Vegetation and land cover characterization

Vegetation and land cover are intrinsically coupled with the water cycle as the distribution and productivity of vegetation is controlled in part by the local water balance. Vegetation and land cover characterization products primarily address the geospatial information needs with regard to river basin characterization, environmental management and sustainable land and water management practices. This thematic information also bears important perspectives for hydrological management, e.g. in the form of runoff and river discharge modelling.

Timely information on land cover is needed in order to assess major changes occurring within a given basin, and in turn develop management strategies to address them. The methodologies employed in the characterization and monitoring of vegetation and land cover vary, based on objectives and scale of study, sensor and environmental setting. Consequently, this service aims to provide a flexible and adaptable approach rather than a rigid methodology that could not reflect the specific nature of a basin.

Known Limitations

The classification of basin wide land cover from high resolution satellite imagery can be labour intensive, time consuming and expensive. This often prevents the frequent, regular repetition needed for a continuous monitoring of land cover changes. The basin scale is therefore a limiting factor in the choice of satellite image resolution used for the classification methodology. Cloud cover and inter and intra-annual variations in soil moisture and vegetation water content are factors that negatively influence the accuracy of VLC characterization.

Future Enhancements

This service aims to exploit the benefits of innovative features of the Sentinel missions 1-3 in order to overcome known limitations related to cloud cover and inter and intra-annual variations in soil moisture and vegetation water content, which influence surface spectral properties. Having more dense image time series, covering a wide range of radiometric and spatial resolutions will help overcome these challenges.