@inproceedings{ac66dbcd993a409488683fcc7557bd1a,
title = "Analysis of anisotropy variance between the kernel-driven model and the PROSAIL model",
abstract = "The surface anisotropy characteristics have important significance in the quantitative remote sensing inversion. The kernel-driven model can express the surface anisotropy well and widely used in remote sensing, and the PROSAIL model is a mature vegetation canopy model which can describe complex vegetation structure, therefore studying surface anisotropy variance of the two models is a key point to combine them for further research. We simulate surface reflectance data with complex vegetation structure through the PROSAIL model, with the RossThick-LiSparseR(RTLSR) model and its extended model of Chen(RTCLSR) considering hotspot effect, we analyze anisotropy variance. The result shows: (1) The overall fitting effect is good, the average fitting RMSE is about 0.0071 in red band and 0.0342 in near infrared band; (2) AFX is sensitive to some vegetation structure parameters; (3) C1 and C2 in Chen model is inversely proportional to each other in different Hspot, while proportional in different LAI.",
keywords = "AFX, BRDF, hotspot, the Kernel-driven model, the PROSAIL model",
author = "Xiaoning Zhang and Ziti Jiao and Yadong Dong and Dongni Bai and Yang Li and Dandan He",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7730435",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5506--5509",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "United States",
}