本数据集主要研究 20 世纪 70 年代至 2000 年青藏高原东部源头河流的冰川质量变化。它提供两种分辨率的数据：高分辨率冰川级数据（30 米）和低分辨率网格数据（0.1 度和 0.5 度）。高分辨率数据为单个冰川提供了宝贵的信息，包括 13117 个冰川 30 年来的海拔变化、年度质量平衡和相关的不确定性。为了计算质量变化，我们将 20 世纪 70 年代地形图（航空摄影测量）得出的数字高程模型（DEM）与 2000 年的航天飞机雷达地形图任务（SRTM）数据进行了比较。共同注册、偏差校正和质量控制程序确保了数据的准确性。我们使用 ICESat-2 和 KH-9 数据评估了基于 DEM 的高程差异。结果表明质量良好，尤其是在低海拔地区，与 KH-9 数据类似。然而，由于使用航空照片捕捉陡峭地形上高反射雪面的局限性，高海拔结果的不确定性较高。该数据集覆盖了 72% 的 ETPR 冰川，是非常宝贵的资源。这种全面性使其非常适合在各种规模的质量平衡模拟中校准参数。此外，该数据集还可用于评估 2000 年前后冰川水文效应的变化。", "ds_source": "
我们共使用了 718 幅历史地形图，其中包括 142 幅比例尺为 1:50,000 的地形图和 576 幅比例尺为 1:100,000 的地形图，这些地形图是根据中国军事大地测量局在 1957 年至 1983 年期间拍摄的航空照片绘制的；在本研究中，我们使用分辨率为 1 弧秒（约 30 米）的 SRTM DEM（无空隙填充版本）；在本研究中，我们获取了覆盖西夏邦马山的 KH-9 图像；以及 ICESat-2数据。
", "ds_process_way": "为了生成网格产品，我们采取了以下步骤： 1) 首先，我们对所有有效冰川的高差、高差误差和时间戳进行空间合并。2) 对于每个网格单元，我们计算该网格单元内的冰川高差、高差误差和时间戳的平均值。这些平均值被指定为网格单元值。3) 对于每个网格单元，我们计算高差的 NMAD 和像素数。利用公式 (6)，计算网格尺度重采样误差。4) 结合网格尺度高差和时间戳，应用公式（7）计算网格尺度质量平衡。5) 结合网格尺度高程变化误差和时间戳，应用公式 (8) 计算初始网格尺度质量平衡误差。最后，结合重采样误差得出最终质量平衡误差。", "ds_quality": "
数据质量良好。
", "ds_acq_start_time": "1970-01-01 00:00:00", "ds_acq_end_time": "2000-12-31 00:00:00", "ds_acq_place": "青藏高原东部", "ds_acq_lon_east": 105.0, "ds_acq_lat_south": 27.0, "ds_acq_lon_west": 75.0, "ds_acq_lat_north": 40.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 555683753, "ds_files_count": 2, "ds_format": "NetCDF", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "75b72d4c-58c3-493f-9a0a-323121f68347.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "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": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2024-09-27 09:23:52", "last_updated": "2025-04-24 16:12:48", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB6680.2024", "i18n": { "en": { "title": "Glacier-level and gridded mass change in the rivers' sources in the eastern Tibetan Plateau (1970s-2000) ", "ds_format": "NetCDF", "ds_source": "We employed a total of 718 historical topographic maps including 142 at a scale of 1:50,000 and 576 at a scale of 1:100,000 compiled from aerial photos taken from 1957 to 1983 by the Chinese Military Geodetic Service. In this study, we use SRTM DEM (no void filled version) with a resolution of 1 arc second (~30 m) refer to the glacier surface in the year of 1999 suggested by previous studies (e.g., Gardelle et al., 2013; Mcnabb et al., 2019). In this study, we acquired the KH-9 images covering Xixiabangma Mountain，and ICESat-2 data.", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
This dataset focuses on glacier mass change in the Eastern Tibetan Plateau's (ETPR) source rivers from the 1970s to 2000. It provides data at two resolutions: high-resolution glacier-level data (30 m) and lower-resolution gridded data (0.1 and 0.5 degrees). The high-resolution data offers valuable insights for individual glaciers, including elevation change over 30 years, annual mass balance, and associated uncertainty for 13,117 glaciers. To calculate mass change, we compared digital elevation models (DEMs) derived from 1970s topographic maps (aerial photogrammetry) with the Shuttle Radar Topography Mission (SRTM) data from 2000. Co-registration, bias correction, and quality control procedures ensured data accuracy. We evaluated the DEM-based elevation differences using ICESat-2 and KH-9 data. The results demonstrate good quality, particularly at lower altitudes, similar to KH-9 data. However, high-altitude results have higher uncertainty due to limitations in capturing highly reflective snow surfaces on steep terrain using aerial photos. This dataset is a valuable resource as it covers 72% of ETPR glaciers. This comprehensiveness makes it ideal for calibrating parameters in mass balance simulations at various scales. Furthermore, the dataset can be used to assess changes in glacier hydrological effects before and after 2000.
", "ds_time_res": "", "ds_acq_place": "Eastern Qinghai Tibet Plateau", "ds_space_res": "", "ds_projection": "", "ds_process_way": "To generate the grid product, we took the following steps: 1) Firstly, we spatially merged the elevation differences, elevation errors, and timestamps of all effective glaciers. 2) For each grid cell, we calculate the average glacier elevation difference, elevation error, and timestamp within that grid cell. These averages are designated as grid cell values. 3) For each grid cell, we calculate the NMAD and pixel count of the height difference. Calculate the grid scale resampling error using formula (6). 4) Combining the grid scale height difference and timestamp, apply formula (7) to calculate the grid scale mass balance. 5) Combining the grid scale elevation variation error and timestamp, apply formula (8) to calculate the initial grid scale mass balance error. Finally, the final mass balance error is obtained by combining the resampling error.", "ds_ref_instruction": "When using data, users should clearly declare the source of the data in the main text and cite the citation method provided by this metadata in the reference section." } }, "submit_center_id": "ncdc", "data_level": 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, "ds_topic_tags": [ "冰川（冰盖）", "冰川高程变化", "质量平衡", "地表冻融循环/状态遥感", "冰冻圈遥感产品" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原东部源头河流" ], "ds_time_tags": [ 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000 ], "ds_contributors": [ { "true_name": "刘时银", "email": "liusy@lzb.ac.cn", "work_for": "云南大学国际河流与生态安全研究院", "country": "中国" }, { "true_name": "朱钰", "email": "", "work_for": "中国科学院西北生态环境资源研究院", "country": "" } ], "ds_meta_authors": [ { "true_name": "朱钰", "email": "", "work_for": "中国科学院西北生态环境资源研究院", "country": "" }, { "true_name": "刘时银", "email": "liusy@lzb.ac.cn", "work_for": "云南大学国际河流与生态安全研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "朱钰", "email": "", "work_for": "中国科学院西北生态环境资源研究院", "country": "" }, { "true_name": "刘时银", "email": "liusy@lzb.ac.cn", "work_for": "云南大学国际河流与生态安全研究院", "country": "中国" } ], "category": "水文" }