Organizers: Gregory Giuliani and Birgitta Putzenlechner
Special Session's Summary Land Cover and Land Use (LCLU) is on the 14 Global Fundamental Geospatial Data Themes driving Sustainable Development. Incredible progress has been made in analyzing Big Data for better land monitoring. However, Land Cover characterization remains a major source of inconsistency and there is a lack of comparability between existing products. Numerous challenges remain to achieve the vision of transforming EO data into actionable knowledge by lowering the entry barrier to massive-use Big Earth Data analysis and derived information products. Consequently, it is crucial to support the development of effective means to build socially robust, transparent, accessible, replicable, and reusable knowledge, to generate decision-ready products based on Land Use & Land Cover data. In particular, the thematic expansion/intensification of ECVs and their impact assessment of LCLUC could be worth considering for several reasons. The current situation is that research on the intercomparison of diverse ECVs is still at its infancy while impact assessment of LCLUC regarding biogeophysical effects using ECVs is gaining importance to assess and understand global change. As satellite-derived ECVs become more available, they will also be used to analyze LULCC effects. Therefore, knowledge and integration of the uncertainties of individual ECVS will be of great importance. Ultimately, LCLU remote sensing is critical to contribute to applied research using powerful geospatial and statistical analyses with the objective to serve as a source of "actionable" and timely early warnings of emerging issues and environmental change, and related multi-scale assessments, based on scientific data, indicators, and real-time information, and helping to catalyze "evidence-based" responses. To reach this objective, we think that a paradigm shift is essential moving from traditional data-centric approaches to information- and knowledge-centric approaches. To fully realize the value chain of EO data, the Data-Information-Knowledge-Wisdom (DIKW) paradigm can facilitate evidence-based decision-making processes and inform us about Earth's limits. Therefore, exploring how best to apply DIKW on LCLUC would be valuable.