CAJ | 학술논문

积雪作为冰冻圈主要组成部分,是全球能量和水循环的重要环节。利用卫星遥感技术获取的高时空分辨率的积雪分布和状态信息对寒区水资源管理、经济发展和社会稳定具有重要意义。目前,利用高分辨率光学和合成孔径雷达(Synthetic Aperture Radar,SAR)卫星数据能够实现积雪覆盖范围的识别和雪层物化参数的反演,但识别和反演的精度在高寒山区条件下受地形影响严重。为改进现有识别和反演模型在山区条件下的适应性,以新疆天山北坡玛纳斯河流域为研究区,分别在2013年冬季积雪期和2014年春季融雪期进行了两次与 SAR 卫星同步的野外积雪观测,为山区积雪识别和积雪参数反演获取了地面实测光谱和积雪参数数据。对两次积雪观测的目的、方法和初步结果进行介绍。观测初步结果显示了积雪在研究区内空间分布不均一,季节性差异性明显,为后续通过高分辨率遥感手段获取山区积雪参数时间和空间变异性提供了基础。
적설작위빙동권주요조성부분,시전구능량화수순배적중요배절。이용위성요감기술획취적고시공분변솔적적설분포화상태신식대한구수자원관리、경제발전화사회은정구유중요의의。목전,이용고분변솔광학화합성공경뢰체(Synthetic Aperture Radar,SAR)위성수거능구실현적설복개범위적식별화설층물화삼수적반연,단식별화반연적정도재고한산구조건하수지형영향엄중。위개진현유식별화반연모형재산구조건하적괄응성,이신강천산북파마납사하류역위연구구,분별재2013년동계적설기화2014년춘계융설기진행료량차여 SAR 위성동보적야외적설관측,위산구적설식별화적설삼수반연획취료지면실측광보화적설삼수수거。대량차적설관측적목적、방법화초보결과진행개소。관측초보결과현시료적설재연구구내공간분포불균일,계절성차이성명현,위후속통과고분변솔요감수단획취산구적설삼수시간화공간변이성제공료기출。
Snow is a key component in cryosphere,which plays a significant role in global energy and water cycles. The development of space-borne remote sensing techniques on monitoring snow cover and status distribution with high temporal and spatial resolution will benefit water resource management,economic growth,and social stability of cold areas.To date,snow cover area can be identified using high resolution optical sensor from the space,and physical properties of snow pack can be retrieved from Synthetic Aperture Radar (SAR)satellite observations.However,the accuracy of identification and retrieval is adversely affected by topography in mountainous areas.To improve the suitability of identification and retrieval models,two field experiments dedicated to snow remote sensing were conducted during the winter of 2013 and the spring of 2014 over a study area of Manas River Basin on north face of the Tianshan Mountains,Xinjiang Province.Intensive in-situ spectral and snow properties sampling were carried out coincident with the coverage of satellite observations.The objectives,methodology,and preliminary results of these two field experiments are presented in this paper.The preliminary results show a significant hetero-geneous distribution and seasonal variation of snow in the study area,and the potential of using high resolution remote sensing techniques to capture the temporal and spatial variability of mountainous snow.