TY  - Data
T1  - ChinaAI-FSC: A Comprehensive AI-Ready MODIS Fractional Snow Cover Dataset for China (2000-2022)
A1  - Hou Jinliang
A1  - HuangChunling
A1  - Zhang Ying
DO  - 10.5281/zenodo.17707386
PY  - 2026
DA  - 2026-03-18
PB  - National Cryosphere Desert Data Center
AB  - ChinaAI-FSC, the first large-scale, standardized, AI-ready fractional snow cover (FSC) sample collection for China, spanning 22 snow seasons from 2000 to 2022 and addressing a critical gap in long-term snow monitoring. The dataset consists of 47,728 samples (each 128×128 MODIS-pixel tiles),  enable both point-scale and tile-scale spatially contextualized AI modelling. A structured and transparent workflow, encompassing systematic sample preparation, rigorous quality control, spatiotemporal sample partitioning, and standardized metadata, ensures reproducibility, physical consistency, and interoperability across machine learning and deep learning applications. Dataset reliability and AI-readiness were systematically evaluated using a novel “Four Layers-Four Domains-Fifteen Attributes (4L-4D-15A)” assessment protocol, covering data, information, system, and application dimensions. The quality, reliability, and usability of ChinaAI-FSC were demonstrated through three representative use cases: (1) benchmarking of six ML/DL models (ANN, SVR, RF, CNN, UNet, and ResNet), (2) validation of the standard MODIS FSC product, and (3) nationwide seamless FSC mapping. By providing harmonized, validated, and well-documented samples, ChinaAI-FSC establishes a unified foundation for AI-driven snow cover mapping, long-term monitoring, and cryosphere–hydrological modelling, promoting reproducible, interoperable, and next-generation research in cryospheric science.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/e44b23cc-0aad-43ec-90c5-9eb1882c696f
ER  -