本数据资源包括基于30 m分辨率数字高程模型提取的坡度与坡向地形因子数据，覆盖东北多年冻土区主要工程走廊及其周边区域。数据集重点刻画了多年冻土区地形形态对地表过程与工程环境稳定性的控制作用，为冻融灾害识别与寒区基础设施监测提供基础地形约束信息。\n
坡度数据揭示了研究区显著的地形空间异质性，整体呈现山区集中、平原开阔的格局特征。大兴安岭和小兴安岭山区以中高坡度地形为主，是多年冻土与冻融灾害发育的重要地貌单元；而西部高原及湖盆平原区域地形平缓，坡度多在低值范围内。该数据能够精细表征工程沿线边坡几何形态及微地形起伏，为识别潜在的坡面侵蚀、热融塌陷及重力变形敏感区提供关键地形参数。\n
坡向数据在30 m空间尺度上反映了复杂的坡面朝向格局，能够刻画多年冻土区典型的坡面辐射差异环境。不同坡向对应的太阳辐射接收条件差异显著，进而影响地表热量交换背景。该数据有助于描述区域尺度上坡面热环境分异特征，为分析工程两侧冻土稳定性差异及灾害空间分布提供重要辅助信息。", "ds_source": "
自主加工产生（基于公开高分辨率DEM影像）。", "ds_process_way": "
数据提取：使用ArcGIS/QGIS等软件的地形分析模块，采用三阶反平方和权算法（Horn算法）计算每个中心像元与其邻域像元的高度差。\n
坡度计算：提取各像元最大地面坡降角，精准识别大兴安岭主脉13°-20°的核心区域及局部超60°的陡坡。\n
坡向计算：计算水平投影方向的方位角，用于分析“阴阳坡”效应。\n
投影转换：为减小高纬度地区面积形变，统一转为Albers等积圆锥投影。", "ds_quality": "
本数据集所使用的基础数字高程模型（DEM）来源于Shuttle Radar Topography Mission（SRTM）。数据空间分辨率为 1 arc-second（约 30 m），高程基准为 WGS84 椭球，垂直基准为 EGM96 大地水准面。\n
在本研究中，DEM 数据经如下流程处理：采用双线性插值重采样方法统一为30 m空间分辨率栅格；基于 GIS 地形分析模块计算坡度与坡向参数，坡度单位为度（°），坡向采用 0°–360° 顺时针方位角表示；所有栅格数据统一投影至 WGS 84 / UTM Zone 52N 坐标系统 以保证空间一致性。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2000-12-31 00:00:00", "ds_acq_place": "东北多年冻土区", "ds_acq_lon_east": 135.0, "ds_acq_lat_south": 42.0, "ds_acq_lon_west": 115.0, "ds_acq_lat_north": 53.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 8249055407, "ds_files_count": 11, "ds_format": "*.tif", "ds_space_res": "30m", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "891d3848-10f5-4471-8fc4-88cd32d4c929.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 16:25:58", "last_updated": "2026-05-12 11:23:47", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7258.2026", "i18n": { "en": { "title": "30m slope and aspect data of the permafrost region in Northeast China (2000)", "ds_format": "*.tif", "ds_source": "
Independently processed (based on publicly available high-resolution DEM images).", "ds_quality": "
The basic digital elevation model (DEM) used in this dataset is derived from the Shuttle Radar Topography Mission (SRTM). The spatial resolution of the data is 1 arc second (approximately 30 meters), the elevation reference is the WGS84 ellipsoid, and the vertical reference is the EGM96 geoid.\r\n
In this study, DEM data was processed through the following process: bilinear interpolation resampling method was used to unify it into a 30m spatial resolution grid; Calculate slope and aspect parameters based on GIS terrain analysis module, with slope unit in degrees (°) and aspect represented by clockwise azimuth angles ranging from 0 ° to 360 °; All raster data is uniformly projected onto the WGS 84/UTM Zone 52N coordinate system to ensure spatial consistency.", "ds_ref_way": "", "ds_abstract": "
This data resource includes slope and aspect terrain factor data extracted based on a 30 meter resolution digital elevation model, covering the main engineering corridors and their surrounding areas in the permafrost region of Northeast China. The dataset focuses on the control effect of terrain morphology in permafrost regions on surface processes and engineering environmental stability, providing basic terrain constraint information for identifying freeze-thaw disasters and monitoring infrastructure in cold regions.\r\n
The slope data reveals significant topographic spatial heterogeneity in the study area, presenting an overall pattern of concentrated mountainous areas and open plains. The mountainous areas of Daxing'anling and Xiaoxing'anling are mainly characterized by medium to high slope terrain, which is an important geomorphic unit for the development of permafrost and freeze-thaw disasters over the years; The terrain in the western plateau and lake basin plain areas is gentle, with slopes mostly within the low range. This data can finely characterize the geometric shape and micro topography of slopes along the engineering route, providing key terrain parameters for identifying potential slope erosion, thermal collapse, and gravity deformation sensitive areas.\r\n
The slope orientation data reflects a complex slope orientation pattern at a spatial scale of 30 meters, which can characterize the typical slope radiation differential environment in permafrost regions. There are significant differences in the solar radiation reception conditions corresponding to different slope orientations, which in turn affect the background of surface heat exchange. This data helps to describe the characteristics of thermal environment differentiation on the uphill surface at the regional scale, providing important auxiliary information for analyzing the differences in frozen soil stability on both sides of the project and the spatial distribution of disasters.", "ds_time_res": "", "ds_acq_place": "Northeast Permafrost Region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
Data extraction: Using terrain analysis modules such as ArcGIS/QGIS, the third-order inverse sum of squares weight algorithm (Horn algorithm) is used to calculate the height difference between each central pixel and its neighboring pixels.\r\n
Slope calculation: Extract the maximum ground slope angle of each pixel, accurately identify the core area of the Daxing'an Mountains main vein at 13 ° -20 °, and locally steep slopes exceeding 60 °.\r\n
Slope calculation: Calculate the azimuth angle of the horizontal projection direction, used to analyze the \"yin-yang slope\" effect.\r\n
Projection conversion: To reduce the area deformation in high latitude regions, it is uniformly converted to Albers equal area cone projection.", "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": [ "数字高程模型", "坡度", "坡向" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "东北多年冻土区" ], "ds_time_tags": [ 2000 ], "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": "冻土" }