WMO:an ontology for the semantic enrichment of wetland monitoring data

Rich observation data generated by ubiquitous sensors are vital for wetland monitoring,spanning from the prediction of natural disasters to emergency response.Such sensors use different data acquisition and description methods and,if combined,could provide a comprehensive description of the wetland.Unfortunately,these data remain hidden in isolated silos,and their variety makes integration and interoperability a significant challenge.In this work,we develop a semantic model for wetland monitoring data using an agile and modular approach,namely,wetland monitoring ontology(WMO),which containsfive modules:wetland ecosystem,monitoring indicator,monitoring context,geospatial context,and temporal context.The proposed ontology supports the semantic interoperability and integration of wetland monitoring data from multiple sources,domains,modes,and spatiotemporal scales.We also provide two real-world use cases to validate the WMO and demonstrate the WMO’s usability and reusability.

Integrating Wintering Waterbird Movements with Earth Observation Data of Wetland Dynamics

Wetlands are among the most productive and essential ecosystems on earth,but they are also highly sensitive and vulnerable to climate change and human disturbance.One of the current scientific challenges is to integrate high-resolution remote sensing data of wetlands with wildlife movements,a task we achieve here for dynamic waterbird movements.We demonstrate that the White-naped cranes Antigone vipio wintering at Poyang Lake wetlands,southeast of China,mainly used the habitats created by the dramatic hydrological variations,i.e.seasonal water level fluctuation.Our data suggest that White-naped cranes tend to follow the water level recession process,keeping close to the boundary of water patches at most of the time.We also highlight the benefits of interdisciplinary approaches to gain a better understanding of wetland ecosystem complexity.

A database of global wetland validation samples for wetland mapping

A database of global wetland validation samples （GWVS） is the foundation for wetland mapping on a global scale. In this work, a database of GWVS was created based on 25 “wetland-related” keyw ord searches of a total of 3,506 full-text documents downloaded from the Web of Science. Eight hundred and three samples from a total of 68 countries and 14i protected areas were recorded by the GWVS, including samples of marine/coastal wetlands, inland wet- lands and human-made wetlands, at ratios of 53 %, 41% and 6 %, respectively. The results exhibit spatial distribution among Terrestrial Ecoregions of the World, the World Database on Protected Areas and the Database of Global Administrative Areas. Within most of the biomes, protected areas and countries examined, the very low concentration of samples requires more attention in the future. The greatest concentration of samples within a single biome is found in the tropical and subtropical moist broadleaf forest biome, accounting for 27 % of the total samples, while no sample is found in the biome of tropical and subtropical coniferous woodland. Greater efforts are expected to be made to record samples in Oceania, Central Europe, Northern Europe, Northern Africa, Central Africa, Central America, the Caribbean, and midwestern South America. Our data show that it is feasible to map global wetlands using Landsat TM/ ETM＋ at 30-m resolution. The continued improvement of the GWVS sharing platform should be reinforced in the future, making a strong contribution to global wetland mapping and monitoring.