Land management, the organisation of the use and development of land, is an important instrument for addressing problems of rising greenhouse gas emissions and loss of natural resources. Yet, natural-social systems in which land management policies are implemented are poorly understood, thus decreasing the effectiveness of these policies. Local studies provide valuable insights, though only for the local conditions prevalent during the investigated period. Synthesising local studies in order to generalise results is impaired by the variety of local conditions. Collaborative research programmes may prevent some of these problems. They support the share of insights across temporal, ecological and spatial-economic contexts. On the basis of existing literature, we identify the challenges which face synthesis and demonstrate how a German research programme attempts to address some of them.

The spatial analysis functionalities of geographic information systems (GIS) are increasingly used across the web. Interface specifications of geoprocessing web services define the syntactic properties of the services (number and type of parameters) and provide textual descriptions of the operations. The discovery and reuse of web services based on these syntactic properties is restricted and has led to the quest for extended operation descriptions. A number of extended operation descriptions have been proposed and are reviewed in this article. The reviewed descriptions focus on particular steps of the workflow development process. In this article we analyse all phases of the development process of a spatial analysis workflow regarding the requirements of operation descriptions. These requirements are translated into a knowledge base that contains information about spatial analysis operations for the operations’ discovery, selection and composition. The knowledge base also foresees the automated discovery of operations in well-defined application contexts such as the transformation of data types or coordinate reference systems. The knowledge base combines the geooperator approach with elements of ontology-based approaches. The geooperator browser is the implementation of the discovery and selection of geoprocessing operations based on the knowledge base. A draft formalization of the knowledge base demonstrates its use and the support it provides during the composition of operations.

Based on various experiences in developing Geodata Infrastructures (GDIs) for scientific applications, this article proposes the concept of a Scientific GDI that can be used by scientists in environmental and earth sciences to share and disseminate their research results and related analysis methods. Scientific GDI is understood as an approach to tackle the science case in Digital Earth and to further enhance e-science for environmental research. Creating Scientific GDI to support the research community in efficiently exchanging data and methods related to the various scientific disciplines forming the basis of environmental studies poses numerous challenges on today's GDI developments. The paper summarizes requirements and recommendations on the publication of scientific geospatial data and on functionalities to be provided in Scientific GDI. Best practices and open issues for governance and policies of a Scientific GDI are discussed and are concluded by deriving a research agenda for the next decade.

Dynamic processes in society and demographics require a rapid response and adaptation of the existing public service infrastructure. Responsible planners must be able to analyse the situation, identify gaps in provision and derive decisions. The paper presents a web application that supports finding answers to various questions and planning decisions in the context of public service infrastructures (e.g., schools, pharmacies, supermarkets). Due to the high complexity, the combination of multi-criteria decision analysis and geographical information systems, especially in the web context, is still rarely implemented. With this spatial decision support system, we are pursuing an approach that makes multi-criteria analyses with spatially explicit methods available to the planning domain. By using this application, the user can select and adjust input parameters independently and thus strongly influence the analysis process and results—without a deep knowledge of decision-making methods or software skills. With such a centrally provided online multi-criteria spatial decision support system, the transparency and the quality of the analysis increase, while the workload for the planners is reduced, since they no longer have to spend time on preliminary data search and integration or on building complex methods and models themselves.