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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Africa's participation in Digital Earth is uneven. There is a tendency to ascribe this state to prevailing governance and cultural challenges in Africa. However, foreign actors such as donors have an apparent role in shaping geospatial policies and outcomes. Thus far, the complex linkages between external aid and improved social and environmental monitoring and decision-making have been handled as a kind of ‘black box’. To better understand the situation, we open the box and focus on the interaction between donors and policy-makers. We use a heuristic from political science, as well as empirical evidence, to describe the policy-influencing tools that donors employ based on four basic resources donors possess: organization, authority, treasure, and nodality. We show an evolution of tool usage as donors shift from ‘old aid’ to ‘new aid’ modalities. The new tools include: technical assistance for geospatial curriculum development, inscription of standards and data access requirements in contracts and grants, cross-agency project design, best-practice analysis, portfolio management, and the use of language to promote participation and accountability. Though these tools reflect donor intent to partner in the realization of Digital Earth, the tools stem from a persisting asymmetric power dynamic between donors and policy-makers. [ABSTRACT FROM PUBLISHER]