Veranderingen
On juni 15, 2022, 19:34:47 (SAST),
wasim:
-
Added resource highresolutionpopulationdensitymaps-zaf to South Africa: High Resolution Population Density Maps + Demographic Estimates
| f | 1 | { | f | 1 | { |
| 2 | "author": "Data for Good at Meta", | 2 | "author": "Data for Good at Meta", | ||
| 3 | "author_email": "", | 3 | "author_email": "", | ||
| 4 | "creator_user_id": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | 4 | "creator_user_id": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | ||
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| 13 | "title": "A_Sort_Later" | 13 | "title": "A_Sort_Later" | ||
| 14 | }, | 14 | }, | ||
| 15 | { | 15 | { | ||
| 16 | "description": "", | 16 | "description": "", | ||
| 17 | "display_name": "Population ", | 17 | "display_name": "Population ", | ||
| 18 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | 18 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | ||
| 19 | "image_display_url": "", | 19 | "image_display_url": "", | ||
| 20 | "name": "population", | 20 | "name": "population", | ||
| 21 | "title": "Population " | 21 | "title": "Population " | ||
| 22 | } | 22 | } | ||
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| 25 | "isopen": true, | 25 | "isopen": true, | ||
| 26 | "license_id": "cc-by", | 26 | "license_id": "cc-by", | ||
| 27 | "license_title": "Creative Commons Attribution", | 27 | "license_title": "Creative Commons Attribution", | ||
| 28 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 28 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| 29 | "maintainer": "Heiko Heilgendorff (OCL)", | 29 | "maintainer": "Heiko Heilgendorff (OCL)", | ||
| 30 | "maintainer_email": "[email protected]", | 30 | "maintainer_email": "[email protected]", | ||
| 31 | "metadata_created": "2021-06-09T14:30:20.667813", | 31 | "metadata_created": "2021-06-09T14:30:20.667813", | ||
| n | 32 | "metadata_modified": "2022-06-15T17:34:15.666326", | n | 32 | "metadata_modified": "2022-06-15T17:34:47.077277", |
| 33 | "name": | 33 | "name": | ||
| 34 | africa-high-resolution-population-density-maps-demographic-estimates", | 34 | africa-high-resolution-population-density-maps-demographic-estimates", | ||
| 35 | "notes": "VERSION 1.5. The world's most accurate population | 35 | "notes": "VERSION 1.5. The world's most accurate population | ||
| 36 | datasets. Seven maps/datasets for the distribution of various | 36 | datasets. Seven maps/datasets for the distribution of various | ||
| 37 | populations in South Africa: (1) Overall population density (2) Women | 37 | populations in South Africa: (1) Overall population density (2) Women | ||
| 38 | (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly | 38 | (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly | ||
| 39 | (ages 60+) (7) Women of reproductive age (ages 15-49).\r\n\r\n### | 39 | (ages 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 | 40 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
| 41 | machine learning techniques to identify buildings from commercially | 41 | machine learning techniques to identify buildings from commercially | ||
| 42 | available satellite images. This is then overlayed with general | 42 | available satellite images. This is then overlayed with general | ||
| 43 | population estimates based on publicly available census data and other | 43 | population estimates based on publicly available census data and other | ||
| 44 | population statistics at Columbia University. The resulting maps are | 44 | population statistics at Columbia University. The resulting maps are | ||
| 45 | the most detailed and actionable tools available for aid and research | 45 | the most detailed and actionable tools available for aid and research | ||
| 46 | organizations. For more information about the methodology used to | 46 | organizations. For more information about the methodology used to | ||
| 47 | create our high resolution population density maps and the demographic | 47 | create our high resolution population density maps and the demographic | ||
| 48 | distributions, click | 48 | distributions, click | ||
| 49 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | 49 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | ||
| 50 | information about how to use HDX to access these datasets, please | 50 | information about how to use HDX to access these datasets, please | ||
| 51 | visit: | 51 | visit: | ||
| 52 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 52 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
| 53 | to match the census population with the UN estimates are applied at | 53 | to match the census population with the UN estimates are applied at | ||
| 54 | the national level. The UN estimate for a given country (or | 54 | the national level. The UN estimate for a given country (or | ||
| 55 | state/territory) is divided by the total census estimate of population | 55 | state/territory) is divided by the total census estimate of population | ||
| 56 | for the given country. The resulting adjustment factor is multiplied | 56 | for the given country. The resulting adjustment factor is multiplied | ||
| 57 | by each administrative unit census value for the target year. This | 57 | by each administrative unit census value for the target year. This | ||
| 58 | preserves the relative population totals across administrative units | 58 | preserves the relative population totals across administrative units | ||
| 59 | while matching the UN total. More information can be found | 59 | while matching the UN total. More information can be found | ||
| 60 | ocs/census-information-for-high-resolution-population-density-maps/)", | 60 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
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| 63 | "organization": { | 63 | "organization": { | ||
| 64 | "approval_status": "approved", | 64 | "approval_status": "approved", | ||
| 65 | "created": "2022-06-15T09:44:22.871262", | 65 | "created": "2022-06-15T09:44:22.871262", | ||
| 66 | "description": "The Humanitarian Data Exchange (HDX) is an open | 66 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
| 67 | platform for sharing data across crises and organisations. Launched in | 67 | platform for sharing data across crises and organisations. Launched in | ||
| 68 | July 2014, the goal of HDX is to make humanitarian data easy to find | 68 | July 2014, the goal of HDX is to make humanitarian data easy to find | ||
| 69 | and use for analysis. Our growing collection of datasets has been | 69 | and use for analysis. Our growing collection of datasets has been | ||
| 70 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 70 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | ||
| 71 | managed by OCHA's Centre for Humanitarian Data, which is located in | 71 | managed by OCHA's Centre for Humanitarian Data, which is located in | ||
| 72 | The Hague. OCHA is part of the United Nations Secretariat and is | 72 | The Hague. OCHA is part of the United Nations Secretariat and is | ||
| 73 | responsible for bringing together humanitarian actors to ensure a | 73 | responsible for bringing together humanitarian actors to ensure a | ||
| 74 | coherent response to emergencies. The HDX team includes OCHA staff and | 74 | coherent response to emergencies. The HDX team includes OCHA staff and | ||
| 75 | a number of consultants who are based in North America, Europe and | 75 | a number of consultants who are based in North America, Europe and | ||
| 76 | Africa.", | 76 | Africa.", | ||
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| 473 | "state": "active", | 500 | "state": "active", | ||
| 474 | "vocabulary_id": null | 501 | "vocabulary_id": null | ||
| 475 | }, | 502 | }, | ||
| 476 | { | 503 | { | ||
| 477 | "display_name": "south africa", | 504 | "display_name": "south africa", | ||
| 478 | "id": "6c1d99aa-1164-481a-b7ef-c05974b84af7", | 505 | "id": "6c1d99aa-1164-481a-b7ef-c05974b84af7", | ||
| 479 | "name": "south africa", | 506 | "name": "south africa", | ||
| 480 | "state": "active", | 507 | "state": "active", | ||
| 481 | "vocabulary_id": null | 508 | "vocabulary_id": null | ||
| 482 | }, | 509 | }, | ||
| 483 | { | 510 | { | ||
| 484 | "display_name": "women", | 511 | "display_name": "women", | ||
| 485 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 512 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
| 486 | "name": "women", | 513 | "name": "women", | ||
| 487 | "state": "active", | 514 | "state": "active", | ||
| 488 | "vocabulary_id": null | 515 | "vocabulary_id": null | ||
| 489 | }, | 516 | }, | ||
| 490 | { | 517 | { | ||
| 491 | "display_name": "youth", | 518 | "display_name": "youth", | ||
| 492 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 519 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
| 493 | "name": "youth", | 520 | "name": "youth", | ||
| 494 | "state": "active", | 521 | "state": "active", | ||
| 495 | "vocabulary_id": null | 522 | "vocabulary_id": null | ||
| 496 | } | 523 | } | ||
| 497 | ], | 524 | ], | ||
| 498 | "title": "South Africa: High Resolution Population Density Maps + | 525 | "title": "South Africa: High Resolution Population Density Maps + | ||
| 499 | Demographic Estimates", | 526 | Demographic Estimates", | ||
| 500 | "type": "dataset", | 527 | "type": "dataset", | ||
| 501 | "url": | 528 | "url": | ||
| 502 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-zaf", | 529 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-zaf", | ||
| 503 | "version": "" | 530 | "version": "" | ||
| 504 | } | 531 | } |