The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Urban land growth in eastern China: a general analytical framework based on the role of urban micro-agents' adaptive behavior
As one of the world regions with the most rapid economic growth and urbanization, eastern China faces many challenges during its urbanization process. The growth is characterized by the broad-scale loss of agricultural land, and by complex and unplanned urban growth, both of which threaten the future sustainability of the regional economy. The goal of this research is to investigate the changes within the driving forces behind the urban growth and to explore an analytical framework that explains the process. In particular, we discuss the role of the behavior of individuals in driving urban growth from a micro-perspective and formalize a framework for understanding and modeling the mechanisms of urban growth in eastern China. We start with an analysis of the changes in the macro-environment and how they have affected the autonomy of individuals, followed by an examination of the role of adaptive behavior in driving urban growth. We then propose a general analytical framework composed of an agent system, an environment system, and a policy and planning system. We present a layout for these subsystems and discuss the interactions within and among the subsystems. Furthermore, we summarize the common elements of urban micro-agents' adaptive behavior into three stages: agent learning, agent decision-making, and agent action. We enrich the urban micro-agents' learning process by importing learning from past self-experience and from shared experiences. The results may be helpful in the further modeling of urban micro-agents' adaptive behavior for simulating urban growth in support of scientific urban planning.
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