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Arid Land Geography ›› 2022, Vol. 45 ›› Issue (3): 763-773.doi: 10.12118/j.issn.1000-6060.2021.347

• Hydrology and Water Resources • Previous Articles     Next Articles

Ice-water classification in Inner Mongolia reach of the Yellow River based on remote sensing images

ZHAI Yongguang1(),ZHANG Xin1,JI Honglan1(),MOU Xianyou1,ZHANG Baosen2   

  1. 1. College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, Inner mongolia, China
    2. Yellow River Institute of Hydraulic Research, Zhengzhou 450003, Henan, China
  • Received:2021-08-03 Revised:2021-10-10 Online:2022-05-25 Published:2022-05-31
  • Contact: Honglan JI E-mail:ychia@imau.edu.cn;honglanji@sina.com

Abstract:

Timely delivery of detailed information on the spatial distribution of river ice during ice-flood season is highly valuable for predicting, and improving communication on, ice disaster. Remote sensing technology provides a key method for obtaining the spatial distribution of river ice. However, the large amount of suspended sediment in the Yellow River represents a challenge to high-precision discrimination between ice and water based on remote sensing technology. Taking the Inner Mongolia reach of the Yellow River as an example, this study compares and evaluates the performance of five indices in the classification of river ice and water: near-infrared reflectance; normalized difference water index (NDWI); normalized difference snow index (NDSI); improved normalized snow index (MNDSI); and normalized difference unfrozen water index (NDUWI). The overall classification accuracy and Kappa coefficient (a measure of reliability) were calculated for each index, and the threshold stability of each index was analyzed. The results show that NDUWI achieves the highest accuracy and reliability (Kappa coefficient) in each studied subregion. The overall classification accuracy and Kappa coefficient of NDUWI are more than 90.0% and 0.90, respectively, and the optimal discrimination threshold between river ice and ice-free water is close to the median value. These results can provide a basis for the selection of ice monitoring methods and optimization of ice-blasting locations on the Yellow River during ice-flood season.

Key words: river ice, remote sensing index, threshold stability, uncertainty, Landsat 8, Inner Mongolia reach of the Yellow River