Modifications
On Juin 14, 2023, 11:51:02 (SAST),
-
Deleted resource gha_men_2020_geotiff.zip from Ghana: 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": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | 4 | "creator_user_id": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | ||
5 | "extras": [], | 5 | "extras": [], | ||
6 | "groups": [ | 6 | "groups": [ | ||
7 | { | 7 | { | ||
8 | "description": "The Humanitarian Data Exchange (HDX) is an open | 8 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
9 | platform for sharing data across crises and organisations. Launched in | 9 | platform for sharing data across crises and organisations. Launched in | ||
10 | July 2014, the goal of HDX is to make humanitarian data easy to find | 10 | July 2014, the goal of HDX is to make humanitarian data easy to find | ||
11 | and use for analysis. Our growing collection of datasets has been | 11 | and use for analysis. Our growing collection of datasets has been | ||
12 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 12 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | ||
13 | managed by OCHA's Centre for Humanitarian Data, which is located in | 13 | managed by OCHA's Centre for Humanitarian Data, which is located in | ||
14 | The Hague. OCHA is part of the United Nations Secretariat and is | 14 | The Hague. OCHA is part of the United Nations Secretariat and is | ||
15 | responsible for bringing together humanitarian actors to ensure a | 15 | responsible for bringing together humanitarian actors to ensure a | ||
16 | coherent response to emergencies. The HDX team includes OCHA staff and | 16 | coherent response to emergencies. The HDX team includes OCHA staff and | ||
17 | a number of consultants who are based in North America, Europe and | 17 | a number of consultants who are based in North America, Europe and | ||
18 | Africa.", | 18 | Africa.", | ||
19 | "display_name": "HDX: Humanitarian Data Exchange", | 19 | "display_name": "HDX: Humanitarian Data Exchange", | ||
20 | "id": "15791998-b8b5-41fa-841f-0393addadcbf", | 20 | "id": "15791998-b8b5-41fa-841f-0393addadcbf", | ||
21 | "image_display_url": | 21 | "image_display_url": | ||
22 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | 22 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | ||
23 | "name": "hdx-humanitarian-data-exchange", | 23 | "name": "hdx-humanitarian-data-exchange", | ||
24 | "title": "HDX: Humanitarian Data Exchange" | 24 | "title": "HDX: Humanitarian Data Exchange" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "description": "", | 27 | "description": "", | ||
28 | "display_name": "Population ", | 28 | "display_name": "Population ", | ||
29 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | 29 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | ||
30 | "image_display_url": "", | 30 | "image_display_url": "", | ||
31 | "name": "population", | 31 | "name": "population", | ||
32 | "title": "Population " | 32 | "title": "Population " | ||
33 | } | 33 | } | ||
34 | ], | 34 | ], | ||
35 | "id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | 35 | "id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | ||
36 | "isopen": true, | 36 | "isopen": true, | ||
37 | "license_id": "cc-by", | 37 | "license_id": "cc-by", | ||
38 | "license_title": "Creative Commons Attribution", | 38 | "license_title": "Creative Commons Attribution", | ||
39 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 39 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
40 | "maintainer": "Heiko Heilgendorff (OCL)", | 40 | "maintainer": "Heiko Heilgendorff (OCL)", | ||
41 | "maintainer_email": "[email protected]", | 41 | "maintainer_email": "[email protected]", | ||
42 | "metadata_created": "2021-06-09T14:01:13.877901", | 42 | "metadata_created": "2021-06-09T14:01:13.877901", | ||
n | 43 | "metadata_modified": "2023-06-14T09:50:49.884894", | n | 43 | "metadata_modified": "2023-06-14T09:51:02.309618", |
44 | "name": | 44 | "name": | ||
45 | "ghana-high-resolution-population-density-maps-demographic-estimates", | 45 | "ghana-high-resolution-population-density-maps-demographic-estimates", | ||
46 | "notes": "VERSION 1.5. The world's most accurate population | 46 | "notes": "VERSION 1.5. The world's most accurate population | ||
47 | datasets. Seven maps/datasets for the distribution of various | 47 | datasets. Seven maps/datasets for the distribution of various | ||
48 | populations in Ghana: (1) Overall population density (2) Women (3) Men | 48 | populations in Ghana: (1) Overall population density (2) Women (3) Men | ||
49 | (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) | 49 | (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) | ||
50 | (7) Women of reproductive age (ages 15-49).\r\n\r\n### | 50 | (7) Women of reproductive age (ages 15-49).\r\n\r\n### | ||
51 | Methodology\r\n\r\nThese high-resolution maps are created using | 51 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
52 | machine learning techniques to identify buildings from commercially | 52 | machine learning techniques to identify buildings from commercially | ||
53 | available satellite images. This is then overlayed with general | 53 | available satellite images. This is then overlayed with general | ||
54 | population estimates based on publicly available census data and other | 54 | population estimates based on publicly available census data and other | ||
55 | population statistics at Columbia University. The resulting maps are | 55 | population statistics at Columbia University. The resulting maps are | ||
56 | the most detailed and actionable tools available for aid and research | 56 | the most detailed and actionable tools available for aid and research | ||
57 | organizations. For more information about the methodology used to | 57 | organizations. For more information about the methodology used to | ||
58 | create our high resolution population density maps and the demographic | 58 | create our high resolution population density maps and the demographic | ||
59 | distributions, click | 59 | distributions, click | ||
60 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | 60 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | ||
61 | information about how to use HDX to access these datasets, please | 61 | information about how to use HDX to access these datasets, please | ||
62 | visit: | 62 | visit: | ||
63 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 63 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
64 | to match the census population with the UN estimates are applied at | 64 | to match the census population with the UN estimates are applied at | ||
65 | the national level. The UN estimate for a given country (or | 65 | the national level. The UN estimate for a given country (or | ||
66 | state/territory) is divided by the total census estimate of population | 66 | state/territory) is divided by the total census estimate of population | ||
67 | for the given country. The resulting adjustment factor is multiplied | 67 | for the given country. The resulting adjustment factor is multiplied | ||
68 | by each administrative unit census value for the target year. This | 68 | by each administrative unit census value for the target year. This | ||
69 | preserves the relative population totals across administrative units | 69 | preserves the relative population totals across administrative units | ||
70 | while matching the UN total. More information can be found | 70 | while matching the UN total. More information can be found | ||
71 | ocs/census-information-for-high-resolution-population-density-maps/)", | 71 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
n | 72 | "num_resources": 7, | n | 72 | "num_resources": 6, |
73 | "num_tags": 10, | 73 | "num_tags": 10, | ||
74 | "organization": { | 74 | "organization": { | ||
75 | "approval_status": "approved", | 75 | "approval_status": "approved", | ||
76 | "created": "2022-07-04T08:06:45.420882", | 76 | "created": "2022-07-04T08:06:45.420882", | ||
77 | "description": "We work to build inclusion and participatory | 77 | "description": "We work to build inclusion and participatory | ||
78 | democracy in cities and urban spaces through empowering citizens, | 78 | democracy in cities and urban spaces through empowering citizens, | ||
79 | building trust and accountability in civic space, and capacitating | 79 | building trust and accountability in civic space, and capacitating | ||
80 | government. You can find our website | 80 | government. You can find our website | ||
81 | [here](https://opencitieslab.org/).", | 81 | [here](https://opencitieslab.org/).", | ||
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89 | "title": "Open Cities Lab", | 89 | "title": "Open Cities Lab", | ||
90 | "type": "organization" | 90 | "type": "organization" | ||
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243 | various populations in Nigeria: (1) Overall population density (2) | 220 | various populations in Nigeria: (1) Overall population density (2) | ||
244 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | 221 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | ||
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248 | "id": "61a01f7e-33ac-453e-bd71-691754879824", | 225 | "id": "61a01f7e-33ac-453e-bd71-691754879824", | ||
249 | "last_modified": null, | 226 | "last_modified": null, | ||
250 | "mimetype": null, | 227 | "mimetype": null, | ||
251 | "mimetype_inner": null, | 228 | "mimetype_inner": null, | ||
252 | "name": "Ghana: high resolution population density maps", | 229 | "name": "Ghana: high resolution population density maps", | ||
253 | "package_id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | 230 | "package_id": "2cf5970c-47cf-435c-88b6-f938d67041e0", | ||
n | 254 | "position": 6, | n | 231 | "position": 5, |
255 | "resource_type": null, | 232 | "resource_type": null, | ||
t | 256 | "revision_id": "075e98b4-53c5-46a1-910b-cf0e84b23f69", | t | 233 | "revision_id": "c1c0cea3-1bf7-4145-9805-83302ba568a4", |
257 | "size": null, | 234 | "size": null, | ||
258 | "state": "active", | 235 | "state": "active", | ||
259 | "url": | 236 | "url": | ||
260 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-gha", | 237 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-gha", | ||
261 | "url_type": null | 238 | "url_type": null | ||
262 | } | 239 | } | ||
263 | ], | 240 | ], | ||
264 | "revision_id": "4d9d9aee-4624-4b51-baf1-469ce08c95eb", | 241 | "revision_id": "4d9d9aee-4624-4b51-baf1-469ce08c95eb", | ||
265 | "state": "active", | 242 | "state": "active", | ||
266 | "tags": [ | 243 | "tags": [ | ||
267 | { | 244 | { | ||
268 | "display_name": "children", | 245 | "display_name": "children", | ||
269 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 246 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
270 | "name": "children", | 247 | "name": "children", | ||
271 | "state": "active", | 248 | "state": "active", | ||
272 | "vocabulary_id": null | 249 | "vocabulary_id": null | ||
273 | }, | 250 | }, | ||
274 | { | 251 | { | ||
275 | "display_name": "demographic", | 252 | "display_name": "demographic", | ||
276 | "id": "b38c78bf-f4fb-459c-b8ff-9c41e3f4f9ae", | 253 | "id": "b38c78bf-f4fb-459c-b8ff-9c41e3f4f9ae", | ||
277 | "name": "demographic", | 254 | "name": "demographic", | ||
278 | "state": "active", | 255 | "state": "active", | ||
279 | "vocabulary_id": null | 256 | "vocabulary_id": null | ||
280 | }, | 257 | }, | ||
281 | { | 258 | { | ||
282 | "display_name": "elderly", | 259 | "display_name": "elderly", | ||
283 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | 260 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | ||
284 | "name": "elderly", | 261 | "name": "elderly", | ||
285 | "state": "active", | 262 | "state": "active", | ||
286 | "vocabulary_id": null | 263 | "vocabulary_id": null | ||
287 | }, | 264 | }, | ||
288 | { | 265 | { | ||
289 | "display_name": "geodata", | 266 | "display_name": "geodata", | ||
290 | "id": "7801f2cc-853c-4190-b21a-641a82b8d1f1", | 267 | "id": "7801f2cc-853c-4190-b21a-641a82b8d1f1", | ||
291 | "name": "geodata", | 268 | "name": "geodata", | ||
292 | "state": "active", | 269 | "state": "active", | ||
293 | "vocabulary_id": null | 270 | "vocabulary_id": null | ||
294 | }, | 271 | }, | ||
295 | { | 272 | { | ||
296 | "display_name": "ghana", | 273 | "display_name": "ghana", | ||
297 | "id": "47eec602-5e10-4083-b862-ac1f0b74aaf4", | 274 | "id": "47eec602-5e10-4083-b862-ac1f0b74aaf4", | ||
298 | "name": "ghana", | 275 | "name": "ghana", | ||
299 | "state": "active", | 276 | "state": "active", | ||
300 | "vocabulary_id": null | 277 | "vocabulary_id": null | ||
301 | }, | 278 | }, | ||
302 | { | 279 | { | ||
303 | "display_name": "men", | 280 | "display_name": "men", | ||
304 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | 281 | "id": "887bf1dd-dcf9-42ab-9e75-7ee55de689a2", | ||
305 | "name": "men", | 282 | "name": "men", | ||
306 | "state": "active", | 283 | "state": "active", | ||
307 | "vocabulary_id": null | 284 | "vocabulary_id": null | ||
308 | }, | 285 | }, | ||
309 | { | 286 | { | ||
310 | "display_name": "population density", | 287 | "display_name": "population density", | ||
311 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 288 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
312 | "name": "population density", | 289 | "name": "population density", | ||
313 | "state": "active", | 290 | "state": "active", | ||
314 | "vocabulary_id": null | 291 | "vocabulary_id": null | ||
315 | }, | 292 | }, | ||
316 | { | 293 | { | ||
317 | "display_name": "reproductive", | 294 | "display_name": "reproductive", | ||
318 | "id": "6fb38736-99e6-40c9-b3b3-da34da5e6cf5", | 295 | "id": "6fb38736-99e6-40c9-b3b3-da34da5e6cf5", | ||
319 | "name": "reproductive", | 296 | "name": "reproductive", | ||
320 | "state": "active", | 297 | "state": "active", | ||
321 | "vocabulary_id": null | 298 | "vocabulary_id": null | ||
322 | }, | 299 | }, | ||
323 | { | 300 | { | ||
324 | "display_name": "women", | 301 | "display_name": "women", | ||
325 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 302 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
326 | "name": "women", | 303 | "name": "women", | ||
327 | "state": "active", | 304 | "state": "active", | ||
328 | "vocabulary_id": null | 305 | "vocabulary_id": null | ||
329 | }, | 306 | }, | ||
330 | { | 307 | { | ||
331 | "display_name": "youth", | 308 | "display_name": "youth", | ||
332 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 309 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
333 | "name": "youth", | 310 | "name": "youth", | ||
334 | "state": "active", | 311 | "state": "active", | ||
335 | "vocabulary_id": null | 312 | "vocabulary_id": null | ||
336 | } | 313 | } | ||
337 | ], | 314 | ], | ||
338 | "title": "Ghana: High Resolution Population Density Maps + | 315 | "title": "Ghana: High Resolution Population Density Maps + | ||
339 | Demographic Estimates", | 316 | Demographic Estimates", | ||
340 | "type": "dataset", | 317 | "type": "dataset", | ||
341 | "url": | 318 | "url": | ||
342 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-gha", | 319 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-gha", | ||
343 | "version": "" | 320 | "version": "" | ||
344 | } | 321 | } |