该数据详尽刻画了东北多年冻土区在气候变化与人类工程活动耦合作用下的冻融灾害空间格局。资源内容涵盖了从大片不连续多年冻土区到季节冻土过渡带的灾害类型分布，重点识别了路面不均匀沉降、热融湖塘、路面裂缝、冻融侵蚀、冰椎及水毁等六大灾害类型。\n
资源特征：（1）空间跨度大： 覆盖了大兴安岭及小兴安岭主要冻土区。（2）精细度高： 采用1:10万比例尺，揭示了“北密南疏、高密低疏”的分布特征。（3）工程相关性强： 突出展示了公路（G111、G331等）、铁路及中俄原油管道等线性工程廊道的灾害聚集态势。（4）典型性代表： 选取了漠河、根河-伊图里河、新林、黑河及加格达奇南段等五个典型区域进行微观解析。", "ds_source": "
自主产生，融合了多期野外科学考察记录，以及机器学习模型得到预测结果。", "ds_process_way": "
实地调查：整合大兴安岭，小兴安岭等典型（漠河、塔河、根河）监测区域的长期病害记录。\n
工程干扰模拟：考虑沥青路面的强吸热效应与常温原油管道的热源排放对冻土上限的深度侵蚀。", "ds_quality": "
（1）资源精度： 比例尺为1:10万。基于机器学习模型生成，其精度足对区域性冻土工程风险评估与灾害防控决策有支撑作用。\n
（2）适用范围： 适用于寒区工程规划（公路、铁路、管道）、多年冻土区环境监测、气候变化影响评估以及地理信息系统相关科学研究。\n
（3）模型方法： 采用先进的机器学习算法进行空间建模，模型充分考虑了自然背景与人为扰动的耦合关系。\n
（4）质量控制： 通过对不同冻土梯度的典型区域进行放大解析与比对，验证了灾害类型（如沉降、裂缝、侵蚀等）与实际地形、水文过程及工程扰动之间的一致性，确保了空间组织特征的准确表述。", "ds_acq_start_time": "2023-01-01 00:00:00", "ds_acq_end_time": "2024-12-31 00:00:00", "ds_acq_place": "东北多年冻土区", "ds_acq_lon_east": 135.08333333333334, "ds_acq_lat_south": 37.2, "ds_acq_lon_west": 114.25, "ds_acq_lat_north": 53.6, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 24244884705, "ds_files_count": 8, "ds_format": "*.tif", "ds_space_res": "30m", "ds_time_res": "2年", "ds_coordinate": "WGS84", "ds_projection": "WGS_1984_Albers", "ds_thumbnail": "6d8f3829-5d4b-4185-a13a-bab98fc24891.jpg", "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": "2026-04-03 08:44:03", "last_updated": "2026-05-12 10:21:29", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7263.2026", "i18n": { "en": { "title": "Distribution map of 30m freeze-thaw disasters in the permafrost region of Northeast China (2023-2024)", "ds_format": "*.tif", "ds_source": "
Independently generated, integrating multiple field scientific expedition records and machine learning models to obtain prediction results.", "ds_quality": "
(1) Resource accuracy: The scale is 1:100000. Based on machine learning models, its accuracy is sufficient to support regional frozen soil engineering risk assessment and disaster prevention decisions.\r\n
(2) Scope of application: Suitable for engineering planning in cold regions (highways, railways, pipelines), environmental monitoring in permafrost regions, assessment of climate change impacts, and scientific research related to geographic information systems.\r\n
(3) Model method: Advanced machine learning algorithms are used for spatial modeling, and the model fully considers the coupling relationship between natural background and human disturbance.\r\n
(4) Quality control: By amplifying and comparing typical areas with different permafrost gradients, the consistency between disaster types (such as settlement, cracks, erosion, etc.) and actual terrain, hydrological processes, and engineering disturbances was verified, ensuring accurate representation of spatial organizational characteristics.", "ds_ref_way": "", "ds_abstract": "
This data provides a detailed characterization of the spatial pattern of freeze-thaw disasters in the permafrost region of Northeast China under the coupling effects of climate change and human engineering activities. The resource content covers the distribution of disaster types from large discontinuous permafrost areas to seasonal permafrost transition zones, with a focus on identifying six major disaster types: uneven road settlement, hot melt lakes and ponds, road cracks, freeze-thaw erosion, ice cones, and water damage.\r\n
Resource characteristics: (1) Large spatial span: covering the main permafrost areas of Daxing'an Mountains and Xiaoxing'an Mountains. (2) High precision: Using a scale of 1:100000, it reveals the distribution characteristics of \"north dense and south sparse, high dense and low sparse\". (3) Strong engineering relevance: Highlighting the disaster gathering trend of linear engineering corridors such as highways (G111, G331, etc.), railways, and Sino Russian crude oil pipelines. (4) Typical representatives: Five typical regions including Mohe, Genhe Ituli River, Xinlin, Heihe, and the southern section of Gagdachi were selected for micro analysis.", "ds_time_res": "", "ds_acq_place": "Northeast Permafrost Region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
Field investigation: Integrate long-term disease records from typical monitoring areas such as Mohe, Tahe, and Genhe in the Greater Khingan Range and Lesser Khingan Range.\r\n
Engineering interference simulation: Consider the strong heat absorption effect of asphalt pavement and the deep erosion of frozen soil upper limit caused by heat source emissions from ambient temperature crude oil pipelines.", "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": [ "工程冻融灾害", "机器学习", "空间分布格局", "线性工程廊道", "路面不均匀沉降", "热融湖塘" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "东北多年冻土区" ], "ds_time_tags": [ 2023, 2024 ], "ds_contributors": [ { "true_name": "金会军", "email": "hjjin@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "唐建军", "email": "jianjuntang@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "王文辉", "email": "wangwenhui@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "金晓颖", "email": "xyj@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "李善珍", "email": "lsz@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "黄帅", "email": "s_hwang@nefu.edu.cn", "work_for": "东北林业大学", "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": "王宏伟", "email": "wanghw@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": "杨岁桥", "email": "yangsuiqiao@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "李祖旺", "email": "lzwang@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "燕翱翔", "email": "yanaoxiang@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "程耀辉", "email": "yhcheng@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "李景涛", "email": "ljtao@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "张泽", "email": "zez@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "王立峰", "email": "9431629@qq.com", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "张虎", "email": "zhanghu@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "刘萌心", "email": "liumengxin@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "张圣嵘", "email": "zhangshengrong@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "杨雪", "email": "yangx014@nenu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "刘子瑞", "email": "lzr@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "岳子颖", "email": "zyyue@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "吴海彬", "email": "haibinwu@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "邢鲁宁", "email": "18363701763@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "陈思宇", "email": "chensy@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "徐景妍", "email": "JingyanXu@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "何峥雲", "email": "yunhardworking@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "米虹岐", "email": "mimhq07@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "彭文昊", "email": "Pengwh@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "梁峻贺", "email": "liangjh@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "史艳玲", "email": "15247298387@163.com", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "周智熠", "email": "v1ncentharrious@outlook.com", "work_for": "东北林业大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "金会军", "email": "hjjin@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "唐建军", "email": "jianjuntang@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" }, { "true_name": "王文辉", "email": "wangwenhui@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" } ], "ds_managers": [ { "true_name": "金会军", "email": "hjjin@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" } ], "category": "灾害" }