ausblenden:
Schlagwörter:
Vegetation, Hyperspectral sensors, Table lookup,Hyperspectral imaging, Performance evaluation,
Sampling methods, Remote sensing, Satellite broadcasting,
Radiometry, Monitoring
Zusammenfassung:
Leaf Area Index (LAI) and surface albedo (r) of maize, alfalfa, vineyard and chicory were estimated and validated with ground data acquired during the PLEIADeS field campaign in Sardinia, Italy, 2007. Hyperspectral field measurements were performed and spectral sampling of three commonly used sensors (Landsat-5 TM, SPOT5 and IKONOS) as well as the one for the future ESA Sentinel-2 satellite was simulated. LAI was retrieved with a radiative transfer model (RTM) based LUT inversion and two (semi-) empirical approaches using NDVI and WDVI. Surface albedo estimation was compared between the traditional weighting coefficient method and RTM simulation. LAI could be best estimated using the LUT approach based on the Sentinel-2 sensor configuration (RMSE = 0.59). For surface albedo, the physical model achieved the more realistic results compared to field measurements with a net radiometer. Results are discussed in view of operational monitoring applications for agriculture.
