Changes
On June 3, 2021, 16:03:35 (SAST), wasim:
-
Added resource nga_children_under_five_2020_csv.zip to Nigeria: High Resolution Population Density Maps + Demographic Estimates
f | 1 | { | f | 1 | { |
2 | "author": "Facebook Data for Good", | 2 | "author": "Facebook Data for Good", | ||
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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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": "Facebook Data For Good", | 12 | "maintainer": "Facebook Data For Good", | ||
13 | "maintainer_email": "", | 13 | "maintainer_email": "", | ||
14 | "metadata_created": "2021-06-03T14:01:21.364366", | 14 | "metadata_created": "2021-06-03T14:01:21.364366", | ||
n | 15 | "metadata_modified": "2021-06-03T14:03:10.605937", | n | 15 | "metadata_modified": "2021-06-03T14:03:35.694217", |
16 | "name": | 16 | "name": | ||
17 | igeria-high-resolution-population-density-maps-demographic-estimates", | 17 | igeria-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 Nigeria: (1) Overall population density (2) Women (3) | 20 | 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 | 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 | h-resolution-population-density-maps-demographic-estimates/\r\n\r\nFor | 32 | h-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/)", | ||
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46 | "organization": { | 46 | "organization": { | ||
47 | "approval_status": "approved", | 47 | "approval_status": "approved", | ||
48 | "created": "2021-02-15T10:09:07.942828", | 48 | "created": "2021-02-15T10:09:07.942828", | ||
49 | "description": "Humanitarian Emergency Response Africa Datasets", | 49 | "description": "Humanitarian Emergency Response Africa Datasets", | ||
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51 | "image_url": | 51 | "image_url": | ||
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56 | "state": "active", | 56 | "state": "active", | ||
57 | "title": "Humanitarian Emergency Response Africa", | 57 | "title": "Humanitarian Emergency Response Africa", | ||
58 | "type": "organization" | 58 | "type": "organization" | ||
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113 | "state": "draft", | 136 | "state": "draft", | ||
114 | "tags": [ | 137 | "tags": [ | ||
115 | { | 138 | { | ||
116 | "display_name": "children", | 139 | "display_name": "children", | ||
117 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 140 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
118 | "name": "children", | 141 | "name": "children", | ||
119 | "state": "active", | 142 | "state": "active", | ||
120 | "vocabulary_id": null | 143 | "vocabulary_id": null | ||
121 | }, | 144 | }, | ||
122 | { | 145 | { | ||
123 | "display_name": "gender", | 146 | "display_name": "gender", | ||
124 | "id": "9923e71e-0c99-4abb-a0fa-5e7ccbc74956", | 147 | "id": "9923e71e-0c99-4abb-a0fa-5e7ccbc74956", | ||
125 | "name": "gender", | 148 | "name": "gender", | ||
126 | "state": "active", | 149 | "state": "active", | ||
127 | "vocabulary_id": null | 150 | "vocabulary_id": null | ||
128 | }, | 151 | }, | ||
129 | { | 152 | { | ||
130 | "display_name": "nigeria", | 153 | "display_name": "nigeria", | ||
131 | "id": "86671c58-04e8-4323-8904-b2b506740271", | 154 | "id": "86671c58-04e8-4323-8904-b2b506740271", | ||
132 | "name": "nigeria", | 155 | "name": "nigeria", | ||
133 | "state": "active", | 156 | "state": "active", | ||
134 | "vocabulary_id": null | 157 | "vocabulary_id": null | ||
135 | }, | 158 | }, | ||
136 | { | 159 | { | ||
137 | "display_name": "population", | 160 | "display_name": "population", | ||
138 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | 161 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | ||
139 | "name": "population", | 162 | "name": "population", | ||
140 | "state": "active", | 163 | "state": "active", | ||
141 | "vocabulary_id": null | 164 | "vocabulary_id": null | ||
142 | }, | 165 | }, | ||
143 | { | 166 | { | ||
144 | "display_name": "population density", | 167 | "display_name": "population density", | ||
145 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 168 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
146 | "name": "population density", | 169 | "name": "population density", | ||
147 | "state": "active", | 170 | "state": "active", | ||
148 | "vocabulary_id": null | 171 | "vocabulary_id": null | ||
149 | }, | 172 | }, | ||
150 | { | 173 | { | ||
151 | "display_name": "women", | 174 | "display_name": "women", | ||
152 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 175 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
153 | "name": "women", | 176 | "name": "women", | ||
154 | "state": "active", | 177 | "state": "active", | ||
155 | "vocabulary_id": null | 178 | "vocabulary_id": null | ||
156 | }, | 179 | }, | ||
157 | { | 180 | { | ||
158 | "display_name": "youth", | 181 | "display_name": "youth", | ||
159 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 182 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
160 | "name": "youth", | 183 | "name": "youth", | ||
161 | "state": "active", | 184 | "state": "active", | ||
162 | "vocabulary_id": null | 185 | "vocabulary_id": null | ||
163 | } | 186 | } | ||
164 | ], | 187 | ], | ||
165 | "title": "Nigeria: High Resolution Population Density Maps + | 188 | "title": "Nigeria: High Resolution Population Density Maps + | ||
166 | Demographic Estimates", | 189 | Demographic Estimates", | ||
167 | "type": "dataset", | 190 | "type": "dataset", | ||
168 | "url": | 191 | "url": | ||
169 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | 192 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | ||
170 | "version": "" | 193 | "version": "" | ||
171 | } | 194 | } |