本数据集为泛北极地区1990年历史时期地表植被覆盖分类产品，空间分辨率为30米，旨在为北极地区长时序土地覆盖变化研究提供历史基准数据。该产品采用与ARC-2024一致的北极专用分类体系，包含9类土地覆盖类型：低灌木(LS)、直立矮灌木(DS)、草地(GR)、小型低矮草本植物(SF)、湿地(WL)、水域(WA)、苔藓地衣(ML)、裸地(BG)及冰雪(IS)。ARC-1990基于Landsat 5 TM历史影像数据构建，采用时间序列匹配分类方法，通过部分物候信号匹配机制实现大尺度自动化分类。该产品与ARC-2024形成时间序列配套数据集，可支撑1990–2024年间北极地区土地覆盖变化检测、苔原植被演替分析及气候变化生态响应研究，为理解过去三十余年北极生态系统变化提供关键数据支撑。", "ds_source": "
本数据集基于美国地质调查局（USGS）与美国国家航空航天局（NASA）联合运营的Landsat 5卫星搭载的专题制图仪（TM）传感器影像数据构建，影像获取时间覆盖1990年北极生长季（5月–10月）。数据预处理在Google Earth Engine云平台完成。", "ds_process_way": "
（1）影像预处理：基于Landsat 5 TM Collection 2 Level-2地表反射率产品，进行云掩膜处理及光谱指数计算，在Google Earth Engine平台完成标准化预处理。\n
（2）样本迁移与适配：基于GLC_FCS30时间序列（1985–2022年）稳定区域筛选，结合1990年影像光谱特征进行样本时间适配，确保训练样本与目标年份影像的一致性。\n
（3）时间序列匹配分类：采用与ARC-2024相同的时序匹配策略，通过部分物候信号匹配机制最大化，利用生长季内可用无云观测数据，实现自动化分类处理。\n
（4）分类后处理：应用空间滤波去除椒盐噪声，结合地形辅助数据修正高海拔区域分类结果。\n
（5）质量验证：采用独立验证样本进行精度评估，并与同期历史土地覆盖产品进行空间一致性对比分析。", "ds_quality": "
本数据集质量受Landsat 5 TM历史影像数据质量及分类算法精度的共同影响。受限于1990年代卫星影像存档条件，部分区域可能存在云覆盖较高、可用观测数据有限的情况。分类方法采用与ARC-2024一致的时间序列匹配算法，确保方法学的一致性与产品间的可比性。精度验证采用独立样本评估，并与ESA CCI Land Cover、GLC_FCS30等同期产品进行空间一致性分析。由于历史时期地面验证数据稀缺，产品精度评估主要依赖于交叉验证及多产品对比分析。用户在使用时应注意历史遥感数据固有的不确定性，建议结合多源数据进行综合分析。", "ds_acq_start_time": "1990-05-01 00:00:00", "ds_acq_end_time": "1990-10-31 00:00:00", "ds_acq_place": "泛北极区域", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 55.79, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 84.08999999999999, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 3052156411, "ds_files_count": 7, "ds_format": "*.tif", "ds_space_res": "50m", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "Albers Equal Area Conic Projection System", "ds_thumbnail": "b26d033c-5848-4fcb-8334-f5dc5d27fa39.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "53943799-d453-4bf2-a141-56c205c1355b", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 3, "publish_time": "2026-02-12 19:50:18", "last_updated": "2026-02-13 10:28:19", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ARCTIC-CHANGE.DB7127.2026", "i18n": { "en": { "title": "ARC-1990: 30m Resolution Land Cover Map of Circumpolar Arctic in 1990", "ds_format": "*.tif", "ds_source": "
This dataset is constructed based on imagery data from the Thematic Mapper (TM) sensor aboard the Landsat 5 satellite, jointly operated by the United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), with image acquisition covering the 1990 Arctic growing season (May–October). Data preprocessing was completed on the Google Earth Engine cloud platform.", "ds_quality": "
The quality of this dataset is jointly influenced by the quality of Landsat 5 TM historical imagery data and the accuracy of classification algorithms. Due to limitations in satellite imagery archival conditions during the 1990s, some regions may have high cloud coverage and limited available observation data. The classification method employs the same time-series matching algorithm as ARC-2024, ensuring methodological consistency and inter-product comparability. Accuracy validation was conducted using independent sample assessment, along with spatial consistency analysis with contemporaneous products such as ESA CCI Land Cover and GLC_FCS30. Due to the scarcity of ground validation data during the historical period, product accuracy assessment primarily relies on cross-validation and multi-product comparative analysis. Users should note the inherent uncertainties in historical remote sensing data and are advised to conduct comprehensive analysis in conjunction with multi-source data.", "ds_ref_way": "", "ds_abstract": "
This dataset is a historical land cover classification product for the Circumpolar Arctic region in 1990, with a spatial resolution of 30 meters, designed to provide historical baseline data for long-term land cover change research in the Arctic. The product employs the same Arctic-specific classification system as ARC-2024, comprising 9 land cover classes: Low-shrub (LS), Dwarf-shrub (DS), Grass (GR), Small low-growing forb (SF), Wetlands (WL), Water (WA), Moss and Lichen (ML), Bare ground (BG), and Ice and Snow (IS). Given the extremely limited spatial extent of Built-up area (BA) in the Circumpolar Arctic region in 1990, this class is excluded from the dataset. ARC-1990 is constructed based on Landsat 5 TM historical imagery data, employing a time-series matching classification approach that achieves large-scale automated classification through a partial phenological signal matching mechanism. This product forms a temporal series paired dataset with ARC-2024, supporting land cover change detection, tundra vegetation succession analysis, and climate change ecological response research in the Arctic region during 1990–2024, providing critical data support for understanding Arctic ecosystem changes over the past three decades.", "ds_time_res": "年", "ds_acq_place": "Circumpolar Arctic", "ds_space_res": "50m", "ds_projection": "", "ds_process_way": "
(1) Image Preprocessing: Based on Landsat 5 TM Collection 2 Level-2 surface reflectance products, cloud masking and spectral index calculation were performed, with standardized preprocessing completed on the Google Earth Engine platform.
(2) Sample Transfer and Adaptation: Stable regions were identified through GLC_FCS30 time series (1985–2022) screening, and sample temporal adaptation was performed by integrating spectral characteristics from 1990 imagery to ensure consistency between training samples and target year imagery. \n
(3) Time-Series Matching Classification: The same time-series matching strategy as ARC-2024 was employed, maximizing the utilization of available cloud-free observations during the growing season through a partial phenological signal matching mechanism to achieve automated classification processing. \n
(4) Post-classification Processing: Spatial filtering was applied to remove salt-and-pepper noise, combined with terrain auxiliary data to correct classification results in high-elevation areas. \n
(5) Quality Validation: Accuracy assessment was conducted using independent validation samples, along with spatial consistency comparative analysis with contemporaneous historical land cover products.", "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, "ds_topic_tags": [ "泛北极", "土地覆盖制图", "历史基准", "时间序列分类", "Landsat", "苔原植被" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "泛北极" ], "ds_time_tags": [ 1990 ], "ds_contributors": [ { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" }, { "true_name": "曲歌", "email": "471920609@stu.lntu.edu.cn", "work_for": "辽宁工程技术大学", "country": "中国" }, { "true_name": "霍思慧", "email": "Huosihui@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" }, { "true_name": "马现伟", "email": "maxianwei_lntu@126.com", "work_for": "辽宁工程技术大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "曲歌", "email": "471920609@stu.lntu.edu.cn", "work_for": "辽宁工程技术大学", "country": "中国" }, { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" } ], "category": "基础地理" }