogen fertilisers and other inputs based on satellite images. The data platforms are currently attracting attention for site-specific weed management because they are free and user-friendly. Satellite imagery is mainly relevant for detecting large, dense weed patches that have unique spectral characteristics in low-resolution images. The objective of this study was to examine whether Sentinel-2 images are useful in the detection of Cirsium arvense and other green vegetation in pre-harvest cereals. It was hypothesised that there is a lower limit for detection and that weeds in large patches are easier to detect than weeds in small patches. Fifteen fields infested with C. arvense were used to evaluate the possibilities of utilising the normalised difference vegetation index (NDVI) from Sentinel-2 images as a weed classifier. High-resolution RGB images from unmanned aerial vehicles (UAV) were used as ground-truthing after classifying green pixels as weeds with C. arvense as the main contributor. The study showed that C. arvense-dominated weed populations were much less aggregated than previously reported. On average, 90 % of the weeds occurred on 50 % of the field area, in a range from 21 % to 72 %. The potential herbicide savings using Sentinel-2 images were in the range of 6 % to 46 %, averaging 24 %. The low weed aggregation combined with low image resolution limited the prospects of using Sentinel-2 images for weed detection. The study showed that UAV imagery offers much greater potential for herbicide savings due to higher image resolution, allowing the detection of individual C. arvense shoots.