TY - CONF
T1 - Sensitivity of brdf sampling to albedo and angle index based on airborne multiangle data
AU - Zhang, Xiaoning
AU - Jiao, Ziti
AU - Dong, Yadong
AU - Yin, Siyang
AU - Cui, Lei
AU - Zhang, Hu
AU - Ding, Anxin
AU - Chang, Yaxuan
AU - Xie, Rui
AU - Guo, Jing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019
Y1 - 2019
N2 - The surface anisotropy plays a key role in the quantitative remote sensing inversion, which is usually described as bidirectional reflectance distribution function (BRDF). Studies show that BRDF sampling has a significant effect on parameter inversion such as albedo. However, BRDF samplings are complex, and only specific samplings were considered in previous studies. In this study, we investigated the sensitivity of BRDF sampling to albedo and the normalized difference between hotspot and dark spot (NDHD) angular index based on the kernel-driven Ross-Li BRDF model. Albedo and NDHD calculated by a set of dense sampling airborne data were used as the reference data, and inversion results from many sparse samplings were compared to the reference results. The result shows the overall number, plane, range and symmetry in observing condition of BRDF sampling can affect albedo and NDHD estimation. Among typical sensors, POLDER shows best sampling while Landsat shows largest errors.
AB - The surface anisotropy plays a key role in the quantitative remote sensing inversion, which is usually described as bidirectional reflectance distribution function (BRDF). Studies show that BRDF sampling has a significant effect on parameter inversion such as albedo. However, BRDF samplings are complex, and only specific samplings were considered in previous studies. In this study, we investigated the sensitivity of BRDF sampling to albedo and the normalized difference between hotspot and dark spot (NDHD) angular index based on the kernel-driven Ross-Li BRDF model. Albedo and NDHD calculated by a set of dense sampling airborne data were used as the reference data, and inversion results from many sparse samplings were compared to the reference results. The result shows the overall number, plane, range and symmetry in observing condition of BRDF sampling can affect albedo and NDHD estimation. Among typical sensors, POLDER shows best sampling while Landsat shows largest errors.
KW - Albedo
KW - BRDF sampling
KW - NDHD
KW - The kernel-driven model
UR - http://www.scopus.com/inward/record.url?scp=85113862117&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2019.8900135
DO - 10.1109/IGARSS.2019.8900135
M3 - Paper
AN - SCOPUS:85113862117
SP - 6696
EP - 6699
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -