Multi-view SDI Assessment Framework

When developing Spatial Data Infrastructures (SDI) initiatives it is increasingly important to assess their outcomes in order to justify the resources spent on those infrastructures. Many researchers throughout the world have been struggling with the issue of assessing SDIs. The task is difficult due to complex, dynamic and constantly evolving nature of SDI. As SDI can be treated as a Complex Adaptive System, the assessment should include strategies for evaluating those kinds of systems. One strategy is to use multiple assessment approaches and methods. The general evaluation research and experience provide additional motives for adopting such a strategy. We present the multi-view framework for assessing SDI initiatives around the world, and argue that the strength of this assessment design lies in its flexibility, its multidisciplinary view on SDI and a reduced bias in the assessment results. The multi-view framework contains methods that not only evaluate SDI performance, but also deepen our knowledge about SDI functioning, and may assist in its development. The article presents the assessment framework and describes its theoretical grounding in complexity theory and evaluation research. The application of the framework is beyond the scope of this paper

Producing consistent visually interpreted land cover reference data: learning from feedback

Reference data for large-scale land cover map are commonly acquired by visual interpretation of remotely sensed data. To assure consistency, multiple images are used, interpreters are trained, sites are interpreted by several individuals, or the procedure includes a review. But little is known about important factors influencing the quality of visually interpreted data. We assessed the effect of multiple variables on land cover class agreement between interpreters and reviewers. Our analyses concerned data collected for validation of a global land cover map within the Copernicus Global Land Service project. Four cycles of visual interpretation were conducted, each was followed by review and feedback. Each interpreted site element was labelled according to dominant land cover type. We assessed relationships between the number of interpretation updates following feedback and the variables grouped in personal, training, and environmental categories. Variable importance was assessed using random forest regression. Personal variable interpreter identifier and training variable timestamp were found the strongest predictors of update counts, while the environmental variables complexity and image availability had least impact. Feedback loops reduced updating and hence improved consistency of the interpretations. Implementing feedback loops into the visually interpreted data collection increases the consistency of acquired land cover reference data

Understanding Governance Dynamics: The Governing System of Spatial Data Infrastructures

The importance and influence of spatial data has risen in all kinds of governmental and non-governmental processes, giving spatial data infrastructures (SDIs) a key role in spatial data sharing and dissemination. SDIs are nowadays challenged by new technologies and user demands. Proper SDI governance seems essential, but it is unclear to what extent current SDI governing systems are fully equipped to deal with the dynamics and complexity of SDIs. This research proposes a governing system framework for analysing the governing system of SDIs, adapted from the concepts of Kooiman. This framework is applied to two Dutch SDI cases: the Risk Map and the New Map of the Netherlands. With the help of the framework, the strong and weak aspects of the governing system of SDIs become more apparent and insights emerge on which interactions, images, instruments, actions and structures enable or constrain SDI governance. By observing changes in governing systems over time, SDI governance dynamics become visible. The governing system framework brings a new perspective to SDIs and SDI theory and is a potentially useful analytical tool for SDI governors

Space-time information analysis for resource-conscious urban planning and design: A stakeholder based identification of urban metabolism data gaps

AbstractThe research presented here examined at which spatial and temporal resolution urban metabolism should be analysed to generate results that are useful for implementation of urban planning and design interventions aiming at optimization of resource flows. Moreover, it was researched whether a lack of data currently hampers analysing resource flows at this desired level of detail. To facilitate a stakeholder based research approach, the SIRUP tool – “Space-time Information analysis for Resource-conscious Urban Planning” – was developed. The tool was applied in a case study of Amsterdam, focused on the investigation of energy and water flows. Results show that most urban planning and design interventions envisioned in Amsterdam require information on a higher spatiotemporal resolution than the resolution of current urban metabolism analyses, i.e., more detailed than the city level and at time steps smaller than a year. Energy-related interventions generally require information on a higher resolution than water-related interventions. Moreover, for the majority of interventions information is needed on a higher resolution than currently available. For energy, the temporal resolution of existing data proved inadequate, for water, data with both a higher spatial and temporal resolution is required. Modelling and monitoring techniques are advancing for both water and energy and these advancements are likely to contribute to closing these data gaps in the future. These advancements can also prove useful in developing new sorts of urban metabolism analyses that can provide a systemic understanding of urban resource flows and that are tailored to urban planning and design

Interplay between land-use dynamics and changes in hydrological regime in the Vietnamese Mekong Delta

Policies supporting rice production and investments in water infrastructure enabled intensification and diversification of farming systems in the Vietnamese Mekong Delta (VMD) over the past 20 years. Yet, demands of food security, economic development, and climate change continue to pose diverging and often conflicting challenges for water resources management in the upper, central, and coastal zones of the delta. The major changes effected in the VMD’s hydrological regime and land-use patterns are acknowledged in the literature, but few studies have examined the interplay between these dynamics at the delta scale. Based on time-series maps and statistical data on land-use, flooding, and salinity intrusion, we investigated the interrelations between land-use dynamics and changes in hydrological regime across the VMD in three representative periods. Land-use was found to be highly variable, changing by 14.94% annually between 2001 and 2012. Rice cropping underwent the greatest change, evolving from single cropping of traditional varieties towards double and triple cropping of high-yielding varieties. Aquaculture remained stable after rapid expansion in the 1990s and early 2000s. Meanwhile, flooding and salinity intrusion were increasingly controlled by hydrological infrastructure erected to supply freshwater for agriculture. Effects of this infrastructure became particularly evident from 2001 to 2012. During this period, spatial and temporal impacts on flooding and salinity intrusion were found, which extended beyond the rice fields to affect adjacent lands and livelihood activities. Unforeseen effects will likely be aggravated by climate change, suggesting a need to rethink the scale of planning towards a more integrated hydrologic approach

Mapping land-use dynamic in the Vietnamese mekong delta

Policies supporting rice cultivation and investments in water infrastructures facilitated intensification and diversification of land-use in the Vietnamese Mekong Delta. Although the major changes are acknowledged in the literature, few studies have examined the dynamism of land-use across the delta. Overlaying land-use maps, we identified land-use dynamic by the number of changes observed during the 11-year study period. Land-use was found to be highly variable, changing by 14.94% annually between 2001 and 2012. Rice cropping underwent the greatest change, evolving from single cropping of traditional varieties towards double and triple cropping of highyielding varieties. A clear trend was observable in the upper delta, where large expanses of triple rice cropping, especially within the dyke systems. Changes in land-use were also observed in the central delta and coastal zone, but here the pattern was more fragmented. Meanwhile, aquaculture remained stable after rapid expansion in the early 2000s.</p

Formal and informal environmental sensing data and integration potential: Perceptions of citizens and experts

Environmental sensing data provide crucial information for environment-related decision-making. Formal data are provided by official environmental institutes. Beyond those, however, there is a growing body of so-called informal sensing data, which are contributed by citizens using low-cost sensors. How good are these informal data, and how might they be applied, next to formal environmental sensing data? Could both types of sensing data be gainfully integrated? This paper presents the results of an online survey investigating perceptions within citizen science communities, environmental institutes and their networks of formal and informal environmental sensing data. The results show that citizens and experts had different views of formal and informal environmental sensing data, particularly on measurement frequency and the data information provision power. However, there was agreement, too, for example, on the accuracy of formal environmental sensing data. Furthermore, both agreed that the integration of formal and informal environmental sensing data offered potential for improvements on several aspects, particularly spatial coverage, data quantity and measurement frequency. Interestingly, the accuracy of informal environmental sensing data was largely unknown to both experts and citizens. This suggests the need for further investigation of informal environmental sensing data and the potential for its effective integration with formal environmental sensing data, if hurdles like standardisation can be overcome

Data of Questionnaire on Formal and Informal Environmental Sensing

Data of Questionnaire on Formal and Informal Environmental Sensin

How is spatial information used in environmental impact assessment in Kenya?

Spatial information is being increasingly used worldwide within environmental impact assessment (EIA), although the extent of its use has not been exhaustively investigated. Using Kenya as a case study, EIA study reports submitted to the Environment Authority from 2002 to 2013 were investigated for the presence/absence of spatial presentations, levels of visual realism exhibited and content presented. Findings demonstrated a high popularity of spatial information, and preference for the combined use of spatial presentations with low and high levels of visual realism, with no clear preference for spatial presentations with either low or high levels of visual realism. A combination of project location and activities/details was the most popular content in the spatial presentations. Despite the lack of information, this study establishes that indeed spatial information is popular in Kenya and by doing so it sets the stage for further research on its specific use and value to EIA

New data sources for social indicators: the case study of contacting politicians by Twitter

Data availability is a persistent constraint in social policy analysis. Web 2.0 technologies could provide valuable new data sources, but first, their potentials and limitations need to be investigated. This paper reports on a method using Twitter data for deriving indications of active citizenship, taken as an example of social indicators. Active citizenship is a dimension of social capital, empowering communities and reducing possibilities of social exclusion. However, classical measurements of active citizenship are generally costly and time-consuming. This paper looks at one of such classic indicators, namely, responses to the survey question ‘contacts to politicians’. It compares official survey results in Spain with findings from an analysis of Twitter data. Each method presents its own strengths and weakness, thus best results may be achieved by the combination of both. Official surveys have the clear advantage of being statistically robust and representative of a total population. Instead, Twitter data offer more timely and less costly information, with higher spatial and temporal resolution. This paper presents our full methodological workflow for analysing and comparing these two data sources. The research results advance the debate on how social media data could be mined for policy analysis