Probabilistic latent semantic analysis as a potential method for integrating spatial data concepts

In this paper we explore the use of Probabilistic Latent Semantic Analysis (PLSA) as a method for quantifying semantic differences between land cover classes. The results are promising, revealing ‘hidden’ or not easily discernible data concepts. PLSA provides a ‘bottom up’ approach to interoperability problems for users in the face of ‘top down’ solutions provided by formal ontologies. We note the potential for a meta-problem of how to interpret the concepts and the need for further research to reconcile the top-down and bottom-up approaches

Image matching of firearm fingerprints

A spent cartridge case exhibits characteristic markings (firearm fingerprint) that can be used to identify the type and possibly make of weapon in which the cartridge was fired. This report details research into the use of discriminant analysis for the purpose of matching spent rim-fire cartridge cases to specific make and model firearms. The discrimination and classification are based on several scalar shape parameters for the two-dimensional silhouette of the firing pin (FP) impression-- shape factor calculated from the second order moment of inertia, G factor calculated from the distance transform, and the P2A factor- as well as the distance between the centre of the cartridge case and the centroid of the FP impression, and the orientation of the principal centroidal axes associated with the FP impression. Classification results for two case studies are detailed: (i) 3 different make/model weapons producing different shaped FP impressions, and (ii) 5 different make/model weapons each producing a rectangular FP impression

Pharmaceuticals in soils of lower income countries: Physico-chemical fate and risks from wastewater irrigation.

Population growth, increasing affluence, and greater access to medicines have led to an increase in active pharmaceutical ingredients (APIs) entering sewerage networks. In areas with high wastewater reuse, residual quantities of APIs may enter soils via irrigation with treated, partially treated, or untreated wastewater and sludge. Wastewater used for irrigation is currently not included in chemical environmental risk assessments and requires further consideration in areas with high water reuse. This study critically assesses the contemporary understanding of the occurrence and fate of APIs in soils of low and lower-middle income countries (LLMIC) in order to contribute to the development of risk assessments for APIs in LLMIC. The physico-chemical properties of APIs and soils vary greatly globally, impacting on API fate, bioaccumulation and toxicity. The impact of pH, clay and organic matter on the fate of organic ionisable compounds is discussed in detail. This study highlights the occurrence and the partitioning and degradation coefficients for APIs in soil:porewater systems, API usage data in LLMICS and removal rates (where used) within sewage treatment plants as key areas where data are required in order to inform robust environmental risk assessment methodologies

Participation in Transition(s):Reconceiving Public Engagements in Energy Transitions as Co-Produced, Emergent and Diverse

This paper brings the transitions literature into conversation with constructivist Science and Technology Studies (STS) perspectives on participation for the first time. In doing so we put forward a conception of public and civil society engagement in sustainability transitions as co-produced, relational, and emergent. Through paying close attention to the ways in which the subjects, objects, and procedural formats of public engagement are constructed through the performance of participatory collectives, our approach offers a framework to open up to and symmetrically compare diverse and interconnected forms of participation that make up wider socio-technical systems. We apply this framework in a comparative analysis of four diverse cases of civil society involvement in UK low carbon energy transitions. This highlights similarities and differences in how these distinct participatory collectives are orchestrated, mediated, and subject to exclusions, as well as their effects in producing particular visions of the issue at stake and implicit models of participation and ‘the public’. In conclusion we reflect on the value of this approach for opening up the politics of societal engagement in transitions, building systemic perspectives of interconnected ‘ecologies of participation’, and better accounting for the emergence, inherent uncertainties, and indeterminacies of all forms of participation in transitions

Building Extraction from Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network

Automated methods to extract buildings from very high resolution (VHR) remote sensing data have many applications in a wide range of fields. Many convolutional neural network (CNN) based methods have been proposed and have achieved significant advances in the building extraction task. In order to refine predictions, a lot of recent approaches fuse features from earlier layers of CNNs to introduce abundant spatial information, which is known as skip connection. However, this strategy of reusing earlier features directly without processing could reduce the performance of the network. To address this problem, we propose a novel fully convolutional network (FCN) that adopts attention based re-weighting to extract buildings from aerial imagery. Specifically, we consider the semantic gap between features from different stages and leverage the attention mechanism to bridge the gap prior to the fusion of features. The inferred attention weights along spatial and channel-wise dimensions make the low level feature maps adaptive to high level feature maps in a target-oriented manner. Experimental results on three publicly available aerial imagery datasets show that the proposed model (RFA-UNet) achieves comparable and improved performance compared to other state-of-the-art models for building extraction

Driving Factors of Land Change in China’s Loess Plateau: Quantification Using Geographically Weighted Regression and Management Implications

Land change is a key topic in research on global environmental change, and the restoration of degraded land is the core component of the global Land Degradation Neutrality target under the UN 2030 Agenda for Sustainable Development. In this study, remote-sensing-derived land-use data were used to characterize the land-change processes in China’s Loess Plateau, which is experiencing large-scale ecological restoration. Geographically Weighted Regression was applied to capture the spatiotemporal variations in land change and driving-force relationships. First, we explored land-use change in the Loess Plateau for the period 1990–2015. Grassland, cropland and forestland were dominant land cover in the region, with a total percentage area of 88%. The region experienced dramatic land-use transitions during the study period: degraded grassland and wetland, expansion of cropland and built-up land and weak restoration of forestland during 1990–2000; and increases in grassland, built-up land, forestland and wetland, concurrent with shrinking cropland during 2000–2015. A Geographically Weighted Regression (GWR) analysis revealed altitude to be the common dominant factor associated with the four major land-use types (forestland, grassland, cropland and built-up land). Altitude and slope were found to be positively associated with forestland, while being negatively associated with cropland in the high, steep central region. For both forestland and grassland, temperature and precipitation behaved in a similar manner, with a positive hotspot in the northwest. Altitude, slope and distance to road were all negatively associated with built-up land across the region. The GWR captured the spatial non-stationarity on different socioeconomic driving forces. Spatial heterogeneity and temporal variation of the impact of socioeconomic drivers indicate that the ecological restoration projects positively affected the region’s greening trend with hotspots in the center and west, and also improved farmer well-being. Notably, urban population showed undesired effects, expressed in accelerating grassland degradation in central and western regions for 1990–2000, hindering forestland and grassland restoration in the south during 2000–2015, and highlighting the long-term sustainability of the vegetation restoration progress. Such local results have the potential to provide a methodological contribution (e.g., nesting local-level approaches, i.e., GWR, within land system research) and spatially explicit evidence for context-related and proactive land management (e.g., balancing urbanization and ecological restoration processes and advancing agricultural development and rural welfare improvement)

Simulation model of pedestrian flow based on multi-agent system and Bayesian Nash equilibrium

Computer-based simulation is a means of exploring complex systems and has become the mainstream method of pedestrian research. In this research, a multi-agent simulation model of pedestrian flow will be established using a multi-agent system (MAS) and Bayesian Nash equilibrium. MAS is used to simulate the crowd movement and the interaction between pedestrians, and Bayesian Nash equilibrium is adopted to analyze the decision-making process of pedestrians. In contrast to previous pedestrian flow simulation modeling methods, this study adopts multi-agent modeling to realize the complete heterogeneity of pedestrians, so as to achieve more accurate simulation and make the research conclusions closer to reality. To be specific, we attempt to determine the cell side length and simulation time step of an initial model parameterized using a dataset of actual pedestrian movements. It allows more than one pedestrian to be in the same cell and stipulates that the utility of pedestrians decreases with the growing number of pedestrians in the cell. The Bayesian Nash equilibrium is applied to analyze the decision-making process of pedestrians and collision avoidance rules and interaction rules of agents are also formulated. A number of areas of further research are discussed

A pedestrian ABM in complex evacuation environments based on Bayesian Nash Equilibrium

This research proposed an improved pedestrian evacuation ABM incorporating Bayesian Nash equilibrium (BNE) to provide more realistic simulations of evacuating behaviours in complex environments. BNE theory was introduced to improve the rationality of model simulations by quantifying individual decision-making process. Latest research put forward that BNE pedestrians (agents) were capable of evacuating faster and displayed more intelligent and representative evacuating behaviours. To further evaluate the role of BNE played in agents’ navigations in complex scenarios, this paper extends the above work by introducing impassable barriers with changeable sizes to realise the simulations in a more complex evacuation space with several narrow corridors. In order to match the demands of efficiently avoiding congestions and impassable areas, the decision-making rule of BNE agents when one patch was occupied by over 10 agents was improved from 100% best strategy to a multi-strategy combination: with 50% optimal strategy, 40% suboptimal strategy and 10% choosing one of the remaining options. It was found that compared with the agents following the other two traditional models, BNE agents could change their original exiting route after considering possible movements of the neighbouring agents and may evacuate through the corridors relatively further from the exit. A detailed introduction of the improved ABM is provided in this paper. Potential research directions are also identified

Engineering Comes Home: Co-designing nexus infrastructure from the bottom-up

The ‘nexus’ between water, food and energy systems is well established. It is conventionally analysed as a supply-side problem of infrastructure interdependencies, overlooking demand-side interactions and opportunities. The home is one of the most significant sites of nexus interactions and opportunities for redesigning technologies and infrastructure. New developments in ‘smart city’ technologies have the potential to support a bottom-up approach to designing and managing nexus infrastructure. The Engineering Comes Home was a research project that turned infrastructure design on its head. The objectives of the project were to: Demonstrate a new paradigm for engineering design starting from the viewpoint of the home, looking out towards systems of provision to meet household demands. Integrate thinking about water, energy, food, waste and data at the domestic scale to support userled innovation and co-design of technologies and infrastructure. Test new design methods that connect homes to communities, technologies and infrastructure, enhancing positive interactions between data, water, energy, food and waste systems. Develop a robust Lifecycle Assessment (LCA) Calculator tool to support environmental decisionmaking in co-design. Working with residents of the Meakin Estate in South London, the project followed a co-design method to identify requirements, analyse options and develop and test a detailed design for a preferred option. The outputs were: 1) Ethnographic study of how residents use water, energy and food resources in their homes and key opportunities for engineering design to improve wellbeing and reduce resource consumption. 2) Co-design of decentralised infrastructural systems in three workshops in 2016-2017. The first workshop identified key priorities for development from the community using a novel token-based system design method, to enable participants to build up alternative designs for local provision of water, energy, food and waste services. The second workshop provided participants with factsheets and photographs of the candidate technologies, which were then analysed using a LCA Calculator tool. 47 Rainwater harvesting was selected as the technology for further co-design in the third workshop, which focussed on scaling up a pilot installation. 3) Pilot-scale smart rainwater system was installed in partnership with the Over The Air Analytics (OTA). OTA’s system enables remote control of the rainwater storage tanks to optimise their performance as stormwater attenuation as well as non-potable water supply. 4) Lifecycle Assessment (LCA) Calculator to enable quick estimation of the impacts of new systems and technology to deliver water, energy and food, and manage waste at the household and neighbourhood scale. 5) Stakeholders, including utilities, design consultancies and community based organisations, were engaged in three workshops to inform the wider relevance and development of the co-design methods and tools. 6) Toolbox and method statements to standardise and disseminate the methods used in the project for wider application and development