世界人口网格化第4版行政单位中心点与人口估计
世界人口网格化第4版（GPWv4）。带有人口估计的行政单位中心点，修订版11包括2000年、2005年、2010年、2015年和2020年的联合国世界人口方案调整后的人口估计和密度，以及2010年的基本人口特征（年龄和性别）。该数据集还包括行政名称、土地和水域面积，以及按行政单位中心点（中心点）位置划分的数据背景。中心点是基于GPWv4中使用的大约1350万个输入行政单位，因此，这些文件需要能够将大量数据读入内存的硬件和软件。
目的：提供GPWv4中使用的输入行政单位的矢量（点）版本，包括人口估计、密度、2010年基本人口特征，以及行政名称、面积和数据背景，以便在数据整合中使用。
代码：
var gpw = ee.FeatureCollection("projects/sat-io/open-datasets/sedac/gpw-v4-admin-unit-center-points-population-estimates-rev11"); Map.addLayer(ee.FeatureCollection(gpw),{},'gpw-v4-admin-center-points-rev11')
矢量数据属性表：
| Feature Index | A00_04B (Float) | A00_04F (Float) | A00_04M (Float) | A05_09B (Float) | A05_09F (Float) | A05_09M (Float) | A10_14B (Float) | A10_14F (Float) | A10_14M (Float) | A15_19B (Float) | A15_19F (Float) | A15_19M (Float) | A20_24B (Float) | A20_24F (Float) | A20_24M (Float) | A25_29B (Float) | A25_29F (Float) | A25_29M (Float) | A30_34B (Float) | A30_34F (Float) | A30_34M (Float) | A35_39B (Float) | A35_39F (Float) | A35_39M (Float) | A40_44B (Float) | A40_44F (Float) | A40_44M (Float) | A45_49B (Float) | A45_49F (Float) | A45_49M (Float) | A50_54B (Float) | A50_54F (Float) | A50_54M (Float) | A55_59B (Float) | A55_59F (Float) | A55_59M (Float) | A60_64B (Float) | A60_64F (Float) | A60_64M (Float) | A65PLUSB (Float) | A65PLUSF (Float) | A65PLUSM (Float) | A65_69B (Float) | A65_69F (Float) | A65_69M (Float) | A70PLUSB (Float) | A70PLUSF (Float) | A70PLUSM (Float) | A70_74B (Float) | A70_74F (Float) | A70_74M (Float) | A75PLUSB (Float) | A75PLUSF (Float) | A75PLUSM (Float) | A75_79B (Float) | A75_79F (Float) | A75_79M (Float) | A80PLUSB (Float) | A80PLUSF (Float) | A80PLUSM (Float) | A80_84B (Float) | A80_84F (Float) | A80_84M (Float) | A85PLUSB (Float) | A85PLUSF (Float) | A85PLUSM (Float) | B_2010_E (Float) | CENTROID_X (Float) | CENTROID_Y (Float) | CONTEXT (Integer) | CONTEXT_NM (String) | COUNTRYNM (String) | F_2010_E (Float) | GUBID (String) | INSIDE_X (Float) | INSIDE_Y (Float) | ISOALPHA (String) | LAND_A_KM (Float) | M_2010_E (Float) | NAME1 (String) | NAME2 (String) | NAME3 (String) | NAME4 (String) | NAME5 (String) | NAME6 (String) | TOTAL_A_KM (Float) | UN_2000_DS (Float) | UN_2000_E (Long) | UN_2005_DS (Float) | UN_2005_E (Long) | UN_2010_DS (Float) | UN_2010_E (Long) | UN_2015_DS (Float) | UN_2015_E (Long) | UN_2020_DS (Float) | UN_2020_E (Long) | WATER_A_KM (Float) | WATER_CODE (String) | system:index (String) |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | -43.5595403393 | -19.3252575766 | 0 | Not applicable | Brazil | 2 | {42464A48-60A0-4ED1-B57C-8B48CD18754A} | -43.5595403393 | -19.3252575766 | BRA | 26.7675033417 | 5 | Minas Gerais | SANTANA DO RIACHO | SERRA DO CIPO | SERRA DO CIPO | 315900110000004 | NA | 26.7675033417 | 0.251654348805 | 7 | 0.264475109663 | 7 | 0.272297089116 | 7 | 0.277452147384 | 7 | 0.27967126833 | 7 | 0 | L | |
| 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 2 | 1 | 1 | 3 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | -43.7991016004 | -19.9832664835 | 0 | Not applicable | Brazil | 3 | {EBA9FA5C-69EF-48E3-9588-23408CCC4003} | -43.7991016004 | -19.9832664835 | BRA | 1.63870372643 | 5 | Minas Gerais | RAPOSOS | RAPOSOS | RAPOSOS | 315390505000015 | NA | 1.63870372643 | 4.70730567322 | 8 | 4.94217901005 | 8 | 5.08326054154 | 8 | 5.17431860928 | 8 | 5.2104908035 | 9 | 0 | L | |
| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1 | 1 | 3 | 2 | 1 | 1 | 1 | 0 | 2 | 1 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 9 | -43.6810336371 | -17.892245422 | 0 | Not applicable | Brazil | 3 | {1EE63B36-32A8-4C5A-9395-6E30704C56AA} | -43.6810336371 | -17.892245422 | BRA | 196.774706684 | 6 | Minas Gerais | DIAMANTINA | INHAI | INHAI | 312160530000004 | NA | 196.774706684 | 0.0456726696786 | 9 | 0.0471196781765 | 9 | 0.0476240208853 | 9 | 0.0476361553958 | 9 | 0.0471370084339 | 9 | 0 | L | |
| 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 9 | -44.067915103 | -19.603577114 | 0 | Not applicable | Brazil | 4 | {75F71A7A-DD3F-422A-9450-5A482CE3E63A} | -44.067915103 | -19.603577114 | BRA | 4.20270140151 | 5 | Minas Gerais | PEDRO LEOPOLDO | PEDRO LEOPOLDO | PEDRO LEOPOLDO | 314930905000033 | NA | 4.20270140151 | 2.03821973673 | 9 | 2.15387248044 | 9 | 2.22980455796 | 9 | 2.28454916732 | 10 | 2.31552188142 | 10 | 0 | L | |
| 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 1 | 0 | 1 | 2 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 2 | 1 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | -44.7811337617 | -23.1200534578 | 0 | Not applicable | Brazil | 3 | {0751F980-4B42-4B73-BC6C-C4D3DA07668A} | -44.7811337617 | -23.1200534578 | BRA | 54.4731117239 | 8 | Rio de Janeiro | PARATY | PARATY | PARATY | 330380705000029 | NA | 54.4731117239 | 0.164436258772 | 9 | 0.187863125141 | 10 | 0.210263226687 | 11 | 0.232901349968 | 13 | 0.255208630303 | 14 | 0 | L | |
| 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 4 | 1 | 3 | 2 | 0 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | -43.9500190254 | -22.7931133552 | 0 | Not applicable | Brazil | 3 | {850652A7-51D7-46E8-BF7D-882C5C57FB9C} | -43.9500190254 | -22.7931133552 | BRA | 97.0767253612 | 9 | Rio de Janeiro | RIO CLARO | SAO JOAO MARCOS | SAO JOAO MARCOS | 330440925000004 | NA | 109.003096119 | 0.119311766706 | 12 | 0.125202269435 | 12 | 0.128711974382 | 12 | 0.13095214071 | 13 | 0.131801672792 | 13 | 11.9263707577 | L | |
| 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 1 | 2 | 2 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | -43.7011305173 | -22.4946956777 | 0 | Not applicable | Brazil | 5 | {42D31B18-8E1B-4E10-910E-D0972660162B} | -43.7011305173 | -22.4946956777 | BRA | 1.39505886545 | 7 | Rio de Janeiro | MENDES | MENDES | MENDES | 330280905000033 | NA | 1.39505886545 | 8.58099364087 | 12 | 8.85728553084 | 12 | 8.95656613297 | 12 | 8.96332879608 | 13 | 8.87384396898 | 12 | 0 | L | |
| 7 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | -44.6567868318 | -23.0897034345 | 0 | Not applicable | Brazil | 4 | {C1280B3D-D3B5-4E73-888F-61618BAA008C} | -44.640792633 | -23.071472843 | BRA | 1.24001939392 | 8 | Rio de Janeiro | PARATY | PARATY | PARATY | 330380705000035 | NA | 1.24001939392 | 7.8802474508 | 10 | 9.00292869743 | 11 | 10.0764044893 | 12 | 11.1612869514 | 14 | 12.2303144902 | 15 | 0 | L | |
| 8 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 2 | 2 | 0 | 2 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | -40.4485026469 | -20.0247911487 | 0 | Not applicable | Brazil | 4 | {EB27AB9D-06E9-4671-893E-AFB9B62FD44D} | -40.4485026469 | -20.0247911487 | BRA | 0.101316903409 | 8 | Espirito Santo | SANTA LEOPOLDINA | DJALMA COUTINHO | DJALMA COUTINHO | 320450010000001 | NA | 0.101316903409 | 124.709663619 | 13 | 125.296004376 | 13 | 123.325294865 | 12 | 120.130698461 | 12 | 115.763196865 | 12 | 0 | L | |
| 9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 2 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | -44.2527626164 | -22.4057957975 | 0 | Not applicable | Brazil | 7 | {E54E00BF-51D9-4181-AFDB-BEBFA9ED0DFD} | -44.2527626164 | -22.4057957975 | BRA | 0.0500853236047 | 5 | Rio de Janeiro | QUATIS | QUATIS | QUATIS | 330412805000033 | NA | 0.0500853236047 | 207.37185642 | 10 | 229.798816409 | 12 | 249.473021007 | 12 | 268.031775839 | 13 | 284.881108896 | 14 | 0 | L |
数据集引用：
Doxsey-Whitfield, Erin, Kytt MacManus, Susana B. Adamo, Linda Pistolesi, John Squires, Olena Borkovska, and Sandra R. Baptista. "Taking advantage of the improved availability of census data: a first look at the gridded population of the world, version 4." Papers in Applied Geography 1, no. 3 (2015): 226-234.
有关数据文档介绍：
Data Collection Documentation:
- GPWv4 Revision 11 documentation (PDF)
- Country-level Information and Sources Revision 11 (Microsoft Excel .xlsx file)
- Log of changes to the data set by version
Additional Documentation:
- Detailed descriptions of the methods and improvements made in the GPWv4 data collection are described in the following paper by Doxsey-Whitfield et al. (2015): Taking Advantage of the Improved Availability of Census Data: A First Look at the Gridded Population of the World, Version 4 (GPWv4)
- NASA EarthData Webinar: Discover NASA’s Updated Gridded Population of the World Data, January 2015 (1 hour long)
共享许可：本作品采用知识共享署名4.0许可。你可以自由地复制和重新发布任何媒介或格式的材料，并为任何目的，甚至为商业目的而改造和建立材料。你必须给予适当的方式，提供许可证的链接，并说明是否进行了修改。
策划者：Samapriya Roy
关键词：人口普查地理学、GPWv4、网格化人口、均匀分布
最后更新。2021-04-07
