Synergistic Potential of Optical and Radar Remote Sensing for Snow Cover Monitoring

被引:0
|
作者
Hidalgo-Hidalgo, Jose-David [1 ]
Collados-Lara, Antonio-Juan [2 ,3 ]
Pulido-Velazquez, David [1 ]
Fassnacht, Steven R. [1 ,4 ,5 ]
Husillos, C. [6 ]
机构
[1] Spanish Geol Survey, Water & Global Change Res, Granada 18006, Spain
[2] Univ Granada, Dept Civil Engn, Granada 18071, Spain
[3] Univ Jaen, Dept Geol, Jaen 23071, Spain
[4] Colorado State Univ, ESS Watershed Sci, Ft Collins, CO 80523 USA
[5] Cooperat Inst Res Atmosphere, Ft Collins, CO 80523 USA
[6] Spanish Geol Survey, Unit Dev & Disseminat Informat Syst, Granada 18006, Spain
关键词
snow-covered area; SAR; optical and radar; satellite; wet snow; snow; remote sensing; Iberian Peninsula; BOREAL FOREST CANOPY; CLIMATE-CHANGE; WET SNOW; SAR DATA; IMPACTS; ALGORITHM; MODEL; DYNAMICS; MAPS;
D O I
10.3390/rs16193705
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This research studies the characteristics of snow-covered area (SCA) from two vastly different sensors: optical (Moderate-Resolution Imaging Spectroradiometer, or MODIS, equipped on board the Terra satellite) and radar (Synthetic Aperture Radar (SAR) on-board Sentinel-1 satellites). The focus are the five mountain ranges of the Iberian Peninsula (Cantabrian System, Central System, Iberian Range, Pyrenees, and Sierra Nevada). The MODIS product was selected to identify SCA dynamics in these ranges using the Probability of Snow Cover Presence Index (PSCPI). In addition, we evaluate the potential advantage of the use of SAR remote sensing to complete optical SCA under cloudy conditions. For this purpose, we utilize the Copernicus High-Resolution Snow and Ice SAR Wet Snow (HRS&I SWS) product. The Pyrenees and the Sierra Nevada showed longer-lasting SCA duration and a higher PSCPI throughout the average year. Moreover, we demonstrate that the latitude gradient has a significant influence on the snowline elevation in the Iberian mountains (R2 >= 0.84). In the Iberian mountains, a general negative SCA trend is observed due to the recent climate change impacts, with a particularly pronounced decline in the winter months (December and January). Finally, in the Pyrenees, we found that wet snow detection has high potential for the spatial gap-filling of MODIS SCA in spring, contributing above 27% to the total SCA. Notably, the additional SCA provided in winter is also significant. Based on the results obtained in the Pyrenees, we can conclude that implementing techniques that combine SAR and optical satellite sensors for SCA detection may provide valuable additional SCA data for the other Iberian mountains, in which the radar product is not available.
引用
收藏
页数:23
相关论文
共 50 条
  • [41] Towards Forecasting Future Snow Cover Dynamics in the European Alps-The Potential of Long Optical Remote-Sensing Time Series
    Koehler, Jonas
    Bauer, Andre
    Dietz, Andreas J.
    Kuenzer, Claudia
    REMOTE SENSING, 2022, 14 (18)
  • [42] Improving snow retrieval performance by fusing multiple snow cover remote sensing data
    Dong, Huaiwei
    Gao, Yang
    Zhao, Chen
    INTERNATIONAL CONFERENCE ON ENVIRONMENTAL REMOTE SENSING AND BIG DATA (ERSBD 2021), 2021, 12129
  • [43] Inference of snow cover beneath obscuring clouds using optical remote sensing and a distributed snow energy and mass balance model
    Cline, DW
    Carroll, TR
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 1999, 104 (D16) : 19631 - 19644
  • [44] Dry and Wet Snow Cover Mapping in Mountain Areas Using SAR and Optical Remote Sensing Data
    He, Guangjun
    Feng, Xuezhi
    Xiao, Pengfeng
    Xia, Zhenghuan
    Wang, Zuo
    Chen, Hao
    Li, Hui
    Guo, Jinjin
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (06) : 2575 - 2588
  • [45] Remote sensing and snow monitoring: Application to flood forecasting
    Schjodt-Osmo, O
    Engeset, R
    OPERATIONAL WATER MANAGEMENT, 1997, : 83 - 87
  • [46] THE POTENTIAL OF SATELLITE REMOTE-SENSING OF SNOW OVER GREAT-BRITAIN IN RELATION TO CLOUD COVER
    ARCHER, DR
    BAILEY, JO
    BARRETT, EC
    GREENHILL, D
    NORDIC HYDROLOGY, 1994, 25 (1-2) : 39 - 52
  • [47] RADAR AND OPTICAL MODELLING OF FOREST REMOTE SENSING
    Albinet, C.
    Borderies, P.
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 7181 - 7184
  • [48] Studying snow cover in European Russia with the use of remote sensing methods
    Telegina, A. A.
    REMOTE SENSING AND GIS FOR HYDROLOGY AND WATER RESOURCES, 2015, 368 : 40 - 45
  • [49] Automated Classification of Terrestrial Images: The Contribution to the Remote Sensing of Snow Cover
    Salzano, Roberto
    Salvatori, Rosamaria
    Valt, Mauro
    Giuliani, Gregory
    Chatenoux, Bruno
    Ioppi, Luca
    GEOSCIENCES, 2019, 9 (02)
  • [50] SURVEY PAPER ON REMOTE SENSING TECHNIQUES TO MAP SNOW COVER.
    Barnes, James C.
    Alternative Energy Sources: Proceedings of the Miami International Congress on Energy and the Environment, 1981, 1 : 123 - 132