EVALUATION OF BRDF ARCHETYPES FROM MODIS MULTI-ANGULAR OBSERVATIONS

被引:1
|
作者
Zhang, Hu [1 ]
Jiao, Ziti [1 ]
Dong, Yadong [1 ]
Li, Xiaowen [1 ]
机构
[1] Beijing Normal Univ & Inst Remote Sensing Applica, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
关键词
Albedo; BRDF archetype; MODIS; BIDIRECTIONAL REFLECTANCE; ALBEDO; ALGORITHM; SURFACE; MODELS;
D O I
10.1109/IGARSS.2014.6947552
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Bidirectional Reflectance distribution Function (BRDF) archetype database[1] briefly summarize reflectance anisotropy into six BRDF archetypes. To evaluate the representation of BRDF archetypes from reflectance anisotropy, the shapes of BRDF archetypes are compared with according MODIS product; then the albedos and the Root Mean Square Errors (RMSE) retrieved from BRDF archetypes are compared with MODIS retrievals, Comparisons show that the shapes of BRDF archetypes agree well with the according MODIS BRDF, and the albedos and RMSEs of BRDF archetype retrieval are close to MODIS product. These archetypes can represent the characteristics of reflectance anisotropy in the retrieval of albedo
引用
收藏
页数:4
相关论文
共 50 条
  • [21] TO RECONSTRUCT HOTSPOT EFFECT FOR MODIS BRDF ARCHETYPES USING A HOTSPOT-CORRECTED KERNEL-DRIVEN BRDF MODEL
    Jiao, Ziti
    Dong, Yadong
    Zhang, Hu
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 2654 - 2656
  • [22] Microwave Vegetation Index Derived from Multi-Angular Passive Microwave Observations at L-Band
    Chen, Liang
    Du, Jinyang
    Shi, Jiancheng
    [J]. 2008 INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND TRAINING AND 2008 INTERNATIONAL WORKSHOP ON GEOSCIENCE AND REMOTE SENSING, VOL 2, PROCEEDINGS,, 2009, : 396 - +
  • [23] Towards LPRM-based soil moisture retrievals with multi-angular microwave observations from SMOS
    Liu, S.
    Su, C. -H.
    Ryu, D.
    Kim, K.
    [J]. 21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015), 2015, : 2339 - 2345
  • [24] A DOWNSCALING APPROACH TO COMBINE SMOS MULTI-ANGULAR AND FULL-POLARIMETRIC OBSERVATIONS WITH MODIS VIS/IR DATA INTO HIGH RESOLUTION SOIL MOISTURE MAPS
    Piles, M.
    Vall-llossera, M.
    Laguna, L.
    Camps, A.
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 1247 - 1250
  • [25] Martian surface microtexture from orbital CRISM multi-angular observations: A new perspective for the characterization of the geological processes
    Fernando, J.
    Schmidt, F.
    Doute, S.
    [J]. PLANETARY AND SPACE SCIENCE, 2016, 128 : 30 - 51
  • [26] Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature
    Song, Lisheng
    Bian, Zunjian
    Kustas, William P.
    Liu, Shaomin
    Xiao, Qing
    Nieto, Hector
    Xu, Ziwei
    Yang, Yang
    Xu, Tongren
    Han, Xujun
    [J]. REMOTE SENSING OF ENVIRONMENT, 2020, 239
  • [27] Analysis of Extracting Prior BRDF from MODIS BRDF Data
    Zhang, Hu
    Jiao, Ziti
    Dong, Yadong
    Du, Peng
    Li, Yang
    Lian, Yi
    Cui, Tiejun
    [J]. REMOTE SENSING, 2016, 8 (12):
  • [28] Retrieval of time series three-dimensional landslide surface displacements from multi-angular SAR observations
    Xuguo Shi
    Lu Zhang
    Chao Zhou
    Menghua Li
    Mingsheng Liao
    [J]. Landslides, 2018, 15 : 1015 - 1027
  • [29] Aerosol properties from multi-spectral and multi-angular aircraft 4STAR observations: Expected advantages and challenges
    Kassianov, Evgueni
    Flynn, Connor
    Redemann, Jens
    Schmid, Beat
    Russell, Philip B.
    Sinyuk, Alexander
    [J]. REMOTE SENSING OF CLOUDS AND THE ATMOSPHERE XVII; AND LIDAR TECHNOLOGIES, TECHNIQUES, AND MEASUREMENTS FOR ATMOSPHERIC REMOTE SENSING VIII, 2012, 8534
  • [30] Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling
    Talebiesfandarani, Somayeh
    Zhao, Tianjie
    Shi, Jiancheng
    Ferrazzoli, Paolo
    Wigneron, Jean-Pierre
    Zamani, Mehdi
    Pani, Peejush
    [J]. REMOTE SENSING, 2019, 11 (06):