Estimating winter wheat Triticum aestivum LAI and leaf chlorophyll content from canopy reflectance data by integrating agronomic prior knowledge with the PROSAIL model

摘要: Leaf area index LAI and leaf chlorophyll content LCC are major considerations in management decisions, agricultural planning, policy-making. When a radiative transfer model RTM was used to retrieve these biophysical variables from remote-sensing data, the ill-posed problem unavoidable. In this study, we focused on use of agronomic prior knowledge APK, constructing relationship between LCC, restrict mitigate inversion results. For purpose, results obtained using SAILH+PROSPECT PROSAIL canopy reflectance alone no knowledge, NAPK those linked with APK were compared. The showed that had high accuracy. validation root mean square error RMSE measured estimated 0.74 0.69 for respectively. Compared NAPK, improved estimation; corresponding values 13.36 µg cm–2 9.35 µg cm–2, Our analysis confirms operational potential retrieval by integrating APK.