该数据集以东北高纬度多年冻土区为研究对象，综合利用30 m空间分辨率的多源遥感数据、地表及地下温度监测资料、冻土类型分布及工程干扰信息，构建了冻土工程基础稳定性预测与评价模型。该数据集定量评估了线性工程沿线及其影响范围内的基础稳定性。评价结果采用0.0–1.0的无量纲稳定性指数表征，揭示了人类工程活动对多年冻土热平衡的破坏作用。数据呈现出显著的“线性聚焦”特征，即低稳定高风险带与交通、能源廊道高度重合，为区域尺度工程规划和冻害风险防控提供核心决策支撑。\n
本数据集核心要素为稳定性指数（无量纲，0-1），根据风险水平划分为三个等级：\n
高稳定区（0–0.30）：低风险，绿色显示。主要分布在大片不连续多年冻土内部，地温低、活动层稳定、干扰小。\n
中稳定区（0.30–0.60）：中风险，黄色显示。分布于融区较多的不连续冻土向岛状/零星冻土的过渡带。\n
低稳定区（0.60–1.0）：高风险，红色显示。\n
高度集中于线性工程（G111、G331、CRCOP管道等）沿线，形成连续或准连续的高风险带。", "ds_source": "
综合利用30 m空间分辨率的多源遥感数据、公开的气候，人为等多源遥感数据资料、冻土类型分布及工程干扰信息，通过构建冻土工程基础稳定性预测与评价模型进行定量评估。", "ds_process_way": "
模型构建：整合地温、冻土特征、活动层厚度及人为热扰动因子。\n
风险分级：根据稳定性指数（0-1）划分高、中、低稳定等级。\n
典型区验证：\n
漠河枢纽段：分析高含冰量区域由于路基吸热导致的热扰动扩散。\n
新林段：评估公路与铁路并行产生的复合扰动叠加效应。\n
黑河/劲松段：针对冻土南界（SLLP）敏感区的退化临界状态进行稳定性突变分析。", "ds_quality": "
（1）资源精度：本资源空间分辨率精确至30 m，评价指数采用无量纲数值（0.0至1.0），能够细致捕捉线性工程廊道内部及其周边3至5 km缓冲范围内的稳定性波动。\n
（2）数据采集与监测：评价模型输入项集成了卫星遥感反演的地表参数、研究区内典型断面及场点的地下温度监测序列，以及高精度的线性工程调查数据。\n
（3）模型方法与规范：稳定性评估算法综合考虑了多年冻土热稳定性、冻土分布特征及下垫面工程扰动强度。模型通过对植被隔热削弱及水热通量扰动的定量模拟，有效反映了工程基础失稳的潜在风险。\n
（4）适用范围与验证：资源质量通过了漠河枢纽段（高含冰量区）、新林段（复合工程扰动区）及黑河边缘段（南界高度敏感区）等典型区域的对比验证。评价结果与实地调查中的路面不均匀沉降、波浪状起伏等病害分布具有高度空间一致性，适用于寒区工程基础稳定性评估、灾害早期预警及环境变化响应研究。", "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": 127.58, "ds_acq_lat_south": 49.11, "ds_acq_lon_west": 117.43, "ds_acq_lat_north": 53.5, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 2840036851, "ds_files_count": 6, "ds_format": "*.tif", "ds_space_res": "30m", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "WGS_1984_Albers", "ds_thumbnail": "70c33bc7-ee0b-47b2-b7b4-092c65bcb222.jpg", "ds_thumb_from": 0, "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": "2026-04-02 20:14:23", "last_updated": "2026-05-12 10:12:19", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7261.2026", "i18n": { "en": { "title": "30m permafrost engineering foundation stability prediction and evaluation data of the permafrost region in Northeast China (2023-2024)", "ds_format": "", "ds_source": "
By comprehensively utilizing multi-source remote sensing data with a spatial resolution of 30 meters, publicly available climate, anthropogenic and other multi-source remote sensing data, frozen soil type distribution and engineering interference information, a quantitative evaluation model for predicting and evaluating the stability of frozen soil engineering foundations is constructed.", "ds_quality": "
(1) Resource accuracy: The spatial resolution of this resource is accurate to 30 meters, and the evaluation index adopts dimensionless values (0.0 to 1.0), which can capture the stability fluctuations within a buffer range of 3 to 5 kilometers inside and around the linear engineering corridor in detail.\r\n
(2) Data collection and monitoring: The evaluation model integrates surface parameters retrieved from satellite remote sensing, underground temperature monitoring sequences of typical cross-sections and field points in the study area, and high-precision linear engineering survey data as input items.\r\n
(3) Model methods and standards: The stability assessment algorithm comprehensively considers the thermal stability of permafrost, the distribution characteristics of permafrost, and the disturbance intensity of underlying surface engineering. The model effectively reflects the potential risk of engineering foundation instability through quantitative simulation of vegetation thermal insulation weakening and water and heat flux disturbance.\r\n
(4) Scope of application and verification: The resource quality has been compared and verified in typical areas such as the Mohe Hub section (high ice content area), Xinlin section (composite engineering disturbance area), and Heihe edge section (southern highly sensitive area). The evaluation results have a high degree of spatial consistency with the distribution of road surface uneven settlement, wavy undulations and other diseases in field investigations, which is suitable for the stability assessment of engineering foundations in cold regions, early warning of disasters, and research on environmental change response.", "ds_ref_way": "", "ds_abstract": "
This dataset takes the high latitude permafrost region in Northeast China as the research object, and comprehensively utilizes multi-source remote sensing data with a spatial resolution of 30 meters, surface and underground temperature monitoring data, permafrost type distribution, and engineering interference information to construct a model for predicting and evaluating the stability of permafrost engineering foundations. This dataset quantitatively evaluates the basic stability along the linear engineering line and its impact range. The evaluation results are characterized by a dimensionless stability index ranging from 0.0 to 1.0, revealing the destructive effect of human engineering activities on the thermal balance of permafrost. The data exhibits a significant \"linear focus\" feature, where the low stability and high risk zones overlap highly with transportation and energy corridors, providing core decision support for regional scale engineering planning and frost damage risk prevention and control.\r\n
The core element of this dataset is the stability index (dimensionless, 0-1), which is divided into three levels based on risk level:\r\n
High stability zone (0-0.30): Low risk, displayed in green. Mainly distributed within large areas of discontinuous permafrost, with low ground temperature, stable active layer, and minimal interference.\r\n
Medium stable zone (0.30-0.60): medium risk, displayed in yellow. Distributed in the transition zone from discontinuous frozen soil with more melting areas to island/sporadic frozen soil.\r\n
Low stability zone (0.60-1.0): High risk, displayed in red.\r\n
Highly concentrated along linear engineering (G111, G331, CRCOP pipelines, etc.), forming continuous or quasi continuous high-risk zones.", "ds_time_res": "", "ds_acq_place": "Northeast Permafrost Region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
Model construction: Integrate ground temperature, frozen soil characteristics, active layer thickness, and anthropogenic thermal disturbance factors.\r\n
Risk classification: High, medium, and low stability levels are classified based on the stability index (0-1).\r\n
Typical area verification:\r\n
Mohe Hub Section: Analyze the thermal disturbance diffusion caused by roadbed heat absorption in areas with high ice content.\r\n
Xinlin section: Evaluate the composite disturbance superposition effect generated by the parallel operation of highways and railways.\r\n
Heihe/Jinsong section: Conduct stability transition analysis on the degradation critical state of the sensitive area of the southern boundary of frozen soil (SLLP).", "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": [ "冻土工程基础稳定性", "30 m分辨率", "线性工程廊道", "冻害工程", "冻害风险评价" ], "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" } ], "ds_managers": [ { "true_name": "金会军", "email": "hjjin@nefu.edu.cn", "work_for": "东北林业大学", "country": "中国" } ], "category": "冻土" }