基于多源卫星数据的积雪BRDF模型评估分析

唐冰倩; 张玉常; 奥勇; 牛云峰; 张文娟

doi:10.7523/j.ucas.2025.061

中国科学院大学学报 >

0 251231

DOI: https://doi.org/10.7523/j.ucas.2025.061

基于多源卫星数据的积雪BRDF模型评估分析

唐冰倩 ,
张玉常 ,
奥勇 ,
牛云峰 ,
张文娟

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1.中国科学院空天信息创新研究院,北京 100094;
2.长安大学土地工程学院,西安 710054;
3.火箭军某代表室,北京 100192

†E-mail：niuyf@aircas.ac.cn

收稿日期: 2025-07-21

修回日期: 2025-12-05

网络出版日期: 2025-12-29

基金资助

*青年科学基金（C类 42201503）资助

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Evaluation and analysis of snow BRDF model based on multi-source satellite data

TANG Bingqian ,
ZHANG Yuchang ,
AO Yong ,
NIU Yunfeng ,
ZHANG Wenjuan

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1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
2 School of Land Engineering, Chang'an University, Xi'an 710054, China;
3 A representative office of the Rocket Army, Beijing 100192, China

Received date: 2025-07-21

Revised date: 2025-12-05

Online published: 2025-12-29

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摘要

积雪具有高反射率和显著的反射各向异性,其在气候变化、全球辐射能量平衡中发挥重要作用。为提升积雪遥感信息提取和反射特性反演精度,本研究基于多角度POLDER数据和单角度MODIS数据,系统评估了ART、RTLSRS和FASMAR 3种典型BRDF模型在不同类型卫星数据源及积雪状态（稳定期与变化期）下的适用性和精度。结果表明：以POLDER数据为数据源时,3种模型均能较好地拟合不同状态积雪的反射特性,其中RTLSRS拟合精度最高,FASMAR次之,ART在前向大角度观测条件下反射率出现低估;采用MODIS数据为数据源时,在积雪状态稳定期,RTLSRS和FASMAR模型的模拟精度优于ART模型。在积雪状态变化期,核驱动模型RTLSRS和FASMAR模型误差增大,而ART模型仅利用单日数据即可开展反演,且精度更高,但其在短波红外波段处拟合误差较大。

关键词： 积雪; 反射率; 二向性反射率分布函数（BRDF）; POLDER; MODIS

本文引用格式

唐冰倩 , 张玉常 , 奥勇 , 牛云峰 , 张文娟 . 基于多源卫星数据的积雪BRDF模型评估分析[J]. 中国科学院大学学报, 0 : 251231 . DOI: 10.7523/j.ucas.2025.061

Abstract

Snow exhibits high reflectivity and significant reflective anisotropy, playing an important role in climate change and the global radiation energy balance. To improve the accuracy of snow cover information extraction and reflectance property inversion from remote sensing data, this study comprehensively assessed three typical BRDF models—ART, RTLSRS, and FASMAR—using multi-angle POLDER data and single-angle MODIS data under different snow conditions (stable and changing periods). The results show that when using POLDER data as the source, all three models can effectively fit the reflective characteristics of snow in different states. Among them, RTLSRS achieves the highest fitting accuracy, followed by FASMAR, while ART tends to underestimate reflectivity under large forward observation angles. When using MODIS data as the source, during the stable snow state period, the simulation accuracy of the RTLSRS and FASMAR models is better than that of the ART model. During the changing snow state period, the errors of the kernel-driven models RTLSRS and FASMAR increase, whereas the ART model, capable of performing inversions with single-day data, demonstrates better accuracy, though it exhibits larger fitting errors in the shortwave infrared band.

Key words： Snow; Reflectance; Bidirectional reflectance distribution function (BRDF); POLDER; MODIS

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