黑河流域积雪面积比例数据集提供了2010到2012年无云日积雪面积比例时间序列产品，该数据利用卫星MODIS数据，具有较高时间分辨率（1天）和空间分辨率（500m）。首先利用自动算法N-FINDR选择端元，在自动提取的基础上，利用人工方法选择了积雪、植被、云、土壤、岩石和水6种类型端元，并根据2009年影像建立了光谱数据库；在光谱数据库的基础上利用全约束线性解混方法（FCLS）进行亚像元分解获取初级积雪面积比例产品；最后利用差值去云的算法获取了MODIS逐日积雪面积比例无云产品。\n
经利用高分辨率影像Landsat TM验证，相比已有MODIS积雪面积比例产品 (MOD10A1)，具有更高的精度。能够为流域水文，气象提供更准确的积雪参数输入。\n
数据说明：0-100积雪面积比例，0非雪；\n投影类型：经纬度投影，WGS-84基准面；\n
空间分辨率：0.005度；\n
时间分辨率：1天。", "ds_source": "
数据说明：0-100积雪面积比例，0非雪；\n
投影类型：经纬度投影，WGS-84基准面；\n
空间分辨率：0.005度；\n
时间分辨率：1天。
", "ds_process_way": "利用人工方法选择了积雪、植被、云、土壤、岩石和水6种类型端元，并根据2009年影像建立了光谱数据库；在光谱数据库的基础上利用全约束线性解混方法（FCLS）进行亚像元分解获取初级积雪面积比例产品；最后利用差值去云的算法获取了MODIS逐日积雪面积比例无云产品。
", "ds_quality": "数据质量良好
", "ds_acq_start_time": "2010-01-01 00:00:00", "ds_acq_end_time": "2012-01-01 00:00:00", "ds_acq_place": "黑河流域", "ds_acq_lon_east": 101.75, "ds_acq_lat_south": 37.25, "ds_acq_lon_west": 97.75, "ds_acq_lat_north": 42.81666666666667, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1058930995, "ds_files_count": 3, "ds_format": "tif", "ds_space_res": "/", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "/", "ds_thumbnail": "25509c26-4912-4e2e-a44b-1539138ef22d.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "本数据由“黑河生态水文遥感试验（HiWATER）”产生，用户在使用数据时请在正文中明确声明数据的来源，并在参考文献部分引用本元数据提供的引用方式。", "ds_from_station": null, "organization_id": "c94b3578-20da-4346-9de9-c702b6ca8983", "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": "2021-08-31 11:28:25", "last_updated": "2025-06-30 16:34:45", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.1751", "i18n": { "en": { "title": "Heihe River eco hydrological remote sensing experiment: Heihe River Basin snow area proportion data set", "ds_format": "tif", "ds_source": "Data Description: 0-100 snow area proportion, 0 Non snow
\nProjection type: longitude and latitude projection, WGS-84 datum
\nSpatial resolution: 0.005 degrees
\nTime resolution: 1 day
", "ds_quality": "Good data quality
", "ds_ref_way": "", "ds_abstract": "The snow area proportion data set of Heihe River basin provides a time series product of snow area proportion on cloudless days from 2010 to 2012. The data uses satellite MODIS data with high temporal resolution (1 day) and spatial resolution (500m). Firstly, the automatic algorithm N-FINDR is used to select the end elements. On the basis of automatic extraction, six types of end elements including snow, vegetation, cloud, soil, rock and water are selected manually, and the spectral database is established according to the 2009 images; Based on the spectral database, the fully constrained linear unmixing method (FCLs) is used for sub-pixel decomposition to obtain the primary snow area proportion product; Finally, the cloud free products of MODIS daily snow area ratio are obtained by using the difference cloud removal algorithm
\nVerified by using high-resolution image Landsat TM, it has higher accuracy than the existing MODIS Snow area proportion product (mod10a1). It can provide more accurate snow parameter input for hydrology and meteorology of the basin
\nData Description: 0-100 snow area proportion, 0 Non snow;\nProjection type: longitude and latitude projection, WGS-84 datum
\nSpatial resolution: 0.005 degrees
\nTime resolution: 1 day
", "ds_time_res": "日", "ds_acq_place": "Heihe River Basin", "ds_space_res": "/", "ds_projection": "/", "ds_process_way": "Six types of end elements including snow, vegetation, cloud, soil, rock and water were selected by artificial method, and the spectral database was established according to the 2009 images; Based on the spectral database, the fully constrained linear unmixing method (FCLs) is used for sub-pixel decomposition to obtain the primary snow area proportion product; Finally, the cloud free products of MODIS daily snow area ratio are obtained by using the difference cloud removal algorithm
", "ds_ref_instruction": "This data is generated by \"Heihe eco hydrological remote sensing experiment (hiwater)\". When using the data, users should clearly state the source of the data in the text and quote the reference method provided by this metadata in the reference part." } }, "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, "is_paper_in_submitting": false, "ds_topic_tags": [ "积雪面积", "MODIS", "卫星遥感产品", "FSC", "积雪" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域" ], "ds_time_tags": [ 2010, 2012 ], "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": "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" }, { "true_name": "李新", "email": "lixin@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" } ], "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": "遥感及产品" }