@article {bnh-7479, title = {A global canopy water content product from AVHRR/Metop}, journal = {Remote Sensing}, volume = {162}, year = {2020}, month = {04/2020}, pages = {77-93}, abstract = {

Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational CWC product available to users. In the context of the Satellite Application Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board Meteorological{\textendash}Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the water conditions at the leaf level and information related to canopy structure. An accuracy assessment of the EPS/AVHRR CWC indicated a close agreement with multi-temporal ground data from SMAPVEX16 in Canada and Dahra in Senegal, with RMSE of 0.19\ kg\ m-2\ and 0.078\ kg\ m-2\ respectively. Particularly, when the Normalized Difference Infrared Index (NDII) was included the algorithm was better constrained in semi-arid regions and saturation effects were mitigated in dense canopies. An analysis of spatial scale effects shows the mean bias error in CWC retrievals remains below 0.001\ kg\ m-2\ when spatial resolutions ranging from 20\ m to 1\ km are considered. The present study further evaluates the consistency of the LSA-SAF product with respect to the Simplified Level 2 Product Prototype Processor (SL2P) product, and demonstrates its applicability at different spatio-temporal resolutions using optical data from MSI/Sentinel-2 and MODIS/Terra \& Aqua. Results suggest that the LSA-SAF EPS/AVHRR algorithm is robust, agrees with the CWC dynamics observed in available ground data, and is also applicable to data from other sensors. We conclude that the EPS/AVHRR CWC product is a promising tool for monitoring vegetation water status at regional and global scales.

}, keywords = {AVHRR/MetOp, Canopy Water Content (CWC), EUMETSAT, Gaussian Process Regression (GPR), MODIS, Polar System (EPS), Sentinel-2}, doi = {https://doi.org/10.1016/j.isprsjprs.2020.02.007}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0924271620300411}, author = {Francis Javier Garcia-Haro and Manuel Campos-Taberner and Alaro Moreno and Hakan Torbern Tagesson and Fernando Camacho and Beatriz Martinez and Sergio Sanchez and Maria Piles and Gustau Campas-Valls and Marta Yebra and Maria Amparo Gilabert} }