本数据集为东北多年冻土区3处监测场地9处不同下垫面地表温度的观测数据，数据时间为2022年6月-2023年6月。\n
该数据集反映了东北多年冻土区不同下垫面条件下地表温度的变化特征，可为多年冻土区的地表能量交换过程、活动层热状况演变及冻土退化机制研究提供基础观测数据支撑，并可作为地表温度模拟、活动层厚度反演和冻土稳定性评价的重要输入数据，对多年冻土区工程规划和运行安全评估具有重要应用价值。", "ds_source": "
本数据集属于第一手观测数据，自主产生。数据通过野外长期监测获取，并经过电子化整理形成标准化数据集。", "ds_process_way": "
采集方法与设备：在各监测场地设置MX2201型HOBO温度记录仪进行自动观测，传感器布设于距地表5 cm深度处，以每2小时记录一次的频率连续采集地表温度数据。\n
数据精度：测量精度为±0.5℃。\n
数据处理：将记录数据进行日平均计算，获得每日平均地表温度，形成结构化数据表格，便于分析与共享。\n
遵循标准规范：监测方法符合相关野外观测标准要求。\n
误差控制：采集设备定野外布点时充分考虑遮挡、积水及地形微差影响，保证数据质量和代表性。", "ds_quality": "
数据集覆盖东北多年冻土区3处典型监测场地、9种不同下垫面类型，时间跨度为2022年6月至2023年6月，时间连续性良好、数据完整性较高。地表温度采用MX2201型HOBO温度记录仪进行自动观测，测量精度为±0.5℃，传感器布设于距地表5cm深度处，并以2h的间隔连续记录，计算获得日平均地表温度数据。观测过程稳定可靠，能够较好反映不同下垫面条件下地表温度的变化特征，数据具有较好的代表性和可靠性，可满足多年冻土热过程分析及相关工程应用研究需求。", "ds_acq_start_time": "2022-06-01 00:00:00", "ds_acq_end_time": "2023-06-30 00:00:00", "ds_acq_place": "东北多年冻土区", "ds_acq_lon_east": 124.31194444444444, "ds_acq_lat_south": 50.61666666666667, "ds_acq_lon_west": 124.00916666666667, "ds_acq_lat_north": 53.325, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 175755, "ds_files_count": 2, "ds_format": "*.xlsx", "ds_space_res": "", "ds_time_res": "日", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "934b41b5-7c6e-43cf-9ca2-9f98044b0065.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "221ebf56-1b0b-4574-972b-1fb6d3cf1be7", "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": "2026-04-07 09:53:31", "last_updated": "2026-05-12 14:55:22", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7288.2026", "i18n": { "en": { "title": "Land surface temperature data of different underlying surfaces in the permafrost region of Northeast China (2022-2023)", "ds_format": "*.xlsx", "ds_source": "
This dataset belongs to first-hand observation data and was generated independently. The data is obtained through long-term field monitoring and electronically organized to form a standardized dataset.", "ds_quality": "
The dataset covers three typical monitoring sites and nine different underlying surface types in the permafrost region of Northeast China, with a time span from June 2022 to June 2023. It has good time continuity and high data integrity. The surface temperature is automatically observed using the MX2201 HOBO temperature recorder, with a measurement accuracy of ± 0.5 ℃. The sensor is installed at a depth of 5cm from the surface and continuously records at intervals of 2 hours to calculate the daily average surface temperature data. The observation process is stable and reliable, which can better reflect the characteristics of surface temperature changes under different underlying surface conditions. The data has good representativeness and reliability, and can meet the needs of analysis of permafrost thermal processes and related engineering application research.", "ds_ref_way": "", "ds_abstract": "
This dataset consists of observation data on surface temperatures of 9 different underlying surfaces at 3 monitoring sites in the permafrost region of Northeast China, covering the period from June 2022 to June 2023.\r\n
This dataset reflects the characteristics of surface temperature changes under different underlying surface conditions in the permafrost region of Northeast China. It can provide basic observational data support for the study of surface energy exchange processes, active layer thermal evolution, and permafrost degradation mechanisms in permafrost regions. It can also serve as important input data for surface temperature simulation, active layer thickness inversion, and permafrost stability evaluation, and has significant application value for engineering planning and operational safety assessment in permafrost regions.", "ds_time_res": "", "ds_acq_place": "Northeast Permafrost Region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
Collection method and equipment: MX2201 HOBO temperature recorders are set up at various monitoring sites for automatic observation. The sensors are installed at a depth of 5 cm from the ground and continuously collect surface temperature data at a frequency of recording every 2 hours.\r\n
Data accuracy: The measurement accuracy is ± 0.5 ℃.\r\n
Data processing: Calculate the daily average of recorded data to obtain the daily average surface temperature, and form a structured data table for easy analysis and sharing.\r\n
Follow standard specifications: The monitoring method complies with relevant field observation standards.\r\n
Error control: When selecting field locations for data collection equipment, full consideration should be given to the effects of occlusion, water accumulation, and terrain differences to ensure data quality and representativeness.", "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": [ "地表温度", "多年冻土", "下垫面" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "东北多年冻土区" ], "ds_time_tags": [ 2022, 2023 ], "ds_contributors": [ { "true_name": "李国玉", "email": "guoyuli@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": "陈敦", "email": "chendun@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": "高凯", "email": "gaokai@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": "王飞", "email": "wangfei@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": "曹亚鹏", "email": "caoyapeng@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": "尹国安", "email": "yinguoan@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": "牛富俊", "email": "niufujun@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": "商允虎", "email": "shangyunhu@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": "林峻岑", "email": "linjuncen@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": "杜青松", "email": "xbdqs@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": "贾寒", "email": "jiahan@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": "王亚鹏", "email": "wangyapeng@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": "齐舜舜", "email": "qishunshun@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": "艾熙惠", "email": "aixihui@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": "杨佳伟", "email": "yangjiawei@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": "李兆祥", "email": "lizhaoxiang@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": "胡美容", "email": "humeirong@nieer.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": "高凯", "email": "gaokai@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": "陈敦", "email": "chendun@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": "陈敦", "email": "chendun@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": "冻土" }