Changes
On June 24, 2022, 13:18:27 (SAST),
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Added resource Angola: High Resolution Population Density Maps + Demographic Estimates to Angola: 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": "77d79e63-5fb4-4320-94e4-51e5e9b8031c", | 4 | "creator_user_id": "77d79e63-5fb4-4320-94e4-51e5e9b8031c", | ||
5 | "extras": [], | 5 | "extras": [], | ||
6 | "groups": [], | 6 | "groups": [], | ||
7 | "id": "e0efdb2c-552a-452b-86af-46657b75527d", | 7 | "id": "e0efdb2c-552a-452b-86af-46657b75527d", | ||
8 | "isopen": true, | 8 | "isopen": true, | ||
9 | "license_id": "cc-by", | 9 | "license_id": "cc-by", | ||
10 | "license_title": "Creative Commons Attribution", | 10 | "license_title": "Creative Commons Attribution", | ||
11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
12 | "maintainer": "Brian O'Leary", | 12 | "maintainer": "Brian O'Leary", | ||
13 | "maintainer_email": "[email protected]", | 13 | "maintainer_email": "[email protected]", | ||
14 | "metadata_created": "2022-06-24T11:17:20.049230", | 14 | "metadata_created": "2022-06-24T11:17:20.049230", | ||
n | 15 | "metadata_modified": "2022-06-24T11:17:20.049242", | n | 15 | "metadata_modified": "2022-06-24T11:18:27.495964", |
16 | "name": | 16 | "name": | ||
17 | angola-high-resolution-population-density-maps-demographic-estimates", | 17 | angola-high-resolution-population-density-maps-demographic-estimates", | ||
18 | "notes": "VERSION 1.5. The world's most accurate population | 18 | "notes": "VERSION 1.5. The world's most accurate population | ||
19 | datasets. Seven maps/datasets for the distribution of various | 19 | datasets. Seven maps/datasets for the distribution of various | ||
20 | populations in Angola: (1) Overall population density (2) Women (3) | 20 | populations in Angola: (1) Overall population density (2) Women (3) | ||
21 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | 21 | 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### | 22 | 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 | 23 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
24 | machine learning techniques to identify buildings from commercially | 24 | machine learning techniques to identify buildings from commercially | ||
25 | available satellite images. This is then overlayed with general | 25 | available satellite images. This is then overlayed with general | ||
26 | population estimates based on publicly available census data and other | 26 | population estimates based on publicly available census data and other | ||
27 | population statistics at Columbia University. The resulting maps are | 27 | population statistics at Columbia University. The resulting maps are | ||
28 | the most detailed and actionable tools available for aid and research | 28 | the most detailed and actionable tools available for aid and research | ||
29 | organizations. For more information about the methodology used to | 29 | organizations. For more information about the methodology used to | ||
30 | create our high resolution population density maps and the demographic | 30 | create our high resolution population density maps and the demographic | ||
31 | distributions, click | 31 | distributions, click | ||
32 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | 32 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | ||
33 | information about how to use HDX to access these datasets, please | 33 | information about how to use HDX to access these datasets, please | ||
34 | visit: | 34 | visit: | ||
35 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 35 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
36 | to match the census population with the UN estimates are applied at | 36 | to match the census population with the UN estimates are applied at | ||
37 | the national level. The UN estimate for a given country (or | 37 | the national level. The UN estimate for a given country (or | ||
38 | state/territory) is divided by the total census estimate of population | 38 | state/territory) is divided by the total census estimate of population | ||
39 | for the given country. The resulting adjustment factor is multiplied | 39 | for the given country. The resulting adjustment factor is multiplied | ||
40 | by each administrative unit census value for the target year. This | 40 | by each administrative unit census value for the target year. This | ||
41 | preserves the relative population totals across administrative units | 41 | preserves the relative population totals across administrative units | ||
42 | while matching the UN total. More information can be found | 42 | while matching the UN total. More information can be found | ||
43 | ocs/census-information-for-high-resolution-population-density-maps/)", | 43 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
n | 44 | "num_resources": 0, | n | 44 | "num_resources": 1, |
45 | "num_tags": 7, | 45 | "num_tags": 7, | ||
46 | "organization": { | 46 | "organization": { | ||
47 | "approval_status": "approved", | 47 | "approval_status": "approved", | ||
48 | "created": "2022-06-15T09:44:22.871262", | 48 | "created": "2022-06-15T09:44:22.871262", | ||
49 | "description": "The Humanitarian Data Exchange (HDX) is an open | 49 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
50 | platform for sharing data across crises and organisations. Launched in | 50 | platform for sharing data across crises and organisations. Launched in | ||
51 | July 2014, the goal of HDX is to make humanitarian data easy to find | 51 | July 2014, the goal of HDX is to make humanitarian data easy to find | ||
52 | and use for analysis. Our growing collection of datasets has been | 52 | and use for analysis. Our growing collection of datasets has been | ||
53 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 53 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | ||
54 | managed by OCHA's Centre for Humanitarian Data, which is located in | 54 | managed by OCHA's Centre for Humanitarian Data, which is located in | ||
55 | The Hague. OCHA is part of the United Nations Secretariat and is | 55 | The Hague. OCHA is part of the United Nations Secretariat and is | ||
56 | responsible for bringing together humanitarian actors to ensure a | 56 | responsible for bringing together humanitarian actors to ensure a | ||
57 | coherent response to emergencies. The HDX team includes OCHA staff and | 57 | coherent response to emergencies. The HDX team includes OCHA staff and | ||
58 | a number of consultants who are based in North America, Europe and | 58 | a number of consultants who are based in North America, Europe and | ||
59 | Africa.", | 59 | Africa.", | ||
60 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | 60 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||
61 | "image_url": | 61 | "image_url": | ||
62 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | 62 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | ||
63 | "is_organization": true, | 63 | "is_organization": true, | ||
64 | "name": "hdx-the-humanitarian-data-exchange", | 64 | "name": "hdx-the-humanitarian-data-exchange", | ||
65 | "revision_id": "e6c349dd-82c3-4176-a1c7-a4d89d8eae93", | 65 | "revision_id": "e6c349dd-82c3-4176-a1c7-a4d89d8eae93", | ||
66 | "state": "active", | 66 | "state": "active", | ||
67 | "title": "HDX - The Humanitarian Data Exchange", | 67 | "title": "HDX - The Humanitarian Data Exchange", | ||
68 | "type": "organization" | 68 | "type": "organization" | ||
69 | }, | 69 | }, | ||
70 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", | 70 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||
71 | "private": false, | 71 | "private": false, | ||
72 | "relationships_as_object": [], | 72 | "relationships_as_object": [], | ||
73 | "relationships_as_subject": [], | 73 | "relationships_as_subject": [], | ||
t | 74 | "resources": [], | t | 74 | "resources": [ |
75 | { | ||||
76 | "cache_last_updated": null, | ||||
77 | "cache_url": null, | ||||
78 | "created": "2022-06-24T11:18:27.521390", | ||||
79 | "datastore_active": false, | ||||
80 | "description": "The world's most accurate population datasets. | ||||
81 | Seven maps/datasets for the distribution of various populations in | ||||
82 | Angola: (1) Overall population density (2) Women (3) Men (4) Children | ||||
83 | (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of | ||||
84 | reproductive age (ages 15-49).", | ||||
85 | "format": "", | ||||
86 | "hash": "", | ||||
87 | "id": "159672e5-6c56-4d43-b378-3ccc5875d5f1", | ||||
88 | "last_modified": null, | ||||
89 | "mimetype": null, | ||||
90 | "mimetype_inner": null, | ||||
91 | "name": "Angola: High Resolution Population Density Maps + | ||||
92 | Demographic Estimates", | ||||
93 | "package_id": "e0efdb2c-552a-452b-86af-46657b75527d", | ||||
94 | "position": 0, | ||||
95 | "resource_type": null, | ||||
96 | "revision_id": "54730198-b5f9-42f8-895d-3f37091336ec", | ||||
97 | "size": null, | ||||
98 | "state": "active", | ||||
99 | "url": | ||||
100 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-ago", | ||||
101 | "url_type": null | ||||
102 | } | ||||
103 | ], | ||||
75 | "revision_id": "0d3244e6-6503-402c-b5ee-d33d35b680cc", | 104 | "revision_id": "0d3244e6-6503-402c-b5ee-d33d35b680cc", | ||
76 | "state": "draft", | 105 | "state": "draft", | ||
77 | "tags": [ | 106 | "tags": [ | ||
78 | { | 107 | { | ||
79 | "display_name": "Angola", | 108 | "display_name": "Angola", | ||
80 | "id": "2e0d491f-049b-43ae-b8e8-25d792fa6ae0", | 109 | "id": "2e0d491f-049b-43ae-b8e8-25d792fa6ae0", | ||
81 | "name": "Angola", | 110 | "name": "Angola", | ||
82 | "state": "active", | 111 | "state": "active", | ||
83 | "vocabulary_id": null | 112 | "vocabulary_id": null | ||
84 | }, | 113 | }, | ||
85 | { | 114 | { | ||
86 | "display_name": "children", | 115 | "display_name": "children", | ||
87 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 116 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
88 | "name": "children", | 117 | "name": "children", | ||
89 | "state": "active", | 118 | "state": "active", | ||
90 | "vocabulary_id": null | 119 | "vocabulary_id": null | ||
91 | }, | 120 | }, | ||
92 | { | 121 | { | ||
93 | "display_name": "elderly", | 122 | "display_name": "elderly", | ||
94 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | 123 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | ||
95 | "name": "elderly", | 124 | "name": "elderly", | ||
96 | "state": "active", | 125 | "state": "active", | ||
97 | "vocabulary_id": null | 126 | "vocabulary_id": null | ||
98 | }, | 127 | }, | ||
99 | { | 128 | { | ||
100 | "display_name": "men", | 129 | "display_name": "men", | ||
101 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | 130 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | ||
102 | "name": "men", | 131 | "name": "men", | ||
103 | "state": "active", | 132 | "state": "active", | ||
104 | "vocabulary_id": null | 133 | "vocabulary_id": null | ||
105 | }, | 134 | }, | ||
106 | { | 135 | { | ||
107 | "display_name": "population density", | 136 | "display_name": "population density", | ||
108 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 137 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
109 | "name": "population density", | 138 | "name": "population density", | ||
110 | "state": "active", | 139 | "state": "active", | ||
111 | "vocabulary_id": null | 140 | "vocabulary_id": null | ||
112 | }, | 141 | }, | ||
113 | { | 142 | { | ||
114 | "display_name": "women", | 143 | "display_name": "women", | ||
115 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 144 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
116 | "name": "women", | 145 | "name": "women", | ||
117 | "state": "active", | 146 | "state": "active", | ||
118 | "vocabulary_id": null | 147 | "vocabulary_id": null | ||
119 | }, | 148 | }, | ||
120 | { | 149 | { | ||
121 | "display_name": "youth", | 150 | "display_name": "youth", | ||
122 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 151 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
123 | "name": "youth", | 152 | "name": "youth", | ||
124 | "state": "active", | 153 | "state": "active", | ||
125 | "vocabulary_id": null | 154 | "vocabulary_id": null | ||
126 | } | 155 | } | ||
127 | ], | 156 | ], | ||
128 | "title": "Angola: High Resolution Population Density Maps + | 157 | "title": "Angola: High Resolution Population Density Maps + | ||
129 | Demographic Estimates", | 158 | Demographic Estimates", | ||
130 | "type": "dataset", | 159 | "type": "dataset", | ||
131 | "url": | 160 | "url": | ||
132 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-ago", | 161 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-ago", | ||
133 | "version": "" | 162 | "version": "" | ||
134 | } | 163 | } |