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On 17 February 2023 at 10:36:37 UTC,
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43 | "license_title": null, | 43 | "license_title": null, | ||
44 | "maintainer": null, | 44 | "maintainer": null, | ||
45 | "maintainer_email": null, | 45 | "maintainer_email": null, | ||
46 | "metadata_created": "2023-02-15T10:34:40.898066", | 46 | "metadata_created": "2023-02-15T10:34:40.898066", | ||
t | 47 | "metadata_modified": "2023-02-17T10:36:36.927400", | t | 47 | "metadata_modified": "2023-02-17T10:36:37.196264", |
48 | "name": "africa-soil-information-service", | 48 | "name": "africa-soil-information-service", | ||
49 | "notes": "<p>The Africa Soil Information Service (AfSIS) is | 49 | "notes": "<p>The Africa Soil Information Service (AfSIS) is | ||
50 | developing continent-wide digital soil maps for sub-Saharan Africa | 50 | developing continent-wide digital soil maps for sub-Saharan Africa | ||
51 | using new types of soil analysis and statistical methods, and | 51 | using new types of soil analysis and statistical methods, and | ||
52 | conducting agronomic field trials in selected sentinel sites. These | 52 | conducting agronomic field trials in selected sentinel sites. These | ||
53 | efforts include the compilation and rescue of legacy soil profile | 53 | efforts include the compilation and rescue of legacy soil profile | ||
54 | data, new data collection and analysis, and system development for | 54 | data, new data collection and analysis, and system development for | ||
55 | large-scale soil mapping using remote sensing imagery and crowdsourced | 55 | large-scale soil mapping using remote sensing imagery and crowdsourced | ||
56 | ground observations.</p>\n<p>The project area includes ~17.5 million | 56 | ground observations.</p>\n<p>The project area includes ~17.5 million | ||
57 | km2 of continental sub-Saharan Africa (SSA), an area that encompasses | 57 | km2 of continental sub-Saharan Africa (SSA), an area that encompasses | ||
58 | more than 90% of Africa\u2019s human population living in 42 | 58 | more than 90% of Africa\u2019s human population living in 42 | ||
59 | countries. The project area excludes hot and cold desert regions based | 59 | countries. The project area excludes hot and cold desert regions based | ||
60 | on the recently revised K\u00f6ppen-Geiger climate classification, as | 60 | on the recently revised K\u00f6ppen-Geiger climate classification, as | ||
61 | well as the non-desert areas of Northern Africa.</p>\n<p>New Data | 61 | well as the non-desert areas of Northern Africa.</p>\n<p>New Data | ||
62 | Collections<br />\nAfSIS ground survey teams are in the process of | 62 | Collections<br />\nAfSIS ground survey teams are in the process of | ||
63 | surveying and sampling this area using a spatially stratified, random | 63 | surveying and sampling this area using a spatially stratified, random | ||
64 | sampling approach consisting of 60, 100 km2 sentinel landscapes, which | 64 | sampling approach consisting of 60, 100 km2 sentinel landscapes, which | ||
65 | are statistically representative of the variability in climate, | 65 | are statistically representative of the variability in climate, | ||
66 | topography and vegetation of the project area. Twenty-one of the 60 | 66 | topography and vegetation of the project area. Twenty-one of the 60 | ||
67 | sentinel landscapes fall within biodiversity hotspots as designated by | 67 | sentinel landscapes fall within biodiversity hotspots as designated by | ||
68 | Conservation International.<br />\nNew data collection uses a | 68 | Conservation International.<br />\nNew data collection uses a | ||
69 | hierarchical sampling approach that replicates soil and other | 69 | hierarchical sampling approach that replicates soil and other | ||
70 | biophysical measurements at different spatial scales, linking | 70 | biophysical measurements at different spatial scales, linking | ||
71 | consistent, georeferenced ground observations to laboratory | 71 | consistent, georeferenced ground observations to laboratory | ||
72 | measurements, agronomic field trials and remote sensing | 72 | measurements, agronomic field trials and remote sensing | ||
73 | data.</p>\n<p>SpecDiag<br />\nGround surveys of the AfSIS sentinel | 73 | data.</p>\n<p>SpecDiag<br />\nGround surveys of the AfSIS sentinel | ||
74 | landscapes will provide ~9,600 new soil profile observations | 74 | landscapes will provide ~9,600 new soil profile observations | ||
75 | consisting of more than 38,000 individual soil samples. Georeferencing | 75 | consisting of more than 38,000 individual soil samples. Georeferencing | ||
76 | and sentinel landscape documentation with digital photography will | 76 | and sentinel landscape documentation with digital photography will | ||
77 | further ensure that sampling locations can be revisited at later | 77 | further ensure that sampling locations can be revisited at later | ||
78 | points in time to quantify where specific changes | 78 | points in time to quantify where specific changes | ||
79 | occurred.</p>\n<p>Soil Spectral Diagnostics<br />\nAfSIS is also using | 79 | occurred.</p>\n<p>Soil Spectral Diagnostics<br />\nAfSIS is also using | ||
80 | both near and mid-infrared spectroscopy for soil analyses, allowing | 80 | both near and mid-infrared spectroscopy for soil analyses, allowing | ||
81 | new samples to be analyzed more quickly and at a lower cost than by | 81 | new samples to be analyzed more quickly and at a lower cost than by | ||
82 | using conventional laboratory techniques alone. Spectral diagnostics | 82 | using conventional laboratory techniques alone. Spectral diagnostics | ||
83 | are used to measure carbon and nutrient content, texture, mineralogy, | 83 | are used to measure carbon and nutrient content, texture, mineralogy, | ||
84 | water holding capacity, and an entire suite of other potentially | 84 | water holding capacity, and an entire suite of other potentially | ||
85 | important soil properties.</p>\n<p>Legacy Data Rescue<br />\nNew data | 85 | important soil properties.</p>\n<p>Legacy Data Rescue<br />\nNew data | ||
86 | collections are also supported with data from the most comprehensive | 86 | collections are also supported with data from the most comprehensive | ||
87 | international soil profile database for Africa (see ISRIC WISE v. 3.1 | 87 | international soil profile database for Africa (see ISRIC WISE v. 3.1 | ||
88 | at <a href=\"http://www.isric.org\">www.isric.org</a>) currently | 88 | at <a href=\"http://www.isric.org\">www.isric.org</a>) currently | ||
89 | available, containing 4,173 African soil profiles. AfSIS is adding to | 89 | available, containing 4,173 African soil profiles. AfSIS is adding to | ||
90 | this resource by digitizing additional soil profile \u201clegacy | 90 | this resource by digitizing additional soil profile \u201clegacy | ||
91 | data\u201d where these can be retrieved from African soil survey and | 91 | data\u201d where these can be retrieved from African soil survey and | ||
92 | research organizations, georeferenced and subjected to ISRIC\u2019s | 92 | research organizations, georeferenced and subjected to ISRIC\u2019s | ||
93 | stringent data quality control criteria. This expanded soil profile | 93 | stringent data quality control criteria. This expanded soil profile | ||
94 | database now contains more than 12,000 georeferenced | 94 | database now contains more than 12,000 georeferenced | ||
95 | profiles.</p>\n<p>Remote Sensing<br />\nSubstantial effort is also to | 95 | profiles.</p>\n<p>Remote Sensing<br />\nSubstantial effort is also to | ||
96 | assembling and harmonizing satellite image time series and digital | 96 | assembling and harmonizing satellite image time series and digital | ||
97 | terrain models for SSA. These base maps are being used as spatial | 97 | terrain models for SSA. These base maps are being used as spatial | ||
98 | covariates for digital soil mapping, but can also be used for other | 98 | covariates for digital soil mapping, but can also be used for other | ||
99 | mapping and modeling purposes. For example, AfSIS is using MODIS, | 99 | mapping and modeling purposes. For example, AfSIS is using MODIS, | ||
100 | Landsat, ASTER and Quickbird images and SRTM terrain models for soil | 100 | Landsat, ASTER and Quickbird images and SRTM terrain models for soil | ||
101 | mapping, land cover change detection and estimation of landscape | 101 | mapping, land cover change detection and estimation of landscape | ||
102 | carbon stocks.</p>\n<p>By linking legacy, field and laboratory data to | 102 | carbon stocks.</p>\n<p>By linking legacy, field and laboratory data to | ||
103 | remote sensing information, digital terrain models, and other existing | 103 | remote sensing information, digital terrain models, and other existing | ||
104 | environmental covariates, AfSIS is able to provide a unique resource | 104 | environmental covariates, AfSIS is able to provide a unique resource | ||
105 | for producing a new generation of Africa soil, vegetation and | 105 | for producing a new generation of Africa soil, vegetation and | ||
106 | land-cover maps as well as wide range of statistical products.</p>\n", | 106 | land-cover maps as well as wide range of statistical products.</p>\n", | ||
107 | "num_resources": 3, | 107 | "num_resources": 3, | ||
108 | "num_tags": 7, | 108 | "num_tags": 7, | ||
109 | "organization": { | 109 | "organization": { | ||
110 | "approval_status": "approved", | 110 | "approval_status": "approved", | ||
111 | "created": "2022-11-28T12:01:18.181587", | 111 | "created": "2022-11-28T12:01:18.181587", | ||
112 | "description": "", | 112 | "description": "", | ||
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114 | "image_url": "", | 114 | "image_url": "", | ||
115 | "is_organization": true, | 115 | "is_organization": true, | ||
116 | "name": "eratosthenes-centre-of-excellence", | 116 | "name": "eratosthenes-centre-of-excellence", | ||
117 | "state": "active", | 117 | "state": "active", | ||
118 | "title": "ERATOSTHENES Centre of Excellence", | 118 | "title": "ERATOSTHENES Centre of Excellence", | ||
119 | "type": "organization" | 119 | "type": "organization" | ||
120 | }, | 120 | }, | ||
121 | "owner_org": "0b46b3cf-a376-4008-a9e1-6a48d0d87c11", | 121 | "owner_org": "0b46b3cf-a376-4008-a9e1-6a48d0d87c11", | ||
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123 | "relationships_as_object": [], | 123 | "relationships_as_object": [], | ||
124 | "relationships_as_subject": [], | 124 | "relationships_as_subject": [], | ||
125 | "resources": [ | 125 | "resources": [ | ||
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139 | "name": "Digital Soil Mapping", | 139 | "name": "Digital Soil Mapping", | ||
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145 | "url": "http://www.isric.org/explore/soilgrids", | 145 | "url": "http://www.isric.org/explore/soilgrids", | ||
146 | "url_type": null | 146 | "url_type": null | ||
147 | }, | 147 | }, | ||
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161 | "name": "Remote Sensing", | 161 | "name": "Remote Sensing", | ||
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166 | "state": "active", | 166 | "state": "active", | ||
167 | "url": "ftp://africagrids.net/", | 167 | "url": "ftp://africagrids.net/", | ||
168 | "url_type": null | 168 | "url_type": null | ||
169 | }, | 169 | }, | ||
170 | { | 170 | { | ||
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181 | "mimetype": null, | 181 | "mimetype": null, | ||
182 | "mimetype_inner": null, | 182 | "mimetype_inner": null, | ||
183 | "name": "Soil Databases", | 183 | "name": "Soil Databases", | ||
184 | "package_id": "73737a40-6524-401e-acc2-8df68721fbeb", | 184 | "package_id": "73737a40-6524-401e-acc2-8df68721fbeb", | ||
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190 | 0&offset=0&type__in=vector&title__icontains=africa%20soil%20profiles", | 190 | 0&offset=0&type__in=vector&title__icontains=africa%20soil%20profiles", | ||
191 | "url_type": null | 191 | "url_type": null | ||
192 | } | 192 | } | ||
193 | ], | 193 | ], | ||
194 | "state": "active", | 194 | "state": "active", | ||
195 | "tags": [ | 195 | "tags": [ | ||
196 | { | 196 | { | ||
197 | "display_name": "Africa", | 197 | "display_name": "Africa", | ||
198 | "id": "62999514-db34-4eda-9cce-6bd154304189", | 198 | "id": "62999514-db34-4eda-9cce-6bd154304189", | ||
199 | "name": "Africa", | 199 | "name": "Africa", | ||
200 | "state": "active", | 200 | "state": "active", | ||
201 | "vocabulary_id": null | 201 | "vocabulary_id": null | ||
202 | }, | 202 | }, | ||
203 | { | 203 | { | ||
204 | "display_name": "Food security", | 204 | "display_name": "Food security", | ||
205 | "id": "7e08c175-576a-4279-81a0-1a14c7a5004b", | 205 | "id": "7e08c175-576a-4279-81a0-1a14c7a5004b", | ||
206 | "name": "Food security", | 206 | "name": "Food security", | ||
207 | "state": "active", | 207 | "state": "active", | ||
208 | "vocabulary_id": null | 208 | "vocabulary_id": null | ||
209 | }, | 209 | }, | ||
210 | { | 210 | { | ||
211 | "display_name": "Raw materials", | 211 | "display_name": "Raw materials", | ||
212 | "id": "3e3d527f-ec38-440d-906e-cbe9dd5e70f6", | 212 | "id": "3e3d527f-ec38-440d-906e-cbe9dd5e70f6", | ||
213 | "name": "Raw materials", | 213 | "name": "Raw materials", | ||
214 | "state": "active", | 214 | "state": "active", | ||
215 | "vocabulary_id": null | 215 | "vocabulary_id": null | ||
216 | }, | 216 | }, | ||
217 | { | 217 | { | ||
218 | "display_name": "Regional", | 218 | "display_name": "Regional", | ||
219 | "id": "e8c4b54e-3890-41f5-bd35-b88401ab9753", | 219 | "id": "e8c4b54e-3890-41f5-bd35-b88401ab9753", | ||
220 | "name": "Regional", | 220 | "name": "Regional", | ||
221 | "state": "active", | 221 | "state": "active", | ||
222 | "vocabulary_id": null | 222 | "vocabulary_id": null | ||
223 | }, | 223 | }, | ||
224 | { | 224 | { | ||
225 | "display_name": "Soils", | 225 | "display_name": "Soils", | ||
226 | "id": "dc67b9c2-ff9f-4522-ac1b-56a54d73f9da", | 226 | "id": "dc67b9c2-ff9f-4522-ac1b-56a54d73f9da", | ||
227 | "name": "Soils", | 227 | "name": "Soils", | ||
228 | "state": "active", | 228 | "state": "active", | ||
229 | "vocabulary_id": null | 229 | "vocabulary_id": null | ||
230 | }, | 230 | }, | ||
231 | { | 231 | { | ||
232 | "display_name": "Spectral", | 232 | "display_name": "Spectral", | ||
233 | "id": "db9a5c31-a1c5-4768-b187-893cf13b0e2a", | 233 | "id": "db9a5c31-a1c5-4768-b187-893cf13b0e2a", | ||
234 | "name": "Spectral", | 234 | "name": "Spectral", | ||
235 | "state": "active", | 235 | "state": "active", | ||
236 | "vocabulary_id": null | 236 | "vocabulary_id": null | ||
237 | }, | 237 | }, | ||
238 | { | 238 | { | ||
239 | "display_name": "universal", | 239 | "display_name": "universal", | ||
240 | "id": "18f6cd03-8b24-43ee-80d0-2432b2b09552", | 240 | "id": "18f6cd03-8b24-43ee-80d0-2432b2b09552", | ||
241 | "name": "universal", | 241 | "name": "universal", | ||
242 | "state": "active", | 242 | "state": "active", | ||
243 | "vocabulary_id": null | 243 | "vocabulary_id": null | ||
244 | } | 244 | } | ||
245 | ], | 245 | ], | ||
246 | "title": "Africa Soil Information Service", | 246 | "title": "Africa Soil Information Service", | ||
247 | "type": "dataset", | 247 | "type": "dataset", | ||
248 | "url": null, | 248 | "url": null, | ||
249 | "version": null | 249 | "version": null | ||
250 | } | 250 | } |