RAMSAR (2018): The use of Earth Observation for wetland inventory, assessment and monitoring

There is a growing awareness that data obtained from Earth Observation (EO) has the potential to provide the information needed for accurate wetland inventory, assessment and monitoring, and for updating a number of data fields in the Ramsar Sites Information Sheets (RIS). The latter includes: the physical features of the wetland, the presence and dominance of particular wetland types and factors affecting the ecological character of the wetland.

As with all current EO-based approaches, the identification of the location, extent and characteristics of any wetland may be limited by the availability of the specific data, including those related to the recognised limitations of optical imagery such as Landsat in cloud-covered tropical regions. Limitations to the use of EO for routinely deriving wetland information have included the cost of the technology, the technical capacity needed to use the data, the unsuitability of the available data for some basic applications (in particular in terms of the spatial and or temporal resolution of the data), the lack of clear, robust and efficient user-oriented methods, the absence of guidelines for using the technology, and a lack of case studies that are suitable for demonstrating how the technology can be applied in an operational manner. Other commonly reported limitations to the scaling-up and operational use of EO in wetland inventory, assessment and monitoring have included: restrictive data access policies; difficulties in discovering and accessing relevant datasets; a lack of standardisation in data analysis and applications; a lack of “fit for purpose” products; a frequency of observations insufficient to track wetlands changes at appropriate scales; the need for continuity of observations in the long-term; and insufficient training programmes for building EO capacities in the countries.

Although mapping of land cover and land uses are one of the most common uses of EO data, there are still challenges in assessing the current status and changes in wetlands over time. Monitoring historical trends and changing patterns of wetlands are complicated by the lack of medium to high-resolution data, in particular prior to 2000. While global thematic products are increasingly being made available, it should be noted that global datasets may not be able to provide the same high level of accuracy as a local scale map derived through ground surveys and the use of finer resolution (aerial, drones) geospatial data. A global area mapping exercise using consistent data and methods generally necessitates a trade-off in terms of local scale accuracy.

The advantages and limitations of EO approaches to the inventory, assessment and monitoring of wetlands in different environments is outlined through a series of case studies that address the following: i) tools and workflows, ii) global thematic datasets and iii) national scale replicable approaches available to the wetland community.

The case studies are presented as illustrative examples of the application of EO, but given a wide variance in local conditions and information needs they do not provide technical guidance for the specific application of any single approach. Such guidance is available through the agencies and organisations that are mentioned in the case studies, and through the specific references. This in itself reinforces the benefits that can accrue through a concerted and ongoing investment in local capacity and capability to apply EO in response to specific management needs. As global data sets become more readily available, the advantages of using EO for wetland inventory, assessment and monitoring are increasingly being realised, as shown through the case studies that have been presented, and it is anticipated that the usefulness of such approaches for reporting locally, nationally and internationally on the status and trends in wetlands will improve rapidly, including for reporting on wetland extent under the Sustainable Development Goals (SDGs)