自然资源遥感2024，Vol.36Issue(3)：13-27,15.DOI:10.6046/zrzyyg.2023065
积雪遥感监测产品研究与应用进展
Advances in research and application of remote sensing-based snow monitoring products
摘要
Abstract
Snow proves to be both an important factor in characterizing the surface cryosphere and a critical parameter for weather and hydrological phenomena.Employing remote sensing to conduct long-term and large-scale monitoring of snow morphologies and their changes plays a vital role in research into global climate change,investigations into hydrology and water resources,and geological disaster prevention.After decades of development,significant progress has been made in the field of remote sensing-based snow monitoring technology both in China and abroad.Accordingly,the products for remote sensing-based snow monitoring have become increasingly abundant,and the snow-orientated inversion algorithms have been continuously improved.This paper provides a summary of the existing,widely applied products after categorizing them into three types:snow-cover extent(SEC),snow coverage,and snow depth/snow water equivalent(SWE)products.Furthermore,this study organizes the commercialized remote sensing inversion algorithms used in existing,typical SEC and SWE products.The review of advances in the relevant scientific research reveals that,with the constant presence of sensors with high temporal and spatial resolutions in China and abroad and the support of both novel optical and microwave data sources and new technologies,researchers have gradually improved the accuracy of snow-orientated inversion algorithms by optimizing these algorithms based on regional characteristics.This will provide more support for continuously improving remote sensing-based snow monitoring products in the future.关键词
积雪遥感监测产品/积雪覆盖/雪水当量/积雪反演算法Key words
remote sensing-based snow monitoring product/snow cover/SWE/snow-orientated inversion algo-rithm分类
信息技术与安全科学引用本文复制引用
孙禧勇,刘稼丰,范景辉,张文凯,石利娟,邱玉宝,朱发容..积雪遥感监测产品研究与应用进展[J].自然资源遥感,2024,36(3):13-27,15.基金项目
国家重点研发计划项目"高亚洲和北极积雪—冰川与地质灾害监测技术及示范应用"(编号:2021YFE0116800)资助. （编号:2021YFE0116800）
