Changes
On July 1, 2024 at 11:36:35 AM UTC, Alessio Bulckaen:
-
Added the following fields to Vegetation Carbon Stock 2001-2020
- Temporal Resolution with value Yearly maps
- Period (years) with value 2001-2020
f | 1 | { | f | 1 | { |
2 | "author": "Alessio Bulckaen", | 2 | "author": "Alessio Bulckaen", | ||
3 | "author_email": "alessio.bulckaen@bc3research.org", | 3 | "author_email": "alessio.bulckaen@bc3research.org", | ||
4 | "creator_user_id": "c074a22a-ce93-493a-bfff-f2f9ec56cd95", | 4 | "creator_user_id": "c074a22a-ce93-493a-bfff-f2f9ec56cd95", | ||
5 | "extras": [ | 5 | "extras": [ | ||
6 | { | 6 | { | ||
7 | "key": "Map content:", | 7 | "key": "Map content:", | ||
8 | "value": "Vegetation carbon stock" | 8 | "value": "Vegetation carbon stock" | ||
9 | }, | 9 | }, | ||
10 | { | 10 | { | ||
n | n | 11 | "key": "Period (years)", | ||
12 | "value": "2001-2020" | ||||
13 | }, | ||||
14 | { | ||||
11 | "key": "Spatial Resolution:", | 15 | "key": "Spatial Resolution:", | ||
12 | "value": "300m" | 16 | "value": "300m" | ||
n | n | 17 | }, | ||
18 | { | ||||
19 | "key": "Temporal Resolution", | ||||
20 | "value": "Yearly maps" | ||||
13 | }, | 21 | }, | ||
14 | { | 22 | { | ||
15 | "key": "Unit of measure:", | 23 | "key": "Unit of measure:", | ||
16 | "value": "Tonnes per hectare (t/ha)" | 24 | "value": "Tonnes per hectare (t/ha)" | ||
17 | } | 25 | } | ||
18 | ], | 26 | ], | ||
19 | "groups": [ | 27 | "groups": [ | ||
20 | { | 28 | { | ||
21 | "description": "#__ Annual carbon vegetation stock all over the | 29 | "description": "#__ Annual carbon vegetation stock all over the | ||
22 | world to identify global trends, comparing results across geographic | 30 | world to identify global trends, comparing results across geographic | ||
23 | areas and over time__\r\n\r\nThe maps are computed based on the | 31 | areas and over time__\r\n\r\nThe maps are computed based on the | ||
24 | original methodology by Gibbs and Ruesch (2008) and using IPCC 2006 | 32 | original methodology by Gibbs and Ruesch (2008) and using IPCC 2006 | ||
25 | default factors to estimate the value of __above-ground__ and | 33 | default factors to estimate the value of __above-ground__ and | ||
26 | __below-ground vegetation carbon stock__. \r\nFor each basic spatial | 34 | __below-ground vegetation carbon stock__. \r\nFor each basic spatial | ||
27 | unit (an area of 9 hectares) in the map, the model considers:\r\n*The | 35 | unit (an area of 9 hectares) in the map, the model considers:\r\n*The | ||
28 | landcover class, according to the ESA-CCI dataset,\r\n*The ecological | 36 | landcover class, according to the ESA-CCI dataset,\r\n*The ecological | ||
29 | area, from the FAO's Ecofloristic region and geographical zones | 37 | area, from the FAO's Ecofloristic region and geographical zones | ||
30 | dataset,\r\n*The geographical location, to capture regional/ | 38 | dataset,\r\n*The geographical location, to capture regional/ | ||
31 | continental specific characteristics,\r\n*in the case of a forest, the | 39 | continental specific characteristics,\r\n*in the case of a forest, the | ||
32 | carbon content also depends on how pristine, old and intact the forest | 40 | carbon content also depends on how pristine, old and intact the forest | ||
33 | is. So-called primary forest stores a higher quantity of | 41 | is. So-called primary forest stores a higher quantity of | ||
34 | carbon,\r\n*areas burned by a fire assume a significantly lower or | 42 | carbon,\r\n*areas burned by a fire assume a significantly lower or | ||
35 | absolutely no vegetation carbon stock for that year. \r\n\r\nThe | 43 | absolutely no vegetation carbon stock for that year. \r\n\r\nThe | ||
36 | vegetation carbon stock includes values for above-ground and | 44 | vegetation carbon stock includes values for above-ground and | ||
37 | below-ground vegetation carbon stock, but do not consider any | 45 | below-ground vegetation carbon stock, but do not consider any | ||
38 | contribution of the soil organic carbon stock.\r\n\r\n##Datasets used | 46 | contribution of the soil organic carbon stock.\r\n\r\n##Datasets used | ||
39 | in the analysis\r\n*ESA-CCI land cover data used to retrieve a | 47 | in the analysis\r\n*ESA-CCI land cover data used to retrieve a | ||
40 | complete time series of land cover classes from 1992 to 2020. Land | 48 | complete time series of land cover classes from 1992 to 2020. Land | ||
41 | cover classes are used to assign IPCC values of carbon stock. It | 49 | cover classes are used to assign IPCC values of carbon stock. It | ||
42 | should be noted that some classes, such as water bodies and glaciers, | 50 | should be noted that some classes, such as water bodies and glaciers, | ||
43 | are excluded from the computation in this first set of results, while | 51 | are excluded from the computation in this first set of results, while | ||
44 | others, like bare areas, only contribute modestly to carbon stock. | 52 | others, like bare areas, only contribute modestly to carbon stock. | ||
45 | \r\n*Ecofloristic region and geographical zones. The zones are assumed | 53 | \r\n*Ecofloristic region and geographical zones. The zones are assumed | ||
46 | to be static and are used to select default IPCC values and to produce | 54 | to be static and are used to select default IPCC values and to produce | ||
47 | results at different spatial scales.\r\nSpatially explicit layers on | 55 | results at different spatial scales.\r\nSpatially explicit layers on | ||
48 | intact/primary forests. The layers provide information on the presence | 56 | intact/primary forests. The layers provide information on the presence | ||
49 | of intact forests, which are used as a proxy for primary forests. The | 57 | of intact forests, which are used as a proxy for primary forests. The | ||
50 | information is available for the years 2000, 2013, 2016, and 2020. The | 58 | information is available for the years 2000, 2013, 2016, and 2020. The | ||
51 | location of intact and non-intact forests allows for a proxy of the | 59 | location of intact and non-intact forests allows for a proxy of the | ||
52 | degree of forest degradation and other anthropogenic effects that | 60 | degree of forest degradation and other anthropogenic effects that | ||
53 | affect the carbon stock in the vegetation on non-intact areas. | 61 | affect the carbon stock in the vegetation on non-intact areas. | ||
54 | \r\n*Occurrence of fires (annually available from 2000 to 2020). The | 62 | \r\n*Occurrence of fires (annually available from 2000 to 2020). The | ||
55 | information is needed to incorporate in the model the effect of | 63 | information is needed to incorporate in the model the effect of | ||
56 | wildfires on the carbon budget of the ecosystem. \r\n\r\n##_Main | 64 | wildfires on the carbon budget of the ecosystem. \r\n\r\n##_Main | ||
57 | drivers of change_\r\nIt is important to emphasize that changes in | 65 | drivers of change_\r\nIt is important to emphasize that changes in | ||
58 | these results are mainly driven by land cover changes, and potentially | 66 | these results are mainly driven by land cover changes, and potentially | ||
59 | by land cover re-classification, which do not always match with the | 67 | by land cover re-classification, which do not always match with the | ||
60 | real, but rather the observed ecological | 68 | real, but rather the observed ecological | ||
61 | information\r\n\r\n##__Results interpretation__\r\n\r\n", | 69 | information\r\n\r\n##__Results interpretation__\r\n\r\n", | ||
62 | "display_name": "Vegetation Carbon Stock 2001-2020", | 70 | "display_name": "Vegetation Carbon Stock 2001-2020", | ||
63 | "id": "9d9a2abf-a4b5-45b6-aa11-57c8e287c89d", | 71 | "id": "9d9a2abf-a4b5-45b6-aa11-57c8e287c89d", | ||
64 | "image_display_url": "", | 72 | "image_display_url": "", | ||
65 | "name": "vegetation-carbon-stock-2001-2020", | 73 | "name": "vegetation-carbon-stock-2001-2020", | ||
66 | "title": "Vegetation Carbon Stock 2001-2020" | 74 | "title": "Vegetation Carbon Stock 2001-2020" | ||
67 | } | 75 | } | ||
68 | ], | 76 | ], | ||
69 | "id": "b6900b3f-c345-4cae-90a2-809104b0ed76", | 77 | "id": "b6900b3f-c345-4cae-90a2-809104b0ed76", | ||
70 | "isopen": true, | 78 | "isopen": true, | ||
71 | "license_id": "cc-by", | 79 | "license_id": "cc-by", | ||
72 | "license_title": "Creative Commons Attribution", | 80 | "license_title": "Creative Commons Attribution", | ||
73 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 81 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
74 | "maintainer": "Ruben Crespo", | 82 | "maintainer": "Ruben Crespo", | ||
75 | "maintainer_email": "ruben.crespo@bc3research.org", | 83 | "maintainer_email": "ruben.crespo@bc3research.org", | ||
76 | "metadata_created": "2023-03-24T16:35:00.363856", | 84 | "metadata_created": "2023-03-24T16:35:00.363856", | ||
t | 77 | "metadata_modified": "2024-07-01T11:19:03.542436", | t | 85 | "metadata_modified": "2024-07-01T11:36:35.467164", |
78 | "name": "global-vegetation-carbon-stock-2001-2020", | 86 | "name": "global-vegetation-carbon-stock-2001-2020", | ||
79 | "notes": "#__Annual global vegetation carbon stocks to identify | 87 | "notes": "#__Annual global vegetation carbon stocks to identify | ||
80 | global spatiotemporal trends__\r\nThese annual global maps are | 88 | global spatiotemporal trends__\r\nThese annual global maps are | ||
81 | computed based on the original methodology by Gibbs and Ruesch (2008) | 89 | computed based on the original methodology by Gibbs and Ruesch (2008) | ||
82 | [1] and using IPCC 2006 [2] default factors to estimate the value of | 90 | [1] and using IPCC 2006 [2] default factors to estimate the value of | ||
83 | __above-ground__ and __below-ground vegetation carbon stock__. The | 91 | __above-ground__ and __below-ground vegetation carbon stock__. The | ||
84 | maps are provided at 300 m spatial resolution, the model to estimate | 92 | maps are provided at 300 m spatial resolution, the model to estimate | ||
85 | these stock considers:\r\n\r\n* the land cover class of the area | 93 | these stock considers:\r\n\r\n* the land cover class of the area | ||
86 | observed, according to the European Space Agency - Climate Change | 94 | observed, according to the European Space Agency - Climate Change | ||
87 | Initiative (ESA-CCI) dataset,\r\n* the ecological area, from the Food | 95 | Initiative (ESA-CCI) dataset,\r\n* the ecological area, from the Food | ||
88 | and Agriculture Organization of the United Nations (FAO)'s | 96 | and Agriculture Organization of the United Nations (FAO)'s | ||
89 | Ecofloristic region and\r\n* the geographical zones to capture | 97 | Ecofloristic region and\r\n* the geographical zones to capture | ||
90 | regional/ continental specific characteristics.\r\n\r\nFor forests, | 98 | regional/ continental specific characteristics.\r\n\r\nFor forests, | ||
91 | the carbon content additionally depends on how intact the forest is, | 99 | the carbon content additionally depends on how intact the forest is, | ||
92 | with so-called primary forest storing a higher quantity of carbon. | 100 | with so-called primary forest storing a higher quantity of carbon. | ||
93 | Moreover, areas burned by fire are modeled to have a significantly | 101 | Moreover, areas burned by fire are modeled to have a significantly | ||
94 | lower to no vegetation carbon stock.\r\n\r\nResults include both | 102 | lower to no vegetation carbon stock.\r\n\r\nResults include both | ||
95 | above-ground and below-ground vegetation carbon but do not consider | 103 | above-ground and below-ground vegetation carbon but do not consider | ||
96 | any contribution of the coarse woody debris or soil organic carbon | 104 | any contribution of the coarse woody debris or soil organic carbon | ||
97 | stocks. The results represent the worldwide terrestrial carbon stocks | 105 | stocks. The results represent the worldwide terrestrial carbon stocks | ||
98 | in vegetation that are modeled based on yearly spatially explicit | 106 | in vegetation that are modeled based on yearly spatially explicit | ||
99 | information on the above-noted inputs, particularly dynamic land | 107 | information on the above-noted inputs, particularly dynamic land | ||
100 | cover, primary forest, and burned area data.\r\n\r\n\r\n##Datasets | 108 | cover, primary forest, and burned area data.\r\n\r\n\r\n##Datasets | ||
101 | used in the analysis\r\n1. ESA-CCI land cover data [3] provide a | 109 | used in the analysis\r\n1. ESA-CCI land cover data [3] provide a | ||
102 | complete time series of land cover from 2001 to 2020. Land cover | 110 | complete time series of land cover from 2001 to 2020. Land cover | ||
103 | classes are used to assign IPCC 2006 values of carbon stock. Some | 111 | classes are used to assign IPCC 2006 values of carbon stock. Some | ||
104 | classes, such as water bodies and glaciers, provide no vegetation | 112 | classes, such as water bodies and glaciers, provide no vegetation | ||
105 | carbon storage, while others, like bare areas and lichen and moss, | 113 | carbon storage, while others, like bare areas and lichen and moss, | ||
106 | contribute negligibly to carbon stock.\r\n2. Ecofloristic region [4] | 114 | contribute negligibly to carbon stock.\r\n2. Ecofloristic region [4] | ||
107 | and geographical zones [5]. The zones are assumed to be static and are | 115 | and geographical zones [5]. The zones are assumed to be static and are | ||
108 | used to select default IPCC 2006 values and to produce results at | 116 | used to select default IPCC 2006 values and to produce results at | ||
109 | different spatial scales.\r\n3. Spatially explicit layers on | 117 | different spatial scales.\r\n3. Spatially explicit layers on | ||
110 | intact/primary forests [6]. The layers provide information on the | 118 | intact/primary forests [6]. The layers provide information on the | ||
111 | presence of intact forests, which are used as a proxy for primary | 119 | presence of intact forests, which are used as a proxy for primary | ||
112 | forests. The information is available for the years 2000, 2013, 2016, | 120 | forests. The information is available for the years 2000, 2013, 2016, | ||
113 | and 2020. Whenever data for a year is not available, the model uses | 121 | and 2020. Whenever data for a year is not available, the model uses | ||
114 | the latest observation for that variable in the time series ( e.g. the | 122 | the latest observation for that variable in the time series ( e.g. the | ||
115 | information in 2000 has been used to estimate values from 2001 to 2012 | 123 | information in 2000 has been used to estimate values from 2001 to 2012 | ||
116 | included).\r\nThe location of intact and non-intact forests allows for | 124 | included).\r\nThe location of intact and non-intact forests allows for | ||
117 | a proxy of the degree of forest degradation and other anthropogenic | 125 | a proxy of the degree of forest degradation and other anthropogenic | ||
118 | effects that affect vegetation carbon stocks in non-intact areas. | 126 | effects that affect vegetation carbon stocks in non-intact areas. | ||
119 | \r\n4. Occurrence of fires [7] (annually available from 2001 to 2020). | 127 | \r\n4. Occurrence of fires [7] (annually available from 2001 to 2020). | ||
120 | The information is required to incorporate the effect of wildfires on | 128 | The information is required to incorporate the effect of wildfires on | ||
121 | vegetation carbon storage.\r\n\r\n##__Interpretation of | 129 | vegetation carbon storage.\r\n\r\n##__Interpretation of | ||
122 | results__\r\nThe results represent the worldwide terrestrial | 130 | results__\r\nThe results represent the worldwide terrestrial | ||
123 | vegetation carbon stocks based on inputs described in the previous | 131 | vegetation carbon stocks based on inputs described in the previous | ||
124 | section. These inputs ensure consistent global results by using time | 132 | section. These inputs ensure consistent global results by using time | ||
125 | series global data sets and an approach aligned with the 2006 IPCC | 133 | series global data sets and an approach aligned with the 2006 IPCC | ||
126 | guidelines. Data may not align with country-level estimates produced | 134 | guidelines. Data may not align with country-level estimates produced | ||
127 | using different data, methods, or spatiotemporal scales, and do not | 135 | using different data, methods, or spatiotemporal scales, and do not | ||
128 | provide a full view of carbon fluxes from lands or other, non-CO2, | 136 | provide a full view of carbon fluxes from lands or other, non-CO2, | ||
129 | greenhouse gas emissions. It is important to emphasize that changes in | 137 | greenhouse gas emissions. It is important to emphasize that changes in | ||
130 | these results are mainly driven by land cover changes, and potentially | 138 | these results are mainly driven by land cover changes, and potentially | ||
131 | by land cover re-classification, which do not always match with the | 139 | by land cover re-classification, which do not always match with the | ||
132 | real, but rather the observed ecological information. Forests\u2019 | 140 | real, but rather the observed ecological information. Forests\u2019 | ||
133 | results can also be affected significantly by the occurrence of | 141 | results can also be affected significantly by the occurrence of | ||
134 | fire.\r\n\r\nThe average global contribution of each aggregated land | 142 | fire.\r\n\r\nThe average global contribution of each aggregated land | ||
135 | cover class from 2001-2020 (expressed in %) to vegetation carbon | 143 | cover class from 2001-2020 (expressed in %) to vegetation carbon | ||
136 | stock:\r\n\r\n* Forest 70,50% | 144 | stock:\r\n\r\n* Forest 70,50% | ||
137 | ...................................................................... | 145 | ...................................................................... | ||
138 | (ESA-CCI LC 50 - 90)\r\n* Shrub and Herbaceous vegetation | 146 | (ESA-CCI LC 50 - 90)\r\n* Shrub and Herbaceous vegetation | ||
139 | 14,18%.......................................... (ESA-CCI LC 100 - | 147 | 14,18%.......................................... (ESA-CCI LC 100 - | ||
140 | 130)\r\n* Agricultural vegetation | 148 | 130)\r\n* Agricultural vegetation | ||
141 | 9,29%............................................................... | 149 | 9,29%............................................................... | ||
142 | (ESA-CCI LC 10 - 40)\r\n* Wetland 5,31% | 150 | (ESA-CCI LC 10 - 40)\r\n* Wetland 5,31% | ||
143 | ...................................................................... | 151 | ...................................................................... | ||
144 | (ESA-CCI LC 160 - 180)\r\n* Bare area 0,40% | 152 | (ESA-CCI LC 160 - 180)\r\n* Bare area 0,40% | ||
145 | ...................................................................... | 153 | ...................................................................... | ||
146 | (ESA-CCI LC 140, 200 - 202)\r\n* Sparse vegetation 0,33% | 154 | (ESA-CCI LC 140, 200 - 202)\r\n* Sparse vegetation 0,33% | ||
147 | .................................................................... | 155 | .................................................................... | ||
148 | (ESA-CCI LC 150 - 153)\r\n* Artificial Surface, Waterbody, and | 156 | (ESA-CCI LC 150 - 153)\r\n* Artificial Surface, Waterbody, and | ||
149 | Permanent snow and ice 0,00%..... (ESA-CCI LC 190, 210 and | 157 | Permanent snow and ice 0,00%..... (ESA-CCI LC 190, 210 and | ||
150 | 220)\r\n\r\n###Funding and acknowledgment\r\nThis work was produced by | 158 | 220)\r\n\r\n###Funding and acknowledgment\r\nThis work was produced by | ||
151 | the ARIES team at BC3 and funded by the World Bank under the GPS and | 159 | the ARIES team at BC3 and funded by the World Bank under the GPS and | ||
152 | PROGREEN programs.\r\n\r\nARIES (ARtificial Intelligence for | 160 | PROGREEN programs.\r\n\r\nARIES (ARtificial Intelligence for | ||
153 | Environment and Sustainability) - | 161 | Environment and Sustainability) - | ||
154 | https://aries.integratedmodelling.org/technology\r\n\r\nBC3 (Basque | 162 | https://aries.integratedmodelling.org/technology\r\n\r\nBC3 (Basque | ||
155 | Center for Climate Change) - | 163 | Center for Climate Change) - | ||
156 | https://www.bc3research.org/index.php\r\n\r\nGPS (Global Program for | 164 | https://www.bc3research.org/index.php\r\n\r\nGPS (Global Program for | ||
157 | Sustainability) - | 165 | Sustainability) - | ||
158 | dbank.org/en/programs/global-program-on-sustainability\r\n\r\nPROGREEN | 166 | dbank.org/en/programs/global-program-on-sustainability\r\n\r\nPROGREEN | ||
159 | (Global Partnership for Sustainable and Resilient Landscapes) - | 167 | (Global Partnership for Sustainable and Resilient Landscapes) - | ||
160 | https://www.progreen.info/about_page\r\n\r\n###References and | 168 | https://www.progreen.info/about_page\r\n\r\n###References and | ||
161 | citations\r\n1. Gibbs and Ruesch (2008) - New IPCC Tier-1 Global | 169 | citations\r\n1. Gibbs and Ruesch (2008) - New IPCC Tier-1 Global | ||
162 | Biomass Carbon Map for the Year 2000 (dataset): | 170 | Biomass Carbon Map for the Year 2000 (dataset): | ||
163 | https://www.osti.gov/biblio/1463800\r\n2. IPCC 2006 - | 171 | https://www.osti.gov/biblio/1463800\r\n2. IPCC 2006 - | ||
164 | rt/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/\r\n3. | 172 | rt/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/\r\n3. | ||
165 | ESA-Climate Change Initiative (CCI) dataset: | 173 | ESA-Climate Change Initiative (CCI) dataset: | ||
166 | https://doi.org/10.24381/cds.006f2c9a\r\n4. (FAO)'s Ecofloristic | 174 | https://doi.org/10.24381/cds.006f2c9a\r\n4. (FAO)'s Ecofloristic | ||
167 | region: | 175 | region: | ||
168 | https://databasin.org/datasets/dc4f6efd1fa84ea99df61ae9c5b3b763/\r\n5. | 176 | https://databasin.org/datasets/dc4f6efd1fa84ea99df61ae9c5b3b763/\r\n5. | ||
169 | Geographic (continental) areas: | 177 | Geographic (continental) areas: | ||
170 | cdiac.ess-dive.lbl.gov/ftp/global_carbon/continental_regions.zip\r\n6. | 178 | cdiac.ess-dive.lbl.gov/ftp/global_carbon/continental_regions.zip\r\n6. | ||
171 | Intact Forest Landscapes data: | 179 | Intact Forest Landscapes data: | ||
172 | https://intactforests.org/data.ifl.html.\r\n7. MODIS burned land maps: | 180 | https://intactforests.org/data.ifl.html.\r\n7. MODIS burned land maps: | ||
173 | https://modis-fire.umd.edu/ba.html, product MCD64A1", | 181 | https://modis-fire.umd.edu/ba.html, product MCD64A1", | ||
174 | "num_resources": 24, | 182 | "num_resources": 24, | ||
175 | "num_tags": 0, | 183 | "num_tags": 0, | ||
176 | "organization": { | 184 | "organization": { | ||
177 | "approval_status": "approved", | 185 | "approval_status": "approved", | ||
178 | "created": "2023-02-03T16:35:39.850142", | 186 | "created": "2023-02-03T16:35:39.850142", | ||
179 | "description": "Scientists in the past collected data in | 187 | "description": "Scientists in the past collected data in | ||
180 | notebooks. In the digital age, we need scientific data and models to | 188 | notebooks. In the digital age, we need scientific data and models to | ||
181 | be Findable, Accessible, Interoperable, and Reusable, helping | 189 | be Findable, Accessible, Interoperable, and Reusable, helping | ||
182 | individuals, businesses, and governments make better informed | 190 | individuals, businesses, and governments make better informed | ||
183 | decisions.\r\nA fully connected information landscape using open, | 191 | decisions.\r\nA fully connected information landscape using open, | ||
184 | safe, accurate, \u201cWikipedia-like\u201d sharing and linking of | 192 | safe, accurate, \u201cWikipedia-like\u201d sharing and linking of | ||
185 | models can enable data-intensive science for decision making on a | 193 | models can enable data-intensive science for decision making on a | ||
186 | scale yet unimagined.\r\nWe want to share the methods and technologies | 194 | scale yet unimagined.\r\nWe want to share the methods and technologies | ||
187 | we have built to achieve this vision. Join us to reach it faster.", | 195 | we have built to achieve this vision. Join us to reach it faster.", | ||
188 | "id": "e7a09a40-27a3-42b0-b265-8e034fe1454a", | 196 | "id": "e7a09a40-27a3-42b0-b265-8e034fe1454a", | ||
189 | "image_url": | 197 | "image_url": | ||
190 | "https://integratedmodelling.org/statics/logos/KLAB_icono_512.png", | 198 | "https://integratedmodelling.org/statics/logos/KLAB_icono_512.png", | ||
191 | "is_organization": true, | 199 | "is_organization": true, | ||
192 | "name": "integrated-modelling-parnership", | 200 | "name": "integrated-modelling-parnership", | ||
193 | "state": "active", | 201 | "state": "active", | ||
194 | "title": "Integrated Modelling Partnership", | 202 | "title": "Integrated Modelling Partnership", | ||
195 | "type": "organization" | 203 | "type": "organization" | ||
196 | }, | 204 | }, | ||
197 | "owner_org": "e7a09a40-27a3-42b0-b265-8e034fe1454a", | 205 | "owner_org": "e7a09a40-27a3-42b0-b265-8e034fe1454a", | ||
198 | "private": false, | 206 | "private": false, | ||
199 | "relationships_as_object": [], | 207 | "relationships_as_object": [], | ||
200 | "relationships_as_subject": [], | 208 | "relationships_as_subject": [], | ||
201 | "resources": [ | 209 | "resources": [ | ||
202 | { | 210 | { | ||
203 | "cache_last_updated": null, | 211 | "cache_last_updated": null, | ||
204 | "cache_url": null, | 212 | "cache_url": null, | ||
205 | "created": "2023-06-20T10:47:39.561951", | 213 | "created": "2023-06-20T10:47:39.561951", | ||
206 | "datastore_active": false, | 214 | "datastore_active": false, | ||
207 | "description": "The map provides the value of the tonnes of | 215 | "description": "The map provides the value of the tonnes of | ||
208 | vegetation carbon stock per hectare (t/ha), each grid has an | 216 | vegetation carbon stock per hectare (t/ha), each grid has an | ||
209 | approximate resolution of 300m.\r\n_[The values in the map are | 217 | approximate resolution of 300m.\r\n_[The values in the map are | ||
210 | expressed using an intensive quantity (intensive physical | 218 | expressed using an intensive quantity (intensive physical | ||
211 | property)]_", | 219 | property)]_", | ||
212 | "format": "WCS", | 220 | "format": "WCS", | ||
213 | "hash": "", | 221 | "hash": "", | ||
214 | "id": "1f4ecb2a-226f-44f2-8875-3e12151b0c0a", | 222 | "id": "1f4ecb2a-226f-44f2-8875-3e12151b0c0a", | ||
215 | "last_modified": null, | 223 | "last_modified": null, | ||
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691 | "name": "Global Vegetation Carbon Stock in 2019", | 699 | "name": "Global Vegetation Carbon Stock in 2019", | ||
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706 | "description": "The map provides the value of the tonnes of | 714 | "description": "The map provides the value of the tonnes of | ||
707 | vegetation carbon stock per hectare (t/ha), each grid has an | 715 | vegetation carbon stock per hectare (t/ha), each grid has an | ||
708 | approximate resolution of 300m.\r\n_[The values in the map are | 716 | approximate resolution of 300m.\r\n_[The values in the map are | ||
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718 | "name": "Global Vegetation Carbon Stock in 2020", | 726 | "name": "Global Vegetation Carbon Stock in 2020", | ||
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727 | }, | 735 | }, | ||
728 | { | 736 | { | ||
729 | "cache_last_updated": null, | 737 | "cache_last_updated": null, | ||
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731 | "created": "2023-07-07T10:05:56.850781", | 739 | "created": "2023-07-07T10:05:56.850781", | ||
732 | "datastore_active": false, | 740 | "datastore_active": false, | ||
733 | "description": "The maps composing this dataset are downloadable | 741 | "description": "The maps composing this dataset are downloadable | ||
734 | as tiff files. Each map provides the value of the tonnes of vegetation | 742 | as tiff files. Each map provides the value of the tonnes of vegetation | ||
735 | carbon stock per hectare (t/ha) for a year in the time series. The | 743 | carbon stock per hectare (t/ha) for a year in the time series. The | ||
736 | maps have a spatial resolution of approximately 300m. _[The values in | 744 | maps have a spatial resolution of approximately 300m. _[The values in | ||
737 | the map are expressed using an intensive quantity (intensive physical | 745 | the map are expressed using an intensive quantity (intensive physical | ||
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753 | "url": "https://integratedmodelling.org/statics/worldbank/", | 761 | "url": "https://integratedmodelling.org/statics/worldbank/", | ||
754 | "url_type": null | 762 | "url_type": null | ||
755 | }, | 763 | }, | ||
756 | { | 764 | { | ||
757 | "cache_last_updated": null, | 765 | "cache_last_updated": null, | ||
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760 | "datastore_active": false, | 768 | "datastore_active": false, | ||
761 | "description": "The table summarizes the tonnes of vegetation | 769 | "description": "The table summarizes the tonnes of vegetation | ||
762 | carbon stored by landcover class, for each year in time series | 770 | carbon stored by landcover class, for each year in time series | ||
763 | (2001-2020), for each country", | 771 | (2001-2020), for each country", | ||
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779 | "url_type": "upload" | 787 | "url_type": "upload" | ||
780 | }, | 788 | }, | ||
781 | { | 789 | { | ||
782 | "cache_last_updated": null, | 790 | "cache_last_updated": null, | ||
783 | "cache_url": null, | 791 | "cache_url": null, | ||
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785 | "datastore_active": false, | 793 | "datastore_active": false, | ||
786 | "description": "__Vegetation carbon stock legend__\r\nThis table | 794 | "description": "__Vegetation carbon stock legend__\r\nThis table | ||
787 | summarizes the aggregation of the original classes in the ESA-CCI | 795 | summarizes the aggregation of the original classes in the ESA-CCI | ||
788 | classification to the _aggregated classes_ used in the report and the | 796 | classification to the _aggregated classes_ used in the report and the | ||
789 | crosswalk to the _ARIES semantic concepts_", | 797 | crosswalk to the _ARIES semantic concepts_", | ||
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820 | "name": "Vegetation Carbon Stock Summary Table (revised)", | 828 | "name": "Vegetation Carbon Stock Summary Table (revised)", | ||
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830 | ], | 838 | ], | ||
831 | "state": "active", | 839 | "state": "active", | ||
832 | "tags": [], | 840 | "tags": [], | ||
833 | "title": "Vegetation Carbon Stock 2001-2020", | 841 | "title": "Vegetation Carbon Stock 2001-2020", | ||
834 | "type": "dataset", | 842 | "type": "dataset", | ||
835 | "url": "", | 843 | "url": "", | ||
836 | "version": "" | 844 | "version": "" | ||
837 | } | 845 | } |