景观多样性是景观生态学与地理信息科学交叉领域的重要量化指标，被生态保护、资源管理、和规划决策等领域广为需求。 本数据集基于ARC-2024环北极土地覆盖产品（10米空间分辨率）提取50公里网格尺度景观多样性指数。该数据集运用Shannon多样性指数（SHDI）衡量各网格单元内土地覆盖类型的组成复杂度与异质性程度，指数值越高表明该网格内土地覆盖类型越丰富、分布越均匀。多样性指数计算基于9类土地覆盖类型：低灌木(LS)、直立矮灌木(DS)、草地(GR)、小型低矮草本植物(SF)、湿地(WL)、水域(WA)、苔藓地衣(ML)、裸地(BG)及冰雪(IS)。鉴于建筑用地(BA)在泛北极地区分布面积极为有限，本数据集未纳入该类别。该数据产品可有效支撑北极生态系统空间异质性评估、生物多样性热点识别、生态过渡带划定及气候变化对景观格局影响研究，为极地景观生态学研究提供量化分析基础。", "ds_source": "
本数据集以ARC-2024环北极土地覆盖产品（10米空间分辨率，总体精度87.78%，Kappa系数0.858）为数据源，通过景观格局指数算法完成50km×50km尺度的Shannon多样性指数计算。网格体系基于Albers等面积圆锥投影构建，确保各网格单元面积一致，多样性指数计算结果具有空间可比性。", "ds_process_way": "
（1）网格体系构建：基于Albers等面积圆锥投影构建覆盖泛北极区域的50km×50km规则网格体系，以确保景观格局分析的空间一致性与可比性。\n
（2）土地覆盖类型提取：将ARC-2024原始10米分辨率土地覆盖栅格数据与网格矢量进行空间叠加运算，逐网格统计9类土地覆盖类型的像元数量及面积占比。\n
（3）Shannon多样性指数计算：采用景观生态学标准公式SHDI = -∑(Pi × ln(Pi))计算各网格的Shannon多样性指数，其中Pi为第i类土地覆盖类型在网格内的面积比例。\n
（4）属性表构建：生成包含网格唯一标识符、中心点地理坐标、Shannon多样性指数值及类型丰富度等完整属性信息的矢量数据集。\n
（5）质量控制：剔除陆地面积不足网格总面积10%的边缘网格，并排除仅含单一土地覆盖类型的网格（多样性指数为0），以确保统计结果的生态学意义与科学性。", "ds_quality": "
本数据集质量取决于ARC-2024源产品的分类精度及多样性指数算法的计算精度。源产品总体精度达87.78%，Kappa系数为0.858，在不同生物气候亚区（A–E区）均保持稳定的分类性能。多样性指数计算采用景观生态学领域广泛认可的Shannon多样性指数公式，算法实现经过严格验证。数据集属性完整性经逐字段校验，确认无空值及异常值。50km×50km网格尺度适用于区域尺度景观格局宏观分析，具有明确的生态学依据。边缘网格及单一类型网格经严格质量筛选，有效保障了多样性指数的生态学可解释性。", "ds_acq_start_time": "2024-05-01 00:00:00", "ds_acq_end_time": "2024-10-31 00:00:00", "ds_acq_place": "泛北极区域", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": 55.79, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 84.08999999999999, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 94533, "ds_files_count": 2, "ds_format": "*.shp", "ds_space_res": "50 km × 50 km", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "Albers Equal Area Conic Projection System", "ds_thumbnail": "ee7d39b8-af04-46a3-b69c-2ac5d25a3a3e.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": [ "170.4599" ], "quality_level": 3, "publish_time": "2026-02-12 16:03:56", "last_updated": "2026-05-13 16:18:30", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ARCTIC-CHANGE.DB7125.2026", "i18n": { "en": { "title": "Distribution Map of 50km×50km Grid Landscape Diversity Index in the Arctic Region, 2024", "ds_format": "*.shp", "ds_source": "
This dataset utilizes the ARC-2024 Circumpolar Arctic Land Cover Product (10-meter spatial resolution, overall accuracy 87.78%, Kappa coefficient 0.858) as its data source, employing landscape pattern index algorithms to compute the Shannon Diversity Index at the 50km×50km scale. The grid system is constructed based on the Albers Equal Area Conic Projection, ensuring consistent area across all grid cells and spatial comparability of diversity index calculations.", "ds_quality": "
The quality of this dataset depends on both the classification accuracy of the ARC-2024 source product and the computational precision of the diversity index algorithm. The source product achieved an overall accuracy of 87.78% with a Kappa coefficient of 0.858, maintaining stable classification performance across different bioclimatic subzones (Zones A–E). The diversity index calculation employs the Shannon Diversity Index formula, which is widely recognized in the field of landscape ecology, with algorithm implementation rigorously validated. Dataset attribute completeness was verified through field-by-field inspection, confirming the absence of null and anomalous values. The 50km×50km grid scale is suitable for regional-scale macro-analysis of landscape patterns, with clear ecological rationale. Marginal grids and single-type grids underwent rigorous quality screening, effectively ensuring the ecological interpretability of diversity indices.", "ds_ref_way": "", "ds_abstract": "
Landscape diversity is a crucial quantitative indicator in the interdisciplinary field of landscape ecology and geographic information science (GIS), and is widely utilized in fields such as ecological conservation, resource management, and planning and decision-making. This dataset is derived from the ARC-2024 Circum-Arctic Land Cover Product (10 m spatial resolution) to extract landscape diversity indices at a 50 km grid scale. Employing Shannon's Diversity Index (SHDI), the dataset measures the compositional complexity and heterogeneity of land cover types within each grid cell—higher index values indicate a richer variety of land cover types and more uniform distribution in the corresponding grid. The diversity index calculation is based on nine land cover categories: Low Shrub (LS), Dwarf Shrub (DS), Grassland (GR), Sparse Forb (SF), Wetland (WL), Water Body (WA), Moss and Lichen (ML), Bare Ground (BG), and Ice and Snow (IS). Given the extremely limited spatial distribution of Built-up Area (BA) across the pan-Arctic region, this category was not included in the dataset. This data product can effectively support the assessment of spatial heterogeneity of Arctic ecosystems, identification of biodiversity hotspots, delineation of ecological transition zones, and research on the impacts of climate change on landscape patterns, thereby providing a quantitative analysis foundation for polar landscape ecology studies.", "ds_time_res": "", "ds_acq_place": "Circumpolar Arctic", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
(1) Grid System Construction: A 50km×50km regular grid system covering the Circumpolar Arctic region was established based on the Albers Equal Area Conic Projection to ensure spatial consistency and comparability in landscape pattern analysis. \r\n
(2) Land Cover Type Extraction: Spatial overlay operations were performed between the ARC-2024 original 10-meter resolution land cover raster data and grid vectors, with pixel counts and proportional coverage statistically computed for 9 land cover types per grid cell. \r\n
(3) Shannon Diversity Index Calculation: The Shannon Diversity Index for each grid was calculated using the standard landscape ecology formula SHDI = -∑(Pi × ln(Pi)), where Pi represents the proportional area of land cover type i within the grid.
(4) Attribute Table Construction: A vector dataset was generated containing complete attribute information including grid unique identifier, center point geographic coordinates, Shannon Diversity Index values, and type richness. \r\n
(5) Quality Control: Marginal grids with land area less than 10% of total grid area were excluded, along with grids containing only a single land cover type (diversity index equals 0), to ensure the ecological significance and scientific validity of statistical results.", "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": [ "泛北极", "景观多样性", "Shannon指数", "空间异质性", "土地覆盖" ], "ds_subject_tags": [ "地理学其他学科" ], "ds_class_tags": [], "ds_locus_tags": [ "泛北极" ], "ds_time_tags": [ 2024 ], "ds_contributors": [ { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" }, { "true_name": "曲歌", "email": "471920609@stu.lntu.edu.cn", "work_for": "辽宁工程技术大学", "country": "中国" }, { "true_name": "霍思慧", "email": "Huosihui@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" }, { "true_name": "马现伟", "email": "maxianwei_lntu@126.com", "work_for": "辽宁工程技术大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "曲歌", "email": "471920609@stu.lntu.edu.cn", "work_for": "辽宁工程技术大学", "country": "中国" }, { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "帅艳民", "email": "shuaiym@zjnu.edu.cn", "work_for": "浙江师范大学", "country": "中国" } ], "category": "极地" }