Változások
On Június 4, 2021, 13:22:20 (SAST),
-
Added resource population_sen_2018-10-01.csv.zip to Senegal: High Resolution Population Density Maps + Demographic Estimates
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2 | "author": "Facebook Data for Good", | 2 | "author": "Facebook Data for Good", | ||
3 | "author_email": "", | 3 | "author_email": "", | ||
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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": "", | 12 | "maintainer": "", | ||
13 | "maintainer_email": "", | 13 | "maintainer_email": "", | ||
14 | "metadata_created": "2021-06-04T11:21:16.687039", | 14 | "metadata_created": "2021-06-04T11:21:16.687039", | ||
n | 15 | "metadata_modified": "2021-06-04T11:22:03.927781", | n | 15 | "metadata_modified": "2021-06-04T11:22:19.926916", |
16 | "name": | 16 | "name": | ||
17 | enegal-high-resolution-population-density-maps-demographic-estimates", | 17 | enegal-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", | ||
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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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90 | "state": "draft", | 113 | "state": "draft", | ||
91 | "tags": [ | 114 | "tags": [ | ||
92 | { | 115 | { | ||
93 | "display_name": "children", | 116 | "display_name": "children", | ||
94 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 117 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
95 | "name": "children", | 118 | "name": "children", | ||
96 | "state": "active", | 119 | "state": "active", | ||
97 | "vocabulary_id": null | 120 | "vocabulary_id": null | ||
98 | }, | 121 | }, | ||
99 | { | 122 | { | ||
100 | "display_name": "elderly", | 123 | "display_name": "elderly", | ||
101 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | 124 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | ||
102 | "name": "elderly", | 125 | "name": "elderly", | ||
103 | "state": "active", | 126 | "state": "active", | ||
104 | "vocabulary_id": null | 127 | "vocabulary_id": null | ||
105 | }, | 128 | }, | ||
106 | { | 129 | { | ||
107 | "display_name": "population density", | 130 | "display_name": "population density", | ||
108 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 131 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
109 | "name": "population density", | 132 | "name": "population density", | ||
110 | "state": "active", | 133 | "state": "active", | ||
111 | "vocabulary_id": null | 134 | "vocabulary_id": null | ||
112 | }, | 135 | }, | ||
113 | { | 136 | { | ||
114 | "display_name": "senegal", | 137 | "display_name": "senegal", | ||
115 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | 138 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | ||
116 | "name": "senegal", | 139 | "name": "senegal", | ||
117 | "state": "active", | 140 | "state": "active", | ||
118 | "vocabulary_id": null | 141 | "vocabulary_id": null | ||
119 | }, | 142 | }, | ||
120 | { | 143 | { | ||
121 | "display_name": "women", | 144 | "display_name": "women", | ||
122 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 145 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
123 | "name": "women", | 146 | "name": "women", | ||
124 | "state": "active", | 147 | "state": "active", | ||
125 | "vocabulary_id": null | 148 | "vocabulary_id": null | ||
126 | }, | 149 | }, | ||
127 | { | 150 | { | ||
128 | "display_name": "women of reproductive age", | 151 | "display_name": "women of reproductive age", | ||
129 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | 152 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | ||
130 | "name": "women of reproductive age", | 153 | "name": "women of reproductive age", | ||
131 | "state": "active", | 154 | "state": "active", | ||
132 | "vocabulary_id": null | 155 | "vocabulary_id": null | ||
133 | }, | 156 | }, | ||
134 | { | 157 | { | ||
135 | "display_name": "youth", | 158 | "display_name": "youth", | ||
136 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 159 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
137 | "name": "youth", | 160 | "name": "youth", | ||
138 | "state": "active", | 161 | "state": "active", | ||
139 | "vocabulary_id": null | 162 | "vocabulary_id": null | ||
140 | } | 163 | } | ||
141 | ], | 164 | ], | ||
142 | "title": "Senegal: High Resolution Population Density Maps + | 165 | "title": "Senegal: High Resolution Population Density Maps + | ||
143 | Demographic Estimates", | 166 | Demographic Estimates", | ||
144 | "type": "dataset", | 167 | "type": "dataset", | ||
145 | "url": "Facebook Data for Good", | 168 | "url": "Facebook Data for Good", | ||
146 | "version": "" | 169 | "version": "" | ||
147 | } | 170 | } |