本数据集为黄河流域2000、2010、2020年3期区县级人口普查人口空间分布栅格数据，数据以全国区县第五、六、七次人口普查的数据为基础，先将Excel格式的人口数据矢量化，结合土地利用数据，通过分区密度制图模型完成区县级矢量数据的栅格化处理，将人口密度值分配至1km分辨率的像元，最终生成人口连续分布栅格，并统一投影至CGCS2000 Albers 坐标系。数据包含3个时期的人口密度栅格，时空范围覆盖整个黄河流域，时间间隔为10年，空间分辨率为 1km。", "ds_source": "
全国区县第五、六、七次人口普查数据。", "ds_process_way": "
基于全国第五、六、七次人口普查的区县级人口数据，结合各县级行政区矢量化并基于行政区面积计算得到 2000、2010、2020 年三期区县级人口密度；其次，以同期土地利用数据为空间参考，采用分区密度制图模型，将县级矢量数据进行栅格化处理，把人口密度值分配至 1km×1km 的像元，生成人口连续分布栅格；最后，将所有栅格数据统一转换至 CGCS2000 Albers 投影坐标系，完成数据格式与空间基准的标准化处理，形成最终的黄河流域2000、2010、2020年3期县级人口普查人口空间分布数据集。", "ds_quality": "
本数据源自2000、2010、2020年全国区县第五、六、七次人口普查数据，反映当时人口空间分布信息。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "黄河流域", "ds_acq_lon_east": 121.23694444444445, "ds_acq_lat_south": 31.310000000000002, "ds_acq_lon_west": 94.5, "ds_acq_lat_north": 42.59388888888889, "ds_acq_alt_low": null, "ds_acq_alt_high": 6009.0, "ds_share_type": "login-access", "ds_total_size": 12439663, "ds_files_count": 4, "ds_format": "GeoTIFF", "ds_space_res": "1000", "ds_time_res": "10年", "ds_coordinate": "CGCS2000", "ds_projection": "Albers", "ds_thumbnail": "51cea538-4714-4c18-b464-df989950d157.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "76330c66-832b-46b3-b501-f5f6edb08dc2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4520" ], "quality_level": 3, "publish_time": "2026-01-29 15:15:06", "last_updated": "2026-02-05 17:11:51", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB7079.2026", "i18n": { "en": { "title": "Population Spatial Distribution Data from the County-Level Census for the Years 2000, 2010, and 2020", "ds_format": "GeoTIFF", "ds_source": "
The Fifth, Sixth, and Seventh National Census Data at the District and County Levels.", "ds_quality": "
The data presented in this study originate from the Fifth, Sixth, and Seventh National Census conducted at the district and county levels in China during 2000, 2010, and 2020 respectively, reflecting the spatial distribution patterns of population at corresponding time points.", "ds_ref_way": "", "ds_abstract": "
This dataset comprises three periods (2000, 2010, and 2020) of county-level population census spatial distribution raster data for the Yellow River Basin. Based on the fifth, sixth, and seventh national population censuses at the county level, the Excel-formatted population data were first vectorized. These vector data were then combined with land use information to perform rasterization processing through a zonal density mapping model. Population density values were allocated to 1 km resolution cells, ultimately generating continuous population distribution rasters. All datasets were projected into the CGCS2000 Albers coordinate system. The data include population density rasters from three distinct time periods, covering the entire Yellow River Basin with a temporal interval of 10 years and a spatial resolution of 1 km.", "ds_time_res": "10年", "ds_acq_place": "Yellow River Basin", "ds_space_res": "1000", "ds_projection": "", "ds_process_way": "
Based on county-level population data from the Fifth, Sixth, and Seventh National Censuses of China, combined with vectorized administrative boundary data of county-level divisions and calculated based on administrative area, three periods (2000, 2010, and 2020) of county-level population density were obtained. Subsequently, using contemporaneous land use data as spatial reference, a zonal density mapping model was applied to rasterize the county-level vector data through gridding processing, thereby assigning population density values to 1 km × 1 km cells and generating continuous population distribution rasters. Finally, all raster datasets were uniformly transformed into the CGCS2000 Albers projection coordinate system to standardize data formats and spatial references, resulting in the final spatial distribution dataset of county-level census population data for the Yellow River Basin across the three periods (2000, 2010, and 2020).", "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, "belong_to_nieer": false, "ds_topic_tags": [ "黄河流域", "人口空间分布", "栅格数据" ], "ds_subject_tags": [ "人文地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黄河流域" ], "ds_time_tags": [ 2000, 2010, 2020 ], "ds_contributors": [ { "true_name": "张举涛", "email": "jutzhang@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": "李雪娇", "email": "lixuejiao@nieer.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": "苏迎庆", "email": "yingqingsu@nieer.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": "刘蔚", "email": "weiliu@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": "朱猛", "email": "zhumeng@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": "廖芮", "email": "liaorui@nieer.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "张举涛", "email": "jutzhang@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": "李雪娇", "email": "lixuejiao@nieer.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": "苏迎庆", "email": "yingqingsu@nieer.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": "刘蔚", "email": "weiliu@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": "朱猛", "email": "zhumeng@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": "廖芮", "email": "liaorui@nieer.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "张举涛", "email": "jutzhang@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "社会经济文化" }