Accuracy Evaluation and Spatiotemporal Characteristics Analysis of Different MODIS Snow Products on the Northern Slope of the Tianshan Mountains
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P426.635

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    Abstract:

    Taking the northern slope of the Tianshan Mountains in Xinjiang as the study area, high-precision snow cover data at specific time benchmarks were generated based on the Landsat time-series sa-tellite images and the SNOMAP snow mapping algorithm. These data were used as "ground truth" to evaluate the data accuracy of three MODIS snow products: MODIS daily cloud-free snow cover 500 m product for China, MODIS daily cloud-free snow product for Northern Hemisphere, and MODIS snow cover index and phenology product for High Mountain Asia. Based on the evaluation results, the MODIS snow product with the highest accuracy was selected to analyze the snow cover frequency and its spatiotemporal variation characteristics in the region from 2001 to 2020. The results showed that: (1) The MODIS snow cover index and phenology product for High Mountain Asia had the highest accuracy, outperforming the other two products in terms of overall accuracy, underestimation error, snow classification accuracy, and Kappa coefficient; (2) The Intra-annual snow cover fraction in the northern slope of the Tianshan Mountains showed periodic changes, with peaks occurring from December to January of the following year and troughs occurring from June to August. The snow cover rate in areas above 4 500 meters above sea level was almost 100% in every month of the year; (3) The spatial distribution of the multi-year average snow cover frequency showed significant differences, with obvious east-west variations, which increased with rising altitude. The snow end date was significantly advanced in the eastern plains and near the Tianshan Mountains, highlighting the impact of climate warming on snow phenology.

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LI Wenhao, SONG Hongli, LIU Xingyu, ZHANG Xiaonan. Accuracy Evaluation and Spatiotemporal Characteristics Analysis of Different MODIS Snow Products on the Northern Slope of the Tianshan Mountains[J].,2026,43(2):93-102

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History
  • Received:October 10,2024
  • Revised:November 21,2024
  • Online: May 11,2026
  • Published: April 25,2026
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