ለውጦች
On ሃምሌ 4, 2022, 14:59:32 (SAST),
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Moved Uganda: High Resolution Population Density Maps + Demographic Estimates from organization HDX - The Humanitarian Data Exchange to organization Open Cities Lab
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2 | "author": "Data for Good at Meta", | 2 | "author": "Data for Good at Meta", | ||
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23 | The Hague. OCHA is part of the United Nations Secretariat and is | ||||
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25 | coherent response to emergencies. The HDX team includes OCHA staff and | ||||
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20 | "name": "population", | 40 | "name": "population", | ||
21 | "title": "Population " | 41 | "title": "Population " | ||
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26 | "license_id": "cc-by", | 46 | "license_id": "cc-by", | ||
27 | "license_title": "Creative Commons Attribution", | 47 | "license_title": "Creative Commons Attribution", | ||
28 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 48 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
29 | "maintainer": "Heiko Heilgendorff (OCL)", | 49 | "maintainer": "Heiko Heilgendorff (OCL)", | ||
30 | "maintainer_email": "[email protected]", | 50 | "maintainer_email": "[email protected]", | ||
31 | "metadata_created": "2021-06-09T14:36:58.143264", | 51 | "metadata_created": "2021-06-09T14:36:58.143264", | ||
n | 32 | "metadata_modified": "2022-06-15T17:32:47.485726", | n | 52 | "metadata_modified": "2022-07-04T12:59:32.551477", |
33 | "name": | 53 | "name": | ||
34 | uganda-high-resolution-population-density-maps-demographic-estimates", | 54 | uganda-high-resolution-population-density-maps-demographic-estimates", | ||
35 | "notes": "VERSION 1.5. The world's most accurate population | 55 | "notes": "VERSION 1.5. The world's most accurate population | ||
36 | datasets. Seven maps/datasets for the distribution of various | 56 | datasets. Seven maps/datasets for the distribution of various | ||
37 | populations in Uganda: (1) Overall population density (2) Women (3) | 57 | populations in Uganda: (1) Overall population density (2) Women (3) | ||
38 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | 58 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | ||
39 | 60+) (7) Women of reproductive age (ages 15-49).\r\n\r\n### | 59 | 60+) (7) Women of reproductive age (ages 15-49).\r\n\r\n### | ||
40 | Methodology\r\n\r\nThese high-resolution maps are created using | 60 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
41 | machine learning techniques to identify buildings from commercially | 61 | machine learning techniques to identify buildings from commercially | ||
42 | available satellite images. This is then overlayed with general | 62 | available satellite images. This is then overlayed with general | ||
43 | population estimates based on publicly available census data and other | 63 | population estimates based on publicly available census data and other | ||
44 | population statistics at Columbia University. The resulting maps are | 64 | population statistics at Columbia University. The resulting maps are | ||
45 | the most detailed and actionable tools available for aid and research | 65 | the most detailed and actionable tools available for aid and research | ||
46 | organizations. For more information about the methodology used to | 66 | organizations. For more information about the methodology used to | ||
47 | create our high resolution population density maps and the demographic | 67 | create our high resolution population density maps and the demographic | ||
48 | distributions, click | 68 | distributions, click | ||
49 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | 69 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | ||
50 | information about how to use HDX to access these datasets, please | 70 | information about how to use HDX to access these datasets, please | ||
51 | visit: | 71 | visit: | ||
52 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 72 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
53 | to match the census population with the UN estimates are applied at | 73 | to match the census population with the UN estimates are applied at | ||
54 | the national level. The UN estimate for a given country (or | 74 | the national level. The UN estimate for a given country (or | ||
55 | state/territory) is divided by the total census estimate of population | 75 | state/territory) is divided by the total census estimate of population | ||
56 | for the given country. The resulting adjustment factor is multiplied | 76 | for the given country. The resulting adjustment factor is multiplied | ||
57 | by each administrative unit census value for the target year. This | 77 | by each administrative unit census value for the target year. This | ||
58 | preserves the relative population totals across administrative units | 78 | preserves the relative population totals across administrative units | ||
59 | while matching the UN total. More information can be found | 79 | while matching the UN total. More information can be found | ||
60 | ocs/census-information-for-high-resolution-population-density-maps/)", | 80 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
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64 | "approval_status": "approved", | 84 | "approval_status": "approved", | ||
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497 | { | 511 | { | ||
498 | "display_name": "population", | 512 | "display_name": "population", | ||
499 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | 513 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | ||
500 | "name": "population", | 514 | "name": "population", | ||
501 | "state": "active", | 515 | "state": "active", | ||
502 | "vocabulary_id": null | 516 | "vocabulary_id": null | ||
503 | }, | 517 | }, | ||
504 | { | 518 | { | ||
505 | "display_name": "population density", | 519 | "display_name": "population density", | ||
506 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 520 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
507 | "name": "population density", | 521 | "name": "population density", | ||
508 | "state": "active", | 522 | "state": "active", | ||
509 | "vocabulary_id": null | 523 | "vocabulary_id": null | ||
510 | }, | 524 | }, | ||
511 | { | 525 | { | ||
512 | "display_name": "reproductive", | 526 | "display_name": "reproductive", | ||
513 | "id": "6fb38736-99e6-40c9-b3b3-da34da5e6cf5", | 527 | "id": "6fb38736-99e6-40c9-b3b3-da34da5e6cf5", | ||
514 | "name": "reproductive", | 528 | "name": "reproductive", | ||
515 | "state": "active", | 529 | "state": "active", | ||
516 | "vocabulary_id": null | 530 | "vocabulary_id": null | ||
517 | }, | 531 | }, | ||
518 | { | 532 | { | ||
519 | "display_name": "women", | 533 | "display_name": "women", | ||
520 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 534 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
521 | "name": "women", | 535 | "name": "women", | ||
522 | "state": "active", | 536 | "state": "active", | ||
523 | "vocabulary_id": null | 537 | "vocabulary_id": null | ||
524 | }, | 538 | }, | ||
525 | { | 539 | { | ||
526 | "display_name": "youth", | 540 | "display_name": "youth", | ||
527 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 541 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
528 | "name": "youth", | 542 | "name": "youth", | ||
529 | "state": "active", | 543 | "state": "active", | ||
530 | "vocabulary_id": null | 544 | "vocabulary_id": null | ||
531 | } | 545 | } | ||
532 | ], | 546 | ], | ||
533 | "title": "Uganda: High Resolution Population Density Maps + | 547 | "title": "Uganda: High Resolution Population Density Maps + | ||
534 | Demographic Estimates", | 548 | Demographic Estimates", | ||
535 | "type": "dataset", | 549 | "type": "dataset", | ||
536 | "url": | 550 | "url": | ||
537 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-uga", | 551 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-uga", | ||
538 | "version": "" | 552 | "version": "" | ||
539 | } | 553 | } |