Snow grain-size estimation over mountainous areas from MODIS imagery

Jiangeng Wang, Xuezhi Feng, Pengfeng Xiao, Nan Ye, Xueliang Zhang, Yinyi Cheng

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Snow in mountainous areas is a major source of surface water and groundwater recharge in the world. The water balance in mountainous regions is controlled by the interactions between the climate, cryospheric, and hydrological systems. Surface snow grain is a sensitive thermodynamic indicator of snowpack and plays an important role in the snow albedo. In mountainous regions, the complicated terrain conditions may introduce errors in the snow grain size estimated from satellite imagery. In this letter, an effective method based on the Snow Grain-Size and Pollution (SGSP) amount algorithm is proposed to estimate the surface snow grain size with careful topographic correction, using spectral reflectance data in Channel 5 (1.24 μm) of the Moderate Resolution Imaging Spectrometer. The SGSP-estimated snow grain size was validated with in situ measurements collected from field campaigns in mountainous areas of Manasi River Basin, China, during the periods of snow accumulation and ablation from 2011 to 2015. The R2 value of 0.90 and root mean squared error of 80.42 μm were obtained.

Original languageEnglish
Pages (from-to)97-101
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Moderate resolution imaging spectrometer (MODIS)
  • Mountainous areas
  • Snow grain size
  • Snow grain-size and pollution (SGSP)

Cite this