积雪是冰冻圈重要的组成部分，积雪覆盖范围影响地气能量平衡，进而影响气候和环境变化。积雪面积是重要的积雪参数之一，是水文和气候模型的重要输入。本数据集针对中国积雪特性，基于MODIS反射率产品MOD/MYD09GA，利用不同土地覆盖类型条件下发展了多指数结合积雪判别算法，提高了林区和山区积雪面积精度，同时利用隐马尔科夫算法、多源数据融合方法实现了产品的完全去云，制备2000-2020年空间分辨率为500m的逐日无云积雪面积数据集。该数据集以HDF5文件格式存储，每个HDF5文件包含18个数据要素，其中包括数据值（0=陆地，1=影像识别积雪， 2=去云插补积雪，3=雪深插补积雪，4=水体，255=填充值）、数据起始日期、经纬度等。同时为了快速预览积雪分布情况，逐日文件包含积雪面积缩略图，以jpg格式存储。此外本数据集还包含了用户使用手册。本数据集将根据实时卫星遥感数据和算法更新情况（目前到2020年12月）进行持续的补充和完善，并采用完全开放共享。
", "ds_source": "MODIS逐日表面反射率产品MOD09GA,MYD09GA来自于美国国家航空航天局（NASA），数据格式为hdf格式，空间分辨率为500m。
", "ds_process_way": "利用Landsat-8 OIL数据作为真值，结合MODIS土地覆盖分类产品MCD12Q1，基于MODIS反射率产品MOD09GA和MYD09GA，获取不同地表覆盖类型条件下的积雪决策树分类算法，基于GEE平台，获取初级产品。初级产品经过隐马尔科夫算法和雪深数据插值方法进行去云处理，基于python语言开发运行程序，最终获取研究区逐日无云积雪面积产品。
", "ds_quality": "数据质量良好。", "ds_acq_start_time": "2000-02-27 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": 17837366645, "ds_files_count": 15230, "ds_format": "HDF5", "ds_space_res": "500", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "经纬度（GLL）投影", "ds_thumbnail": "be3a4134-2e5c-467f-8a5e-b1c0ed6cc341.jpg", "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": "2022-05-10 15:35:14", "last_updated": "2025-04-25 16:01:01", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.I-SNOW.2020.9", "license": null, "i18n": { "en": { "title": "China Daily Cloud-free 500m Snow Cover Extent Product Dataset from MODIS", "ds_format": "HDF5", "ds_source": "
MODIS day-by-day surface reflectance products MOD09GA,MYD09GA from the National Aeronautics and Space Administration (NASA), the data format is hdf format, the spatial resolution is 500m.
", "ds_quality": "The data quality is good.", "ds_ref_way": "", "ds_abstract": "
Snowpack is an important component of the cryosphere, and the extent of snow cover affects the energy balance of the earth's atmosphere, which in turn affects climate and environmental change. Snowpack area is one of the important snowpack parameters, which is an important input to hydrological and climate models.\n
This dataset addresses the characteristics of snow accumulation in China, based on the MODIS reflectance product MOD/MYD09GA, and develops a multi-index combined snow discrimination algorithm under different land cover types to improve the accuracy of snow area in forested and mountainous areas, and at the same time realizes complete de-cloudedness of the product by using the Hidden Markov Algorithm and multi-source data fusion methods to prepare the cloud-free day-by-day snow accumulation data for the period of 2000-2020 at the spatial resolution of The day-by-day cloud-free snow accumulation area dataset with a spatial resolution of 500 m from 2000 to 2020 is prepared.\n
The dataset is stored in HDF5 file format, and each HDF5 file contains 18 data elements, including data values (0=land, 1=image-identified snow, 2=declouded interpolated snow, 3=snow-depth interpolated snow, 4=water, 255=fill value), data start date, latitude, longitude, and so on. Also for a quick preview of the snow distribution, the day-by-day file contains thumbnails of the snow area, stored in jpg format. In addition, this dataset contains a user manual. This dataset will be continuously supplemented and improved based on real-time satellite remote sensing data and algorithm updates (currently until December 2020), and will be adopted for full open sharing.
", "ds_time_res": "日", "ds_acq_place": "China's Land Territory", "ds_space_res": "500", "ds_projection": "GLL", "ds_process_way": "Using Landsat-8 OIL data as the true value, combined with MODIS land cover classification product MCD12Q1, based on MODIS albedo products MOD09GA and MYD09GA, the snow accumulation decision tree classification algorithms under different conditions of surface cover types were obtained, and based on the GEE platform, the primary products were obtained.\n
The primary products were de-clouded by Hidden Markov Algorithm and snow depth data interpolation method, and the running program was developed based on python language to finally obtain the day-by-day cloud-free snow area products in the study area.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "MODIS", "积雪面积", "去云", "逐日" ], "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": "郝晓华", "email": "haoxh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "孙兴亮", "email": "0219771@stu.lzjtu.edu.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "纪文政", "email": "jiwenzheng@nieer.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王晓艳", "email": "wangxiaoy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" }, { "true_name": "高扬", "email": "yanggao0924@163.com", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "赵琴", "email": "zhaoqin21@mails.ucas.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "赵宏宇", "email": "zhaohongyu@lzb.ac.cn", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "王建", "email": "wjian@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "李弘毅", "email": "lihongyi@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "郝晓华", "email": "haoxh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "孙兴亮", "email": "0219771@stu.lzjtu.edu.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "郝晓华", "email": "haoxh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "积雪" }