Zmiany
On June 15, 2022, 19:26:58 (SAST),
wasim:
-
Updated description of resource Ghana: high resolution population density maps in Ghana: High Resolution Population Density Maps + Demographic Estimates to
VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nigeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
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| 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", | ||
| 5 | "extras": [], | 5 | "extras": [], | ||
| 6 | "groups": [ | 6 | "groups": [ | ||
| 7 | { | 7 | { | ||
| 8 | "description": "", | 8 | "description": "", | ||
| 9 | "display_name": "A_Sort_Later", | 9 | "display_name": "A_Sort_Later", | ||
| 10 | "id": "3e71b430-62d6-4b65-8157-527fd8e9c52f", | 10 | "id": "3e71b430-62d6-4b65-8157-527fd8e9c52f", | ||
| 11 | "image_display_url": "", | 11 | "image_display_url": "", | ||
| 12 | "name": "not-useful", | 12 | "name": "not-useful", | ||
| 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 | } | ||
| 23 | ], | 23 | ], | ||
| 24 | "id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | 24 | "id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | ||
| 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": "2021-06-09T14:01:13.877901", | 31 | "metadata_created": "2021-06-09T14:01:13.877901", | ||
| n | 32 | "metadata_modified": "2022-06-15T17:26:41.529267", | n | 32 | "metadata_modified": "2022-06-15T17:26:58.743430", |
| 33 | "name": | 33 | "name": | ||
| 34 | "ghana-high-resolution-population-density-maps-demographic-estimates", | 34 | "ghana-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 Nigeria: (1) Overall population density (2) Women (3) | 37 | populations in Nigeria: (1) Overall population density (2) Women (3) | ||
| 38 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | 38 | 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### | 39 | 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 | h-resolution-population-density-maps-demographic-estimates/\r\n\r\nFor | 49 | h-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/)", | ||
| 61 | "num_resources": 14, | 61 | "num_resources": 14, | ||
| 62 | "num_tags": 10, | 62 | "num_tags": 10, | ||
| 63 | "organization": { | 63 | "organization": { | ||
| 64 | "approval_status": "approved", | 64 | "approval_status": "approved", | ||
| 65 | "created": "2021-02-15T10:09:07.942828", | 65 | "created": "2021-02-15T10:09:07.942828", | ||
| 66 | "description": "Humanitarian Emergency Response Africa Datasets", | 66 | "description": "Humanitarian Emergency Response Africa Datasets", | ||
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| 68 | "image_url": | 68 | "image_url": | ||
| 69 | "2021-02-15-100907.924510Humanitarian-Emergency-Response-Africa.png", | 69 | "2021-02-15-100907.924510Humanitarian-Emergency-Response-Africa.png", | ||
| 70 | "is_organization": true, | 70 | "is_organization": true, | ||
| 71 | "name": "humanitarian-emergency-response-africa", | 71 | "name": "humanitarian-emergency-response-africa", | ||
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| 73 | "state": "active", | 73 | "state": "active", | ||
| 74 | "title": "Humanitarian Emergency Response Africa", | 74 | "title": "Humanitarian Emergency Response Africa", | ||
| 75 | "type": "organization" | 75 | "type": "organization" | ||
| 76 | }, | 76 | }, | ||
| 77 | "owner_org": "4607d385-0a0b-4fd9-a553-cc650210c096", | 77 | "owner_org": "4607d385-0a0b-4fd9-a553-cc650210c096", | ||
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