A visualization tool for the kernel-driven model with improved ability in data analysis and kernel assessment

作者:Dong, YD (Dong, Yadong)[ 1,2 ] ; Jiao, ZT (Jiao, Ziti)[ 1,2,3 ] ; Zhang, H (Zhang, Hu)[ 4,5 ] ; Bai, DN (Bai, Dongni)[ 1,2 ] ; Zhang, XN (Zhang, Xiaoning)[ 1,2 ] ; Li, Y (Li, Yang)[ 1,2 ] ; He, DD (He, Dandan)[ 1,2 ]

COMPUTERS & GEOSCIENCES

卷: 95  页: 1-10

DOI: 10.1016/j.cageo.2016.06.010

出版年: OCT 2016

摘要

The semi-empirical, kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model has been widely used for many aspects of remote sensing. With the development of the kernel-driven model, there is a need to further assess the performance of newly developed kernels. The use of visualization tools can facilitate the analysis of model results and the assessment of newly developed kernels. However, the current version of the kernel-driven model does not contain a visualization function. In this study, a user-friendly visualization tool, named MaKeMAT, was developed specifically for the kernel driven model. The POLDER-3 and CAR BRDF datasets were used to demonstrate the applicability of MaKeMAT. The visualization of inputted multi-angle measurements enhances understanding of multi angle measurements and allows the choice of measurements with good representativeness. The visualization of modeling results facilitates the assessment of newly developed kernels. The study shows that the visualization tool MaKeMAT can promote the widespread application of the kernel-driven model. (C) 2016 Elsevier Ltd. All rights reserved.

通讯作者地址: Jiao, ZT (通讯作者)

Beijing Normal Univ, 19 Xinjiekouwai St, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China

[ 3 ] Beijing Normal Univ, Beijing Key Lab Environm Remote Sensing & Digital, Beijing 100875, Peoples R China

[ 4 ] Tianjin Normal Univ, Coll Urban & Environm Sci, Tianjin, Peoples R China

[ 5 ] Tianjin Engn Ctr Geospatial Informat Technol, Tianjin, Peoples R China