本数据集是北半球逐日无云二值积雪产品资料，时间自2000年1月至2015年12月，数据包含了积雪和非雪两种地物类型。数据覆盖范围为0-86°N，180°W-180°E。该数据集的数据源使用的积雪产品是通过NSIDC网站下载的V005版本的每日积雪分类产品MOD10A1和MYD10A1，以及AMSR-E每日雪水当量产品和雪冰产品IMS。利用MOD10A1、MYD10A1、AMSR-E AWE和IMS原始数据，采用最大积雪面积融合方法，生成逐日无云二值积雪图像。
", "ds_source": "数据来自课题：国家重大科学研究计划“冰冻圈变化及其影响研究”\n
负责人:丁永建\n
单位：中国科学院寒区旱区环境与工程研究所\n
资助者：科技部\n
数据源使用的积雪产品是通过NSIDC网站下载的V005版本的每日积雪分类产品MOD10A1和MYD10A1，以及AMSR-E每日雪水当量产品和雪冰产品IMS。
", "ds_process_way": "利用MOD10A1、MYD10A1、AMSR-E AWE和IMS原始数据，采用最大积雪面积融合方法，生成逐日无云二值积雪图像\n
(1)数据生产过程：使用专门的图形工作站进行数据处理过程\n
(2)方法和标准规范: 采用最大积雪面积融合方法\n
(3)应用范围: 北半球\n
", "ds_quality": "该数据的原始数据为通过NSIDC网站下载的V005版本的每日积雪分类产品MOD10A1和MYD10A1，以及AMSR-E每日雪水当量产品数据，采用最大积雪面积融合方法，生成北半球逐日无云二值积雪产品，加工生成后的数据分辨率达到1km×1km。对合成的最终逐日积雪产品精度分析表明，积雪一致性达到87.1%，陆地一致性达到92%，总体分类精度为90.7%。
", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2015-12-31 00:00:00", "ds_acq_place": "北半球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 0.0, "ds_acq_lon_west": 180.0, "ds_acq_lat_north": 86.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 67336709161, "ds_files_count": 18, "ds_format": "*.tif", "ds_space_res": "1km*1km", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "GCS_WGS_1984", "ds_thumbnail": "daec254a-4434-4e17-b770-2ea8effd50da.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "由于本数据集测定时间不尽一致，指标繁杂，如需要详细原始数据者，请联系数据管理者。\r\n 联系信息：\r\n 联系人姓名：黄晓东\r\n Email: huangxd@lzu.edu.cn \r\n Tel: 0931-8912896", "ds_from_station": null, "organization_id": "b3c14ec7-0cc1-417f-8986-b6fc1352242f", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2020-12-03 08:55:15", "last_updated": "2026-05-26 16:51:25", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.CCI.2020.72", "i18n": { "en": { "title": "MODIS daily cloudless binary snow products in Northern Hemisphere from 2000 to 2015", "ds_format": "*.tif", "ds_source": "Data comes from the topic: \"Research on Cryosphere Changes and Their Impact\", a major national scientific research program\r\n
Person in charge: Ding Yongjian\r\n
Unit: Institute of Cold and Arid Regions Environment and Engineering, China Academy of Sciences\r\n
Funder: Ministry of Science and Technology\r\n
The snow products used by the data source are the V005 versions of the daily snow classification products MOD10A1 and MYD10A1 downloaded through the NSIDC website, as well as the AMSR-E daily snow water equivalent product and snow ice product IMS.
", "ds_quality": "The raw data of this data is the V005 version of the daily snow classification products MOD10A1 and MYD10A1 downloaded through the NSIDC website, and the AMSR-E daily snow-water equivalent product data. The maximum snow cover area fusion method is used to generate daily cloudless binary snow in the northern hemisphere. Product, the processed data resolution reaches 500m×500m. An analysis of the accuracy of the synthesized final daily snow cover products shows that the snow cover consistency reaches 87.1%, the land consistency reaches 92%, and the overall classification accuracy is 90.7%.
", "ds_ref_way": "", "ds_abstract": "This dataset is the daily cloudless binary snow cover product data in the Northern Hemisphere. The time period is from January 2000 to December 2015. The data includes two types of snow cover and non-snow feature. Data coverage ranges from 0-86°N, 180°W-180°E. The snow products used by the data sources for this dataset are the V005 versions of the daily snow classification products MOD10A1 and MYD10A1 downloaded through the NSIDC website, as well as the AMSR-E daily snow water equivalent product and snow ice product IMS. Using MOD10A1, MYD10A1, AMSR-E AWE and IMS raw data, the maximum snow cover area fusion method is used to generate daily cloud-free binary snow cover images.
", "ds_time_res": "", "ds_acq_place": "Northern Hemisphere", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Using MOD10A1, MYD10A1, AMSR-E AWE and IMS raw data, using the maximum snow cover area fusion method to generate daily cloud-free binary snow cover images\r\n
(1) Data production process: Use a special graphics workstation to perform the data processing process\r\n
(2) Methods and standard specifications: Use the maximum snow area fusion method\r\n
(3) Application scope: Northern Hemisphere\r\n
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "北半球", "无云", "积雪" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "北半球" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015 ], "ds_contributors": [ { "true_name": "黄晓东", "email": "huangxd@lzu.edu.cn", "work_for": "兰州大学草地农业科技学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "黄晓东", "email": "huangxd@lzu.edu.cn", "work_for": "兰州大学草地农业科技学院", "country": "中国" } ], "ds_managers": [ { "true_name": "黄晓东", "email": "huangxd@lzu.edu.cn", "work_for": "兰州大学草地农业科技学院", "country": "中国" } ], "category": "积雪" }