Results 31 to 40 of about 5,611 (211)

BRDFs acquired by directional radiative measurements during EAGLE and AGRISAR [PDF]

, 2008
Radiation is the driving force for all processes and interactions between earth surface and atmosphere. The amount of measured radiation reflected by vegetation depends on its structure, the viewing angle and the solar angle. This angular dependence is
Vekerdy, Zoltán, Tol, C van der, Weligepolage, K., Timmermans, J., Jia, L., Su, Z.   +5 more
core   +1 more source

Relationship between Light Use Efficiency and Photochemical Reflectance Index Corrected Using a BRDF Model at a Subtropical Mixed Forest

Remote Sensing, 2020
Light use efficiency (LUE) is a key indicator of vegetation photosynthesis, which provides important insights into how vegetation productivity responds to environmental conditions.
Li Ma, Shaoqiang Wang, Jinghua Chen, Bin Chen, Leiming Zhang, Lixia Ma, Muhammad Amir, Leigang Sun, Guoyi Zhou, Ze Meng   +9 more
doaj   +1 more source

Development of a High Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance with MODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China

Remote Sensing, 2015
A land-cover-based linear BRDF (bi-directional reflectance distribution function) unmixing (LLBU) algorithm based on the kernel-driven model is proposed to combine the compact airborne spectrographic imager (CASI) reflectance with the moderate resolution
Dongqin You, Jianguang Wen, Qing Xiao, Qiang Liu, Qinhuo Liu, Yong Tang, Baocheng Dou, Jingjing Peng   +7 more
doaj   +1 more source

Neural BRDFs: Representation and Operations

CoRR, 2021
Bidirectional reflectance distribution functions (BRDFs) are pervasively used in computer graphics to produce realistic physically-based appearance. In recent years, several works explored using neural networks to represent BRDFs, taking advantage of neural networks' high compression rate and their ability to fit highly complex functions. However, once
Jiahui Fan, Beibei Wang 0002, Milos Hasan, Jian Yang 0003, Ling-Qi Yan 0001   +4 more
openaire   +2 more sources

Java BRDF viewer

, 2002
A Bi-directional Reflection Distribution Function, BRDF, is a mathematical model used to reproduce a realistic reflection in computer generated graphics. To study the effects of BRDFs, one uses a BRDF viewer.
Chong, Randy Christopher
core   +3 more sources

Directional Applicability Analysis of Albedo Retrieval Using Prior BRDF Knowledge

Remote Sensing
Surface albedo measures the proportion of incoming solar radiation reflected by the Earth’s surface. Accurate albedo retrieval from remote sensing data usually requires sufficient multi-angular observations to account for the surface reflectance ...
Hu Zhang, Qianrui Xi, Junqin Xie, Xiaoning Zhang, Lei Chen, Yi Lian, Hongtao Cao, Yan Liu, Lei Cui, Yadong Dong   +9 more
doaj   +1 more source

BRDF Correction in Landsat Directional Reflectance Data by Combining Optimal BRDF Archetype With Spectral Characteristics

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The Landsat optical images have provided a unique long-term record of the terrestrial surface and have always been an important data source for earth observation.
Aojie Shen, Jie Shao, Xin Qi, Zhongzheng Zhu, Yujie Dai, Qi Zeng   +5 more
doaj   +1 more source

Radiometric Cross Calibration and Validation Using 4 Angle BRDF Model between Landsat 8 and Sentinel 2A

Remote Sensing, 2020
This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors.
M M Farhad, Morakot Kaewmanee, Larry Leigh, Dennis Helder   +3 more
doaj   +1 more source

Field Reflectance Measurements at Night of Beach and Desert Sands within a Particulate BRDF Model

Remote Sensing, 2022
The Bidirectional Reflectance Distribution Function (BRDF) of soils is frequently assumed to be Lambertian in remote sensing applications, even though many soils are observed to have a distinct backscatter.
John E. Wise, John C. Mars
doaj   +1 more source

Learning to Learn and Sample BRDFs

Computer Graphics Forum, 2023
AbstractWe propose a method to accelerate the joint process of physically acquiring and learning neural Bi‐directional Reflectance Distribution Function (BRDF) models. While BRDF learning alone can be accelerated by meta‐learning, acquisition remains slow as it relies on a mechanical process.
Chen Liu 0029, Michael Fischer 0011, Tobias Ritschel 0001   +2 more
openaire   +3 more sources