基于非负矩阵分解的中红外地表特性光谱重建方法

doi:10.3964/j.issn.1000-0593(2024)02-0563-08

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摘要：在中红外遥感领域，高光谱地表反射率/发射率等地表特性具有极高的应用价值和应用需求，但利用卫星遥感手段难以获取吸收波段的高光谱地表反射/发射特性，且通过光谱重建获取全波段的地表特性方法仍存在很多问题。为解决中红外全波段地表特性光谱重建所面临的难题，基于约翰霍普金斯大学（Johns Hopkins University，JHU）地物波谱库和中分辨率成像光谱仪（MODIS）短波红外和中红外地表多光谱卫星产品，提出了一种利用非负矩阵分解（NMF）重建高光谱地表反射率的方法，对2.5~5.0 μm中红外光谱范围内的地表反射/发射率进行光谱重建，重建后的光谱分辨率可达10 nm。首先基于JHU地物波谱库选取4种典型地物类型（土壤、植被、人造材料和岩石），建立地物光谱库样本信息，再利用MODIS传感器光谱响应函数，根据等效计算公式将2.0~5.0 μm波段范围反射率结果重采样到10 nm光谱间隔、共301个波段，得到JHU地表反射率光谱数据集。对光谱数据集进行非负矩阵分解处理，提取4条端元向量光谱曲线，结合MODIS短波红外和中红外4个波段（2.13、3.75、3.96和4.05 μm）的全球月均地表反射率/发射率产品，可计算每个像元对应的权重系数向量，从而进行任意波段的光谱重建，得到全球范围内陆地5 km×5 km分辨率的月均地表反射率重建结果。同时为综合评价该光谱重建方法，从光谱数据集中提取MODIS短波红外和中红外4个波段（2.13、3.75、3.96和4.05 μm）的子数据集，计算对应的权重系数向量，进行2.0~5.0 μm光谱范围内的全波段的反射率光谱重建。重建结果对应的平均绝对误差优于0.01，平均相对误差优于10%，在只有MODIS卫星4个波段数据可用的低秩病态的情况下，可较好地满足光谱重建的精度要求。并且为满足重建结果可视化需求，基于网络地理信息系统（WebGIS）技术，利用Cesium框架，采用浏览器/服务器架构，搭建了二三维一体化可视化系统，将卫星底图、地形数据与光谱重建结果等集成展示，从而进行直观的多因素分析，为卫星产品的展示与验证提供支撑。

关键词：高光谱；非负矩阵分解；地表反射率；光谱重建；MODIS；WebGIS

Abstract：In the field of mid-infrared remote sensing, hyperspectral surface reflectance/emissivity has high application value and application demand. However, it is difficult to obtain hyperspectral surface reflectance/emission characteristics in absorption band by satellite remote sensing, and there are still many problems in the method of obtaining full band surface characteristics by spectral reconstruction. In order to solve the problem of mid-infrared full band spectral reconstruction of land surface characteristics, based on the Johns Hopkins University (JHU) surface spectrum library and moderate resolution imaging spectrometer (MODIS) short wave infrared and mid-infrared surface multi spectral satellite products, A method for hyperspectral surface reflectance reconstruction using nonnegative matrix factorization (NMF) is proposed. The spectral resolution of the reconstructed hyperspectral reflectance/emissivity in the mid-infrared range of 2.5~5.0 μm can reach 10 nm. Firstly, four typical types of ground objects (soil, vegetation, artificial materials and rocks) were selected based on the JHU spectral library to establish the sample information of surface features. Then, using the spectral response function of the MODIS sensor, the reflectance results of 2.0~5.0 μm band were resampled to 301 bands with 10 nm spectral interval according to the equivalent calculation formula to obtain the JHU surface reflectance spectrum data set. Four endmember vector spectral curves were extracted by non-negative matrix decomposition of the spectral data set. Combined with the global monthly average surface reflectance/emissivity products of MODIS short wave infrared and mid infrared bands (2.13, 3.75, 3.96 and 4.05 μm), the weight coefficient vector corresponding to each pixel can be calculated, and the spectrum reconstruction of any band can be carried out to obtain the global land 5 km×5 km resolution of the monthly mean surface reflectance reconstruction results. At the same time, in order to comprehensively evaluate the spectral reconstruction method, the sub datasets of MODIS short wave infrared and mid infrared bands (2.13, 3.75, 3.96 and 4.05 μm) were extracted from the spectral data set, and the corresponding weight coefficient vector results were calculated, and the full band reflectance spectral reconstruction in the spectral range of 2.0~5.0 μm was performed. The average absolute error and relative error of the reconstruction results are better than 0.01 and 10%, respectively, which can meet the accuracy requirements of spectral reconstruction under the condition that only MODIS satellite data of 4 bands are available. In order to meet the needs of visualization of reconstruction results, based on WebGIS (Web Geographic information system, WebGIS) technology, using cesium framework and browser/server architecture, a two-dimensional and three-dimensional integrated visualization system was built, which integrated satellite base map, terrain data and spectral reconstruction results, to conduct intuitive multi-factor analysis, It provides support for the demonstration and verification of satellite products.

Key words：Hyperspectral; Non-negative matrix factorization; Surface reflectance; Spectral reconstruction; MODIS;WebGIS

收稿日期: 2022-09-07 修订日期: 2023-02-13

中图分类号:

TP79

基金资助: 国家杰出青年科学基金项目（41925019），国家自然科学基金项目（41871269）资助

通讯作者: 李正强 E-mail: lizq@radi.ac.cn

作者简介: 李殷娜，女，1998年生，中国科学院空天信息创新研究院硕士研究生 e-mail: liyinna20@mails.ucas.ac.cn

引用本文:

李殷娜，李正强，郑杨，侯伟真，徐文斌，马䶮，樊程，葛邦宇，姚前，史正. 基于非负矩阵分解的中红外地表特性光谱重建方法[J]. 光谱学与光谱分析, 2024, 44(02): 563-570.
LI Yin-na, LI Zheng-qiang, ZHENG Yang, HOU Wei-zhen, XU Wen-bin, MA Yan, FAN Cheng, GE Bang-yu, YAO Qian, SHI Zheng. Spectral Reconstruction Method of Mid-Infrared Surface Characteristics Based on Non-Negative Matrix Factorization. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(02): 563-570.

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