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Abstract: Six examples are used to illustrate the potential for application-oriented landscape research in bridging human and natural sciences. The paper therefore examines: (i) uncertainty, (ii) data modelling, (iii) the role of scenarios, (iv) the use of process-oriented and participatory methods, (v) the development of an integrative framework. On the way from “data to decision” we start with data uncertainty in spatially explicit data. An assessment of critical loads in Southwest Germany in different spatial scales is examplified, and landscape research should make these data properties as clear and transparent as possible, e.g. with probability maps. In a next step, data modeling techniques like neural nets in a Geographical Information System (GIS) can improve the availability of maps and therefore spatial data—in our second case study we elaborated a synthetic soil map in the German region Hohenlohe out of various other data like geomorphology and elevation, as well as a reference soil map in an adjacent area. This shows how we can better exploit already existing data with new techniques. The third case study continues with genetic algorithms in order to predict the occurrence of species and habitats (here: heathlands) in the Hohenlohe area in Germany, and hence showing further techniques as well as methods in creating potentials and scenarios. How scenarios can be used to translate options from science to society in order to find a future as well as its implications for a landscape is shown in a next case study. Due to general complexity, we finally suggest to use indicators. On top of that, we developed an Information System to run scenarios for future land use in a municipality, and assess indicator values depending on the envisaged future. The Information System was then used in a participatory process, based in our case on a method from social science, in order to achieve high involvement and acceptance of people for decision making. The final step from data to decision is the development of an integrative framework, which we call Environmental Impact Assessment Multi-level Approach. We conclude that under such a framework it should be easier to bridge gaps between human and natural sciences for an application-oriented landscape research. [Copyright &y& Elsevier]