{ "created": "2026-06-15 17:44:59", "updated": "2026-10-27 08:15:49", "id": "3b16d0c9-994c-4f95-8f6b-06e8b36ddeab", "version": 3, "ds_topic": null, "title_cn": "全球人口数据（1901-2021）", "title_en": "Global population data", "ds_abstract": "

本数据集为全球历史人口栅格数据，空间范围为全球，时间范围为 1901—2021 年，时间分辨率为年（逐年），空间分辨率为 0.5°×0.5°（30 弧分）。数据实体为 NetCDF 格式文件 population_histsoc_30arcmin_annual_1901_2021.nc（含同名 .aux.xml 统计信息文件），栅格值表示各 0.5° 网格内的人口数量，数值范围为 0 至约 220 万（后期年份单栅格最大值约 222.8 万），用于全球城乡人口对干旱-热浪复合事件暴露程度的分析。

", "ds_source": "

来自ISIMIP数据库 https://data.isimip.org/search/tree/ISIMIP2a/InputData/geo_conditions/tree/ISIMIP2b/tree/ISIMIP3a/tree/ISIMIP3b/tree/ISIMIP2a/InputData/socioeconomic/pop/

", "ds_process_way": "", "ds_quality": "

ISIMIP 为国际权威的跨行业影响模型对比计划，其人口数据基于历史人口统计重建，来源可信、被广泛使用，处理规范。局限在于：空间分辨率较粗（0.5°），难以刻画城市内部人口分布的细节；历史人口数据在早期年份及统计薄弱地区存在一定的估算与插值不确定性。

", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 65757304, "ds_files_count": 1, "ds_format": "NetCDF文件", "ds_space_res": "0.5°≈30弧分", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "WGS84", "ds_thumbnail": "3b16d0c9-994c-4f95-8f6b-06e8b36ddeab.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "ISIMIP数据引用规范如下：\r\nFranziska Piontek, Tobias Geiger (2017): ISIMIP2a population input data (v1.0). ISIMIP Repository. https://doi.org/10.48364/ISIMIP.523208", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 1, "publish_time": "2026-10-27 10:16:14", "first_publish_time": null, "last_updated": "2026-10-27 10:16:14", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "extra": null, "files_shape": [ { "name": "population_histsoc_30arcmin_annual_1901_2021.zip", "size": 65757304, "is_dir": false } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "Global population data", "ds_abstract": "This dataset contains historical population data at the global level. The spatial range covers the entire world, while the time period ranges from 1901 to 2021. The time resolution is annual, and the spatial resolution is 0.5° × 0.5° (equivalent to 30 arcminutes). The data is stored in NetCDF format, with the file name population_histsoc_30arcmin_annual_1901_2021.nc. An accompanying .aux.xml file provides statistical information for each grid cell. The values represent the population density within each 0.5° grid cell. The numerical range is from 0 to approximately 2.2 million people per cell. This dataset is useful for analyzing the exposure to drought and heatwave events across different urban and rural areas around the world.", "ds_source": "

From the ISIMIP database: https://data.isimip.org/search/tree/ISIMIP2a/InputData/geo_conditions/tree/ISIMIP2b/tree/ISIMIP3a/tree/ISIMIP3b/tree/ISIMIP2a/InputData/socioeconomic/pop/

", "ds_process_way": "* According to the research requirements, it has been determined to use the historical social population data provided by ISIMIP. This data covers the years from 1901 to 2021, with annual data for a global population grid of 30 arcminutes (0.5°). \r\n* The global population data is stored in NetCDF format. Additionally, statistical information files in .aux.xml format are generated alongside these data,以便于在ArcGIS and other software applications for analysis.", "ds_quality": "ISIMIP is an internationally recognized cross-industry impact modeling comparison program. Its population data is based on historical statistical data, making it reliable and widely used. However, its limitations include: relatively low spatial resolution (0.5°), which makes it difficult to capture detailed information about population distribution within cities; there is also some uncertainty in the estimation and interpolation methods used for historical population data in earlier years and areas with weak statistical data.", "ds_acq_place": "", "ds_ref_instruction": "", "ds_ref_way": "", "ds_format": "", "ds_projection": "", "ds_space_res": "", "ds_time_res": "" } }, "license_type": null, "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": [ "SPEI", "数据库", "全球" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 ], "ds_contributors": [ "李涛" ], "ds_meta_authors": [ "李涛" ], "ds_managers": [ "包安明" ], "category": "生态环境" }