首页 >  2020, Vol. 24, Issue (6) : 701-716

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引用本文:

DOI:

10.11834/jrs.20209482

收稿日期:

2019-12-24

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测绘地物波谱本底数据库
钟守熠1,6,肖青1,6,闻建光1,6,郑兴明2,马明国3,5,屈永华4,郑柯1,池天河1,唐勇1,游冬琴1,郝大磊1,6,程娟1,6,贺敏1,6,姜涛2,晋锐3,姚晓婧1,赵理君1
1.中国科学院空天信息创新研究院 遥感科学国家重点实验室, 北京 100101;2.中国科学院东北地理与农业生态研究所, 长春 130102;3.中国科学院西北生态环境资源研究院, 兰州 730000;4.北京师范大学 地理学与遥感科学学院, 北京 100875;5.西南大学 地理科学学院, 重庆 400715;6.中国科学院大学 资源与环境学院, 北京 100049
摘要:

地物波谱特性是利用遥感进行建模反演和地物目标探测识别的理论基础,波谱数据库对于提高遥感应用水平有重要作用。为规范和丰富中国波谱数据库并促进其在测绘等领域的应用,依托国家科技性基础专项,建立了“测绘地物波谱本底数据库”,在数据规范编制、波谱数据采集实验与整编入库、地物波谱数据库建设和应用示范初步探索方面取得重要进展。在波谱数据采集和处理的标准规范方面,建立完善了测绘地物波谱与配套非波谱数据收集与汇总标准、测绘地物波谱和配套非波谱参数测试技术规范、测绘地物波谱库地物分类编码规范。依照项目制定的数据规范标准,对现有波谱数据进行了整编和入库,共计整编数据1.4万余条;组织实施了全国范围的典型地物波谱采集实验以及相应配套参数测量实验,主要试验类型包括典型地物波谱测量试验、定点时间序列测量试验、多尺度测量试验、全波段测量试验、参数控制测量试验和无人机观测试验等,共计获取地物波谱1.7万余条。特别是在华北和东北进行了全波段观测试验(可见光—近红外波(0.35—2.5 μm)、红外波段(3—15 μm)、微波波段(Ka、K、X、C、L波段)),获取冰雪、土壤、植被冠层、人工目标的全波段数据。为方便波谱数据的应用和共享,项目建设了包含3万余条数据的测绘地物波谱本底数据库(GOSPEL)及数据共享平台。依据地物波谱数据的类型和应用需求,形成了全波段典型地物波谱数据集、多角度光谱反射率数据集、多尺度典型地物反射率数据集、长时间系列波谱数据集等共25个特色数据集。基于测绘地物波谱本底数据库进行了地物分类、遥感机理模拟、遥感定量反演、遥感产品验证等方面的应用示范。

Design and realization of ground object background spectral library for surveying and mapping
Abstract:

The spectral characteristics of ground objects are the theoretical basis for target detection and identification using remote sensing. The spectral library plays an important role in improving the level of remote sensing applications. In this study, we established the “Ground Object Background Spectral Library for Surveying and Mapping (GOSPEL)” under the National Science and Technology Foundation Project to standardize and enrich China’s spectral database and promote its application in the fields of surveying and mapping. Notable progress was observed in the construction of the ground feature spectrum library, warehousing, and preliminary exploration of application demonstrations. Moreover, the Ground Spectral Spectrum and Supporting Non-spectral Data Collection and Summary Standards, Spectral and Supporting Non-spectral Parameter Test Technical Specifications, and Feature Classification Code Standards were established on the basis of the existing spectrum acquisition and processing specifications. Since the implementation of the project, more than 14,000 existing spectral data were compiled and stored in accordance with the data norms and standards formulated by the project. In addition, nationwide spectrum collection experiments were organized and implemented involving the major regions in China, which acquired more than 17,000 ground feature spectra. Full-band experiments (visible–near infrared, infrared, and microwave bands) were performed in north and northeast China to obtain full-band data of snow, soil, vegetation canopy, and artificial target. To facilitate the application and sharing of spectral data, a ground feature spectral database (i.e., GOSPEL) and a data sharing platform containing more than 30,000 data were constructed. Twenty-five datasets were formed according to the type of ground feature spectral data and application requirements, including full-band typical feature spectrum dataset, multi-angle spectral reflectance dataset, multiscale typical feature reflectance dataset, and long-term series spectral dataset. We also performed application demonstrations on ground feature classification, remote sensing mechanism simulation, remote sensing quantitative inversion, and remote sensing product validation based on the current ground feature spectrum from GOSPEL.

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