Recently, the National Glacier, Frozen Soil and Desert Scientific Data Center released and shared products with long-term series of 500-meter daily snow cover ranges in China (1981 - 2000). The dataset was completed by the team of Professor Wang Xiaoyan of Lanzhou University and is open to users. The related paper is "A long-term daily 500m snow cover extensive product over China (1981 - 2000)" published in the journal Big Earth Data. Scientific researchers are warmly welcome to download and use it.

Snow cover is the most widely distributed and significantly changed member of the cryosphere. Its unique high albedo and low thermal conductivity make it play a key role in regulating surface energy budget, earth-atmosphere interactions and hydrological processes. Limited by the spatial resolution, temporal resolution and available time series of early sensors, there is still a lack of Snow Cover Extent (SCE) products with a spatial resolution of 500 meters before 2000. In order to fill this data gap, the research was based on the existing SCPOT (Similar Conditional Probability & OTSU) algorithm, extended it to the entire China, and improved some shortcomings in the original algorithm. First, using MODIS SCE and AVHRR SCE covering the same time period, the conditional probability of similarity (SCP) between images at different scales is calculated. Based on the 5km AVHRR SCE from 1981 to 2000, the downscaled products were generated under a series of post-processing.

This dataset has high stability and reliability in plains and areas with moderate terrain fluctuations. It can clearly depict the spatio-temporal distribution and seasonal and interannual variation characteristics of regional-scale snow cover. It can be used for cryosphere changes, climate dry and wet analysis, and Water Resources assessment and other related research provides high-quality, long-time series basic data support. In complex mountainous areas such as the Qinghai-Tibet Plateau, high-altitude mountainous areas, or application scenarios such as small watersheds and fine mapping that require high spatial accuracy, it is recommended to combine higher-resolution remote sensing images or ground measured data to carry out necessary local verification to further improve the accuracy and applicability of the analysis results. Overall, this dataset fills the gap in high-resolution daily snow cover data in historical periods, and has extensive applications in long-time series snow cover change monitoring, watershed hydrological process simulation, cryosphere and climate interaction research, ecological hydrological assessment and other fields. and important application potential.

The spatial resolution of this data product is 500m and the temporal resolution is 1 day. The data naming format is "YMMDD.tif", such as "19810626.tif", which contains six pixel values (0= land, 1=SCP identifies snow cover, 2= Space-Time Cube (STCPI) interpolated snow cover, 3= snow depth interpolated snow cover, 4= water body, 255= fill value).

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Figure 1 Spatial distribution of the study area, three typical snow accumulation areas, meteorological stations, and Landsat-5 validation data

Figure 2 Comparison of processing results in each downscaling step

Figure 3 Spatial distribution of downscaled SCE accuracy at each CMA station

Figure 4 Analysis of interannual variation and temporal continuity of snow cover area in different regions based on downscaled SCE and MODIS SCE data

[Project Support]

1. National Science Fund for Distinguished Young Persons: Snow Remote Sensing (42125604);

2. National Natural Science Foundation of China: Research on remote sensing monitoring methods for snowfall interception in forest canopies (42271373);

[Article Information]

Shen Yanlong, Wang Xiaoyan, Zhu Ruixiang, Liang Shi, Che Tao, Hao Xiaohua. A long-term daily 500 m snow cover extent product over China (1981–2000)[J/OL]. Big Earth Data, 2026, 0, (0): 1-32. DOI: 10.1080/20964471.2026.2648197.