Public Participation GIS for sustainable urban mobility planning: methods, applications and challenges

Sustainable mobility planning is a new approach to planning, and as such it requires new methods of public participation, data collection and data aggregation. In the article we present an overview of Public Participation GIS (PPGIS) methods with potential use in sustainable urban mobility planning. We present the methods using examples from two recent case studies conducted in Polish cities of Poznań and Łodź. Sustainable urban mobility planning is a cyclical process, and each stage has different data and participatory requirements. Consequently, we situate the PPGIS methods in appropriate stages of planning, based on potential benefits they may bring into the planning process. We discuss key issues related to participant recruitment and provide guidelines for planners interested in implementing methods presented in the paper. The article outlines future research directions stressing the need for systematic case study evaluation

Innovative Data Capture and Presentation Techniques in Support of the EU Environmental Noise Directive

The Environmental Protection Agency of Ireland (EPA) funded from 2006 to 2007 a research project to develop methodologies to meet data-related challenges arising under the European Union (EU) Environmental Noise Directive (END) (2002/49/EC) for Ireland. The research project sought to assess the role of advanced ground-based spatial video and also aerial digital photography in the creation of data required for suitably accurate noise modelling in road environments

Information extraction from sensor networks using the Watershed transform algorithm

Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%

A scoping review of spatial analysis approaches using health survey data in Sub-Saharan Africa

CITATION: Manda, S., Haushona, N. & Bergquist, R. 2020. A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa. International Journal of Environmental Research and Public Health, 17(9). doi:10.3390/ijerph17093070The original publication is available at https://www.mdpi.com/journal/ijerphSpatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.https://www.mdpi.com/1660-4601/17/9/3070/htmPublishers versio

Balancing Spatial and Environmental Impacts of large scale Renewable Offshore Energy Generation in the North Sea

The growing EU energy ambitions in the North Sea region are urging for an accelerated deployment of large-scale renewable energy (RE) infrastructure, with offshore wind farms (OWF) playing an essential role. However, implementing the current EU targets can be limited by the multiple competing spatial claims between existing sea uses, ecological values and OWFs, causing key uncertainties related to potential risks of interaction that may result in barriers to a swift roll-out of RE infrastructure. Up to this date there is no clear understanding of the space availability for different renewable energy installations. Such space availability depends on the alternative space management options applied, relying e.g. on more sectoral management to separate activities or instead, more integrated management to pursue multiuse in time or space. Understanding these trade-offs is especially urgent in the current context of planning marine resources on the North Sea, characterized by lack of coordination, sectoral and fragmented planning, which exacerbates the uncertainties on the potential socio-economic and ecological risks of interaction. In response to these challenges, this thesis aimed to:Develop and demonstrate a set of integrated analytical tools for quantifying and qualifying the spatially explicit trade-offs between offshore spatial claims, in the context of the energy system transition in the North Sea basin.The analytical frameworks developed and used in this study relied and benefited from multiple interactions with multiple research disciplines and methodologies developed as part of the larger network of the ENSYSTRA project

Enhancing partnership among Africa RISING, NAFAKA and TUBORESHE CHAKULA Programs for fast tracking delivery and scaling of agricultural technologies in Tanzania: Annual Report (1 October 2014 - 30 September 2015)

United States Agency for International Developmen