冬季道路是泛北极地区社会经济的生命线，为依赖于不同载具的多种运输场景提供了季节性通道。然而，由于现有冬季道路潜在区的识别基于较为单一且固定的环境条件阈值，无法量化冬季道路潜在区的承载力，目前在泛北极地区仍缺乏面对应不同载具的冬季道路潜在区承载力分级数据。为区分冬季道路潜在区的承载力等级，我们在传统环境条件阈值的基础上，进一步考虑了土壤冻结深度和湖冰厚度对应的承载力，并结合泛北极地区常见载具总重量类别对承载力进行分级。由此生产了2003–2022水文年泛北极地区冷季（10月–5月）的月度冬季道路潜在区承载力分级数据，空间分辨率为0.1°。数值类型为字节型，范围为0–5。其中，0表示非冬季道路潜在区或冬季道路潜在区的承载力（P < 0.5 t）不足以支撑超轻型载具（如雪橇和雪地摩托）；1–5表示承载力（对应载具重量）逐渐提高的冬季道路潜在区，1表示承载力（0.5 t ≤ P < 5 t）可支撑超轻型载具，2表示承载力（5 t ≤ P < 12 t）可支撑轻型载具（如小客车和皮卡），3表示承载力（12 t ≤ P < 36 t）可支撑中型载具（如大客车和中型箱式卡车），4表示承载力（36 t ≤ P < 55 t）可支撑重型载具（如大型卡车和牵引车），5表示承载力（P ≥ 55 t）可支撑超重型载具（如搅拌车和自卸卡车）。该数据为泛北极地区的交通运输和可达性研究提供基础数据支持。", "ds_source": "
用于识别冬季道路潜在区及其承载力的环境栅格数据包括：（1）ERA5-Land全球陆地再分析产品，以0.1°分辨率提供月度地表温度、雪深、多层土壤温度和体积含水量以及湖冰厚度等数据（https://doi.org/10.24381/cds.68d2bb30）；（2）MOD44W v006，250 m分辨率的全球水体分布产品，源于Terra卫星上的中分辨率成像光谱仪观测（https://doi.org/10.5067/MODIS/MOD44W.006）；（3）Global River Widths from Landsat数据集，刻画了30m分辨率的全球河流分布（https://zenodo.org/records/1297434）；（4）ETOPO1，1'分辨率的全球高程数据（https://doi.org/10.7289/V5C8276M）以及（5）VectorMap0，1：100万地理要素矢量数据，包含陆地冰川范围（https://gis-lab.info/qa/vmap0-eng.html）。\n我们编制的泛北极载具重量分类用于划分冬季道路潜在区的承载力等级。该分类包含了美国联邦公路管理局定义的载具总重分类中的轻型、中型和重型载具（https://afdc.energy.gov/data/10380），并补充了超轻型（如雪橇和雪地摩托）和超重型（重量超过重型载具范围）这两类文献中报告的在冬季道路上运行的载具。取每类载具中的最大总重量作为冬季道路潜在区可支撑该类载具的承载力阈值。", "ds_process_way": "
（1）根据下列环境条件阈值确定冬季道路潜在区：地表气温≤ 0 ℃，陆上积雪厚度≥ 20 cm，非山区（高程 < 500 m且坡度 < 5%）和非冰川区。\n
（2）在冬季道路潜在区，分别利用Shoop公式和Gold公式在陆上和冰上部分根据土壤冻结深度（由多层土壤温度线性插值得到0 ℃处的土壤深度表示）和湖冰厚度计算相应的承载力。\n
（3）采用泛北极载具重量分类划分冬季道路潜在区的承载力等级。", "ds_quality": "
数据集的生产方法具有科学性，其中冬季道路潜在区的环境条件阈值、陆上和冰上部分承载力的计算公式以及泛北极载具重量分类用于研究和工程中。输入数据为为权威的遥感产品或最先进的再分析数据，能确保生产高质量数据。本数据集的时空分辨率较高（0.1°，月度），覆盖的时空范围广（60°N–85°N的泛北极地区，近20年（2002–2023水文年）冷季共160个月份）。", "ds_acq_start_time": "2003-10-01 00:00:00", "ds_acq_end_time": "2022-05-31 00:00:00", "ds_acq_place": "泛北极地区", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 60.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 85.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 4728573, "ds_files_count": 2, "ds_format": "Geotiff", "ds_space_res": "11132 m （0.1°）", "ds_time_res": "月", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "9f13d5d1-adf6-42cb-9acb-8c068f8f5634.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": [ "410" ], "quality_level": 3, "publish_time": "2026-05-13 15:11:16", "last_updated": "2026-05-13 15:38:51", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ARCTIC-CHANGE.DB7141.2026", "i18n": { "en": { "title": "Monthly Winter Road Potential Zone Carrying Capacity Grading Dataset for the Pan Arctic (Hydrological Years 2003-2022)", "ds_format": "Geotiff", "ds_source": "
Environmental raster datasets used to identify potential winter roads and their bearing capacity include: (1) ERA5-Land, a global reanalysis dataset that provides monthly land surface temperature, snow depth, multi-layer soil temperature and volumetric water content, and lake ice thickness data at 0.1° resolution (https://doi.org/10.24381/cds.68d2bb30); (2) MOD44W v006, a global map of surface water derived from Terra Moderate Resolution Imaging Spectroradiometer images at 250 m resolution (https://doi.org/10.5067/MODIS/MOD44W.006); (3) Global River Widths from Landsat, which characterizes global river distribution at 30 m resolution (https://zenodo.org/records/1297434); (4) ETOPO1, global elevation data at 1 arc-minute resolution (https://doi.org/10.7289/V5C8276M); and (5) VectorMap0, a 1:1000000 geographical element vector data, including land ice areas (https://gis-lab.info/qa/vmap0-eng.html).\r\n
To classify the bearing capacity of potential winter roads, we compiled the pan-Arctic vehicle weight category. It includes light, medium, and heavy vehicles as defined by the Federal Highway Administration's Gross Vehicle Weight Rating Category (https://afdc.energy.gov/data/10380), and are supplemented by super-light (e.g., sleds and snowmobiles) and super-heavy vehicles (exceeding the heavy vehicle weight range) reported to operate on winter roads in the literature. The maximum gross weight of each vehicle class was used as the bearing threshold that potential winter roads can support for that vehicle class.", "ds_quality": "
The dataset was produced using scientifically established methods, including environmental thresholds for identifying potential winter roads, formulas for estimating bearing capacity in land- and ice-sections, and the pan-Arctic vehicle weight category, all of which are widely applied in research and engineering. The input data consist of authoritative remote sensing products and state-of-the-art reanalysis datasets, ensuring high data quality. The dataset provides relatively high spatiotemporal resolution (0.1°, monthly) and broad coverage, spanning the Pan-Arctic region from 60°N to 85°N over 160 cold-season months during water years 2002–2023.", "ds_ref_way": "", "ds_abstract": "
Winter roads are the lifeline of the socio economy in the Pan Arctic region, providing seasonal pathways for various transportation scenarios that rely on different vehicles. However, due to the fact that the identification of potential winter road areas is based on a relatively single and fixed environmental threshold, it is impossible to quantify the carrying capacity of potential winter road areas. Currently, there is still a lack of graded data on the carrying capacity of potential winter road areas for different vehicles in the Pan Arctic region. To distinguish the bearing capacity levels of potential winter road areas, we further considered the bearing capacity corresponding to soil freezing depth and lake ice thickness based on traditional environmental threshold values, and classified the bearing capacity based on the total weight categories of common vehicles in the Pan Arctic region. Thus, monthly winter road potential carrying capacity classification data for the cold season (October May) in the Pan Arctic region from 2003 to 2022 hydrological years were produced, with a spatial resolution of 0.1 °. The numerical type is byte type, with a range of 0-5. Among them, 0 indicates that the bearing capacity (P<0.5 t) of non winter road potential areas or winter road potential areas is insufficient to support ultra light vehicles (such as sleds and snowmobiles); 1-5 represents the potential area of winter roads where the carrying capacity (corresponding to the weight of the vehicle) gradually increases. 1 represents the carrying capacity (0.5 t ≤ P<5 t) that can support ultra light vehicles, 2 represents the carrying capacity (5 t ≤ P<12 t) that can support light vehicles (such as small buses and pickups), 3 represents the carrying capacity (12 t ≤ P<36 t) that can support medium vehicles (such as buses and medium box trucks), 4 represents the carrying capacity (36 t ≤ P <55 t) that can support heavy vehicles (such as large trucks and tractors), and 5 represents the carrying capacity (P ≥ 55 t) that can support ultra heavy vehicles (such as mixer trucks and dump trucks). This data provides basic data support for transportation and accessibility research in the Pan Arctic region.", "ds_time_res": "", "ds_acq_place": "Pan Arctic region", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
(1) Potential winter roads were identified using the following environmental thresholds: land surface temperature ≤ 0 ℃, land snow depth ≥ 20 cm, non-mountainous areas (elevation < 500 m and slope < 5%), and non-glacial areas. \r\n
(2) For potential winter roads, Shoop's formula and Gold's formula were applied to estimate bearing capacity in land- and ice-sections, respectively, based on soil freeze depth (defined as the soil depth at 0 ℃ interpolated from multi-layer soil temperature) and lake ice thickness. \r\n
(3) The bearing capacity level of potential winter roads was then classified according to the pan-Arctic vehicle weight category.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 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": [ "冬季道路潜在区", "承载力等级", "载具重量", "泛北极地区" ], "ds_subject_tags": [ "工程与技术科学基础学科" ], "ds_class_tags": [], "ds_locus_tags": [ "泛北极地区" ], "ds_time_tags": [ 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "陈力原", "email": "lychen@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "朱文泉", "email": "zhuwq75@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "陈力原", "email": "lychen@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "陈力原", "email": "lychen@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "category": "极地" }