由于气候变暖和复杂的冰川动力过程，斯瓦尔巴群岛冰川正在快速消融，需要定期更新冰川边界以获取动态变化规律，并为海平面上升预估提供基础数据支撑。因此，以Landsat系列遥感影像为主要数据源，采用半自动化冰川制图方法，生产了斯瓦尔巴群岛3个时期的冰川编目产品（SGI-1990s, SIG-2000s, SGI-2020s），数据总体精度为±1.29%。
", "ds_source": "Landsat系列光学影像：包括Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI；空间分辨率为30m。 获取地址：https://earthexplorer.usgs.gov/
", "ds_process_way": "1.波段比值法自动提取初始冰川边界；2.人工修订初始边界
", "ds_quality": "采用两种方法对编目数据集进行了精度评估。基于Sentinel-2等较高分辨率影像的重复人工数字化结果表明，不同时期的冰川编目精度依次为±0.43%，±0.77%和±1.33%。基于缓冲区的精度评估结果则依次为±1.25%,±1.29%和±1.28%。
", "ds_acq_start_time": "1988-01-01 00:00:00", "ds_acq_end_time": "2021-12-31 00:00:00", "ds_acq_place": "斯瓦尔巴群岛", "ds_acq_lon_east": 10.0, "ds_acq_lat_south": 74.0, "ds_acq_lon_west": 35.0, "ds_acq_lat_north": 81.0, "ds_acq_alt_low": null, "ds_acq_alt_high": 1710.0, "ds_share_type": "login-access", "ds_total_size": 21048033, "ds_files_count": 2, "ds_format": "shapefile", "ds_space_res": "-", "ds_time_res": "-", "ds_coordinate": "WGS84", "ds_projection": "WGS_1984_UTM_Zone_33N", "ds_thumbnail": "fd938ae1-2320-4edf-a36c-925498b0031d.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "李红星", "ds_serv_phone": "09314967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2025-01-14 16:54:45", "last_updated": "2026-01-19 09:33:05", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "i18n": { "en": { "title": "Three interdecadal glacier inventories for Svalbard in the High Arctic", "ds_format": "shapefile", "ds_source": "A series of Landsat images: including Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI; spatial resolution is 30m. Obtain address: https://earthexplorer.usgs.gov/
", "ds_quality": "Two methods were used to evaluate the accuracy of the datasets. The results of repeated manual digitization based on higher-resolution images such as Sentinel-2 showed that the glacier cataloging accuracy in different periods was ±0.43%, ±0.77%, and ±1.33%, respectively. The accuracy assessment results based on the buffer were ±1.25%, ±1.29%, and ±1.28%, respectively.
", "ds_ref_way": "", "ds_abstract": "Due to climate warming and complex glacier dynamics, glaciers in Svalbard are melting rapidly, and it is necessary to regularly update glacier boundaries to obtain dynamic change information to provide basic data support for sea level rise projections. Therefore, using a series of Landsat images as the main data source and a semi-automated glacier mapping method, we have produced glacier inventories for three periods (SGI-1990s, SIG-2000s, and SGI-2020s) in Svalbard with an overall data accuracy of ±1.29%.
", "ds_time_res": "-", "ds_acq_place": "Svalbard ", "ds_space_res": "-", "ds_projection": "", "ds_process_way": "