Changes
On June 15, 2022, 13:25:00 (SAST),
wasim:
-
Moved Nigeria: High Resolution Population Density Maps + Demographic Estimates from organization Humanitarian Emergency Response Africa to organization HDX - The Humanitarian Data Exchange
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Set maintainer of Nigeria: High Resolution Population Density Maps + Demographic Estimates to Heiko Heilgendorff (OCL) (previously Facebook Data For Good)
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Set maintainer email of Nigeria: High Resolution Population Density Maps + Demographic Estimates to [email protected]
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Set author of Nigeria: High Resolution Population Density Maps + Demographic Estimates to Data for Good at Meta (previously Facebook Data for Good)
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| n | 2 | "author": "Facebook Data for Good", | n | 2 | "author": "Data for Good at Meta", |
| 3 | "author_email": "", | 3 | "author_email": "", | ||
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| 5 | "extras": [], | 5 | "extras": [], | ||
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| 14 | }, | ||||
| 15 | { | ||||
| 16 | "description": "", | ||||
| 17 | "display_name": "Population ", | ||||
| 18 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | ||||
| 19 | "image_display_url": "", | ||||
| 20 | "name": "population", | ||||
| 21 | "title": "Population " | ||||
| 22 | } | ||||
| 23 | ], | ||||
| 7 | "id": "fe17bb29-52c2-4029-af8e-58e4f362f956", | 24 | "id": "fe17bb29-52c2-4029-af8e-58e4f362f956", | ||
| 8 | "isopen": true, | 25 | "isopen": true, | ||
| 9 | "license_id": "cc-by", | 26 | "license_id": "cc-by", | ||
| 10 | "license_title": "Creative Commons Attribution", | 27 | "license_title": "Creative Commons Attribution", | ||
| 11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 28 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| n | 12 | "maintainer": "Facebook Data For Good", | n | 29 | "maintainer": "Heiko Heilgendorff (OCL)", |
| 13 | "maintainer_email": "", | 30 | "maintainer_email": "[email protected]", | ||
| 14 | "metadata_created": "2021-06-03T14:01:21.364366", | 31 | "metadata_created": "2021-06-03T14:01:21.364366", | ||
| n | 15 | "metadata_modified": "2021-06-15T08:28:47.146851", | n | 32 | "metadata_modified": "2022-06-15T11:25:00.728706", |
| 16 | "name": | 33 | "name": | ||
| 17 | igeria-high-resolution-population-density-maps-demographic-estimates", | 34 | igeria-high-resolution-population-density-maps-demographic-estimates", | ||
| 18 | "notes": "VERSION 1.5. The world's most accurate population | 35 | "notes": "VERSION 1.5. The world's most accurate population | ||
| 19 | datasets. Seven maps/datasets for the distribution of various | 36 | datasets. Seven maps/datasets for the distribution of various | ||
| 20 | populations in Nigeria: (1) Overall population density (2) Women (3) | 37 | populations in Nigeria: (1) Overall population density (2) Women (3) | ||
| 21 | 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 | ||
| 22 | 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### | ||
| 23 | Methodology\r\n\r\nThese high-resolution maps are created using | 40 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
| 24 | machine learning techniques to identify buildings from commercially | 41 | machine learning techniques to identify buildings from commercially | ||
| 25 | available satellite images. This is then overlayed with general | 42 | available satellite images. This is then overlayed with general | ||
| 26 | population estimates based on publicly available census data and other | 43 | population estimates based on publicly available census data and other | ||
| 27 | population statistics at Columbia University. The resulting maps are | 44 | population statistics at Columbia University. The resulting maps are | ||
| 28 | the most detailed and actionable tools available for aid and research | 45 | the most detailed and actionable tools available for aid and research | ||
| 29 | organizations. For more information about the methodology used to | 46 | organizations. For more information about the methodology used to | ||
| 30 | create our high resolution population density maps and the demographic | 47 | create our high resolution population density maps and the demographic | ||
| 31 | distributions, click | 48 | distributions, click | ||
| 32 | h-resolution-population-density-maps-demographic-estimates/\r\n\r\nFor | 49 | h-resolution-population-density-maps-demographic-estimates/\r\n\r\nFor | ||
| 33 | information about how to use HDX to access these datasets, please | 50 | information about how to use HDX to access these datasets, please | ||
| 34 | visit: | 51 | visit: | ||
| 35 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 52 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
| 36 | 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 | ||
| 37 | the national level. The UN estimate for a given country (or | 54 | the national level. The UN estimate for a given country (or | ||
| 38 | state/territory) is divided by the total census estimate of population | 55 | state/territory) is divided by the total census estimate of population | ||
| 39 | for the given country. The resulting adjustment factor is multiplied | 56 | for the given country. The resulting adjustment factor is multiplied | ||
| 40 | by each administrative unit census value for the target year. This | 57 | by each administrative unit census value for the target year. This | ||
| 41 | preserves the relative population totals across administrative units | 58 | preserves the relative population totals across administrative units | ||
| 42 | while matching the UN total. More information can be found | 59 | while matching the UN total. More information can be found | ||
| 43 | ocs/census-information-for-high-resolution-population-density-maps/)", | 60 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
| 44 | "num_resources": 15, | 61 | "num_resources": 15, | ||
| 45 | "num_tags": 7, | 62 | "num_tags": 7, | ||
| 46 | "organization": { | 63 | "organization": { | ||
| 47 | "approval_status": "approved", | 64 | "approval_status": "approved", | ||
| n | 48 | "created": "2021-02-15T10:09:07.942828", | n | 65 | "created": "2022-06-15T09:44:22.871262", |
| 49 | "description": "Humanitarian Emergency Response Africa Datasets", | 66 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
| 50 | "id": "4607d385-0a0b-4fd9-a553-cc650210c096", | 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 | ||||
| 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 | ||||
| 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 | ||||
| 73 | responsible for bringing together humanitarian actors to ensure a | ||||
| 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 | ||||
| 76 | Africa.", | ||||
| 77 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||||
| 51 | "image_url": | 78 | "image_url": | ||
| n | 52 | "2021-02-15-100907.924510Humanitarian-Emergency-Response-Africa.png", | n | 79 | "https://data.humdata.org/images/homepage/logo-hdx.svg", |
| 53 | "is_organization": true, | 80 | "is_organization": true, | ||
| n | 54 | "name": "humanitarian-emergency-response-africa", | n | 81 | "name": "hdx-the-humanitarian-data-exchange", |
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| 56 | "state": "active", | 83 | "state": "active", | ||
| n | 57 | "title": "Humanitarian Emergency Response Africa", | n | 84 | "title": "HDX - The Humanitarian Data Exchange", |
| 58 | "type": "organization" | 85 | "type": "organization" | ||
| 59 | }, | 86 | }, | ||
| n | 60 | "owner_org": "4607d385-0a0b-4fd9-a553-cc650210c096", | n | 87 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", |
| 61 | "private": false, | 88 | "private": false, | ||
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