The implications of COVID-19 for urban planning and governance are wide ranging and have triggered a rethinking of how policies related to housing, transportation, sustainability, climate change and governance might be redeveloped to be better suited for post-pandemic cities. Over the past five years, both academic and popular accounts have highlighted commonalities between adaptations that cities are making to become more resilient to infectious disease outbreaks like COVID-19, while also addressing sustainable development and climate change indicators and goals. Much of this literature has suggested that a shift towards greater implementation of urban blue and green space - along with other interventions, such as encouraging compact city design, reducing sprawl and encouraging active transit modes - can contribute to healthier and socio-environmentally friendly cities, while also reducing carbon emissions and achieving urban climate goals. However, this article argues that there have been significant barriers faced in doing so that have hampered their effectiveness and implementation. These include the entrenched ideologies favouring 'grey' over 'green' infrastructure; political-economic and financial constraints; reactive forms of urban and climate governance; and what we call the temporal politics of urban climate governance vis-& agrave;-vis infectious disease responses. We suggest how these barriers can be potentially overcome through more engaged forms of grassroots planning and governance in cities which can implement more rapid and place-specific responses. Our review is largely based on scholarship that has emerged in the wake of the COVID-19 pandemic in the fields of urban and environmental studies. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic),(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic),(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic):(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)"(sic)(sic)"(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic);(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic);(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic);(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)((sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).
Robust robot navigation in outdoor environments requires accurate perception systems capable of handling visual challenges such as repetitive structures and changing appearances. Visual feature matching is crucial to vision-based pipelines but remains particularly challenging in natural outdoor settings due to perceptual aliasing. We address this issue in vineyards, where repetitive vine trunks and other natural elements generate ambiguous descriptors that hinder reliable feature matching. We hypothesise that semantic information tied to keypoint positions can alleviate perceptual aliasing by enhancing keypoint descriptor distinctiveness. To this end, we introduce a keypoint semantic integration technique that improves the descriptors in semantically meaningful regions within the image, enabling more accurate differentiation even among visually similar local features. We validate this approach in two vineyard perception tasks: (i) relative pose estimation and (ii) visual localisation. Our method improves matching accuracy across all tested keypoint types and descriptors, demonstrating its effectiveness over multiple months in challenging vineyard conditions.
Biochar facilitates the reduction of N2O to N-2 by promoting denitrification through its electron shuttle function, a mechanism widely recognized as key to its role in mitigating soil N2O accumulation. This electron shuttle capacity is primarily attributed to surface redox-active functional groups, such as quinones and phenolic hydroxyls. Among these, quinone/hydroquinone (Q/QH(2)) groups serve as reversible redox pairs, enhancing electron transport efficiency through cyclic electron acceptance and donation. However, the mechanisms by which quinone functional groups regulate the electron-shuttling capacity of biochar, and thereby amplify its ability to promote complete denitrification and N2O mitigation, remain unclear. In this study, biochar with enhanced electron-shuttling capacity was prepared by incorporating redox-active quinone groups. The biochar's effectiveness in reducing soil N2O accumulation was evaluated by incorporating it into soil. Quinone-enhanced biochar (QBC) markedly enhanced the biochar's electron-shuttling function and reduced soil N2O accumulation by 82.3 % relative to a control biochar. Furthermore, quinone-loaded biochar increased the relative expression of Acidobacteria and upregulated the abundance of nosZ-II genes, resulting in lower N2O/(N2O + N-2) ratios, lower residual NO3-, and higher N-2 accumulation that are consistent with more complete denitrification. Our results therefore indicate that the improved electron-shuttling function of biochar is consistent with more complete denitrification and enhanced N2O reduction. These findings indicate that incorporating quinone groups into biochar is a viable strategy to mitigate N2O accumulation by enhancing its electron-shuttling function.
Navigating within narrow spaces is a fundamental challenge in robotics, requiring precise localisation, localisation error recovery, dynamic path planning, and adaptive control for effective manoeuvring. This paper presents a modular and perception-driven navigation framework designed for constrained environments, focusing primarily on agricultural applications. The proposed method integrates a multi-step point cloud processing pipeline for robust local perception, including pole detection, boundary line estimation, and trajectory refinement to ensure safe and precise traversal by refining initial trajectories based on detected environmental constraints and dynamically adapting to kinematic limitations. Experimental validation in a real strawberry polytunnel demonstrates superior trajectory accuracy and control stability compared to state-of-the-art navigators, achieving an average lateral deviation of 0.08 ± 0.01 m. The adaptive trajectory tracking and regulated pure pursuit control of the framework contribute to consistent navigation, even under increased velocity constraints, outperforming the resilient timed elastic band (RTEB) and model predictive path integral (MPPI) methods. This modular and generalisable framework offers significant potential for advancing autonomous navigation in narrow-space applications.
