Changes
On June 9, 2021, 16:33:45 (SAST),
wasim:
-
Added resource zaf_women_of_reproductive_age_15_49_csv.zip to South Africa: 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", | ||
| 5 | "extras": [], | 5 | "extras": [], | ||
| 6 | "groups": [], | 6 | "groups": [], | ||
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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": "2021-06-09T14:30:20.667813", | 14 | "metadata_created": "2021-06-09T14:30:20.667813", | ||
| n | 15 | "metadata_modified": "2021-06-09T14:33:29.707940", | n | 15 | "metadata_modified": "2021-06-09T14:33:44.957885", |
| 16 | "name": | 16 | "name": | ||
| 17 | africa-high-resolution-population-density-maps-demographic-estimates", | 17 | africa-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", | ||
| 50 | "id": "4607d385-0a0b-4fd9-a553-cc650210c096", | 50 | "id": "4607d385-0a0b-4fd9-a553-cc650210c096", | ||
| 51 | "image_url": | 51 | "image_url": | ||
| 52 | "2021-02-15-100907.924510Humanitarian-Emergency-Response-Africa.png", | 52 | "2021-02-15-100907.924510Humanitarian-Emergency-Response-Africa.png", | ||
| 53 | "is_organization": true, | 53 | "is_organization": true, | ||
| 54 | "name": "humanitarian-emergency-response-africa", | 54 | "name": "humanitarian-emergency-response-africa", | ||
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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" | ||
| 59 | }, | 59 | }, | ||
| 60 | "owner_org": "4607d385-0a0b-4fd9-a553-cc650210c096", | 60 | "owner_org": "4607d385-0a0b-4fd9-a553-cc650210c096", | ||
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| 308 | "id": "6e432f96-22f4-4aa9-9777-96774158a52b", | 331 | "id": "6e432f96-22f4-4aa9-9777-96774158a52b", | ||
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| 318 | "vocabulary_id": null | 341 | "vocabulary_id": null | ||
| 319 | }, | 342 | }, | ||
| 320 | { | 343 | { | ||
| 321 | "display_name": "men", | 344 | "display_name": "men", | ||
| 322 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | 345 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | ||
| 323 | "name": "men", | 346 | "name": "men", | ||
| 324 | "state": "active", | 347 | "state": "active", | ||
| 325 | "vocabulary_id": null | 348 | "vocabulary_id": null | ||
| 326 | }, | 349 | }, | ||
| 327 | { | 350 | { | ||
| 328 | "display_name": "population density", | 351 | "display_name": "population density", | ||
| 329 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 352 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
| 330 | "name": "population density", | 353 | "name": "population density", | ||
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| 332 | "vocabulary_id": null | 355 | "vocabulary_id": null | ||
| 333 | }, | 356 | }, | ||
| 334 | { | 357 | { | ||
| 335 | "display_name": "south africa", | 358 | "display_name": "south africa", | ||
| 336 | "id": "6c1d99aa-1164-481a-b7ef-c05974b84af7", | 359 | "id": "6c1d99aa-1164-481a-b7ef-c05974b84af7", | ||
| 337 | "name": "south africa", | 360 | "name": "south africa", | ||
| 338 | "state": "active", | 361 | "state": "active", | ||
| 339 | "vocabulary_id": null | 362 | "vocabulary_id": null | ||
| 340 | }, | 363 | }, | ||
| 341 | { | 364 | { | ||
| 342 | "display_name": "women", | 365 | "display_name": "women", | ||
| 343 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 366 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
| 344 | "name": "women", | 367 | "name": "women", | ||
| 345 | "state": "active", | 368 | "state": "active", | ||
| 346 | "vocabulary_id": null | 369 | "vocabulary_id": null | ||
| 347 | }, | 370 | }, | ||
| 348 | { | 371 | { | ||
| 349 | "display_name": "youth", | 372 | "display_name": "youth", | ||
| 350 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 373 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
| 351 | "name": "youth", | 374 | "name": "youth", | ||
| 352 | "state": "active", | 375 | "state": "active", | ||
| 353 | "vocabulary_id": null | 376 | "vocabulary_id": null | ||
| 354 | } | 377 | } | ||
| 355 | ], | 378 | ], | ||
| 356 | "title": "South Africa: High Resolution Population Density Maps + | 379 | "title": "South Africa: High Resolution Population Density Maps + | ||
| 357 | Demographic Estimates", | 380 | Demographic Estimates", | ||
| 358 | "type": "dataset", | 381 | "type": "dataset", | ||
| 359 | "url": | 382 | "url": | ||
| 360 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-zaf", | 383 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-zaf", | ||
| 361 | "version": "" | 384 | "version": "" | ||
| 362 | } | 385 | } |