本数据集为中国陆域八天合成积雪反照率数据，时间范围覆盖2000年1月至2020年3月，为HDF格式的栅格数据。地理空间范围为72°-142°E，16°-56°N，采用等经纬度投影，空间分辨率0.01°。数据集基于MODIS反射率产品MOD09GA，积雪产品MOD10A1/MYD10A1和全球数字高程模型SRTM数据，在ART模型基础上发展了积雪反照率反演模型，并利用GEE和本地端交互生产而来，最后经过八天合成达到去云目的。数据要素包含黑空反照率，白空反照率，太阳天顶角，反演标识，云标识等。
", "ds_source": "MOD09GA是美国宇航局（NASA）的LP DAAC发布的反射率数据产品（L2G），在云端可直接调用；MOD10A1/MYD10A1是美国雪冰数据中心（NSIDC）发布的雪盖数据产品；SRTM是NASA/CGIAR发布的全球数字高程数据。
", "ds_process_way": "反演计算使用的模型：在ART模型基础上发展的积雪反照率反演模型。\n
软件工具：云端（GEE）和本地端（Python）交互生产，Jupyter Notebook用于8天合成去云，MATLAB用于数据格式转换，ArcPy用于缩略图生成。\n
误差控制、处理的方法：在每一幅产品中添加反演情况标识波段。
", "ds_quality": "数据质量良好。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国陆域", "ds_acq_lon_east": 142.0, "ds_acq_lat_south": 16.0, "ds_acq_lon_west": 72.0, "ds_acq_lat_north": 56.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 329784482967, "ds_files_count": 1933, "ds_format": "HDF", "ds_space_res": "1100", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "等经纬度投影", "ds_thumbnail": "d61a44bd-96ea-4555-9e54-c02a41210c4e.gif", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "aba68fe5-65d3-41b1-b036-bc274a834b5e", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2021-12-31 16:12:11", "last_updated": "2025-04-25 16:01:01", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.I-SNOW.2020.8", "i18n": { "en": { "title": "China 8-day Composite Snow Albedo Product (2000-2020)", "ds_format": "HDF", "ds_source": "
MOD09GA is a reflectance data product (L2G) released by NASA's LP DAAC, which can be directly recalled in the cloud.\n
MOD10A1/MYD10A1 is a snow cover data product released by the U.S. Snow and Ice Data Center (NSIDC); SRTM is a global digital elevation data released by NASA/CGIAR.", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
This dataset is an eight-day synthetic snow albedo data for the land area of China, covering the time range from January 2000 to March 2020, in raster data in HDF format. The geospatial range is 72°-142°E, 16°-56°N, and the equal latitude/longitude projection is used with a spatial resolution of 0.01°.\n
The dataset is based on MODIS albedo product MOD09GA, snow accumulation product MOD10A1/MYD10A1 and Global Digital Elevation Model SRTM data, and the snow accumulation albedo inversion model is developed on the basis of the ART model and produced interactively with GEE and the local end, and finally synthesized to achieve the purpose of de-cloud after eight days.\n
The data elements include black sky albedo, white sky albedo, solar zenith angle, inversion identifier, cloud identifier, and so on.
", "ds_time_res": "日", "ds_acq_place": "China's Land Territory", "ds_space_res": "1100", "ds_projection": "Equal latitude and longitude projection", "ds_process_way": "Model used for inversion calculations: snowpack albedo inversion model developed on the basis of the ART model.\n
Software tools: cloud (GEE) and local (Python) interactive production, Jupyter Notebook for 8-day synthetic de-clouds, MATLAB for data format conversion, ArcPy for thumbnail generation.\n
Methods for error control, processing: adding inversion case identification bands to each product.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "积雪反照率", "黑空反照率", "白空反照率", "太阳天顶角", "反演标识", "云标识" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国陆域" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "肖鹏峰", "email": "xiaopf@nju.edu.cn", "work_for": "南京大学", "country": "中国" }, { "true_name": "胡瑞", "email": "", "work_for": "南京大学", "country": "中国" }, { "true_name": "张正", "email": "", "work_for": "南京大学", "country": "中国" }, { "true_name": "秦棽", "email": "", "work_for": "南京大学", "country": "中国" }, { "true_name": "李震", "email": "lizhen@aircas.ac.cn", "work_for": "中国科学院空天信息创新研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "秦棽", "email": "", "work_for": "南京大学", "country": "中国" } ], "ds_managers": [ { "true_name": "肖鹏峰", "email": "xiaopf@nju.edu.cn", "work_for": "南京大学", "country": "中国" } ], "category": "积雪" }