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  "author": "IHP-WINS",
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  "author": "IHP-WINS",
            
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  "author_email": "ihp-wins@unesco.org",
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  "contact_email": "ihp-wins@unesco.org",
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  "created": "2025-08-20",
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  "created": "2025-08-20",
            
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  "doi": "10.63253/atktsf8a",
            
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  "doi_date_published": "2025-08-28",
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  "doi_date_published": "2025-08-28",
            
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      "description": "UNESCO member since 1978",
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      "description": "UNESCO member since 1978",
            
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      "display_name": "Cabo Verde",
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      "display_name": "Cabo Verde",
            
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      "name": "cabo-verde",
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      "name": "cabo-verde",
            
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      "title": "Cabo Verde"
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      "title": "Cabo Verde"
            
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  "identifier": 
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  "identifier": 
            
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-Novo-Town,-Porto-Novo-Municipality,-Cabo-Verde-as-of-13-August-2025",
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-Novo-Town,-Porto-Novo-Municipality,-Cabo-Verde-as-of-13-August-2025",
            
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  "license_title": "Creative Commons Attribution Share-Alike",
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  "maintainer": "IHP-WINS",
            
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  "metadata_created": "2025-08-20T13:42:57.401426",
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  "metadata_created": "2025-08-20T13:42:57.401426",
            
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  "metadata_modified": "2025-08-28T13:17:53.204683",
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  "metadata_modified": "2025-08-28T13:46:50.680137",
            
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  "metadata_profile": [],
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  "metadata_profile": [],
            
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  "modified": "2025-08-28",
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  "modified": "2025-08-28",
            
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  "name": 
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  "name": 
            
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to-novo-town-porto-novo-municipality-cabo-verde-as-of-13-august-2025",
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to-novo-town-porto-novo-municipality-cabo-verde-as-of-13-august-2025",
            
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  "notes": "This dataset illustrates satellite-detected mudflow extent 
62
  "notes": "This dataset illustrates satellite-detected mudflow extent 
            
63
in Sao Vicente, Cabo Verde as observed from Pleiades very 
63
in Sao Vicente, Cabo Verde as observed from Pleiades very 
            
64
high-resolution satellite image. About 12 km\u00b2 of land appears to 
64
high-resolution satellite image. About 12 km\u00b2 of land appears to 
            
65
be affected by the flood / mudflow extent. UNOSAT identified around 
65
be affected by the flood / mudflow extent. UNOSAT identified around 
            
66
4200 affected buildings with around 12600 people potentially affected. 
66
4200 affected buildings with around 12600 people potentially affected. 
            
67
In addition, approximately 80 km of roads with 5 bridges were 
67
In addition, approximately 80 km of roads with 5 bridges were 
            
68
affected. \r\n\r\nThis is a preliminary analysis and has not yet been 
68
affected. \r\n\r\nThis is a preliminary analysis and has not yet been 
            
69
validated in the field. Please send ground feedback to the United 
69
validated in the field. Please send ground feedback to the United 
            
70
Nations Satellite Centre (UNOSAT).",
70
Nations Satellite Centre (UNOSAT).",
            
71
  "notes_translated": {
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  "notes_translated": {
            
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    "en": "This dataset illustrates satellite-detected mudflow extent 
72
    "en": "This dataset illustrates satellite-detected mudflow extent 
            
73
in Sao Vicente, Cabo Verde as observed from Pleiades very 
73
in Sao Vicente, Cabo Verde as observed from Pleiades very 
            
74
high-resolution satellite image. About 12 km\u00b2 of land appears to 
74
high-resolution satellite image. About 12 km\u00b2 of land appears to 
            
75
be affected by the flood / mudflow extent. UNOSAT identified around 
75
be affected by the flood / mudflow extent. UNOSAT identified around 
            
76
4200 affected buildings with around 12600 people potentially affected. 
76
4200 affected buildings with around 12600 people potentially affected. 
            
77
In addition, approximately 80 km of roads with 5 bridges were 
77
In addition, approximately 80 km of roads with 5 bridges were 
            
78
affected. \r\n\r\nThis is a preliminary analysis and has not yet been 
78
affected. \r\n\r\nThis is a preliminary analysis and has not yet been 
            
79
validated in the field. Please send ground feedback to the United 
79
validated in the field. Please send ground feedback to the United 
            
80
Nations Satellite Centre (UNOSAT).",
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Nations Satellite Centre (UNOSAT).",
            
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2025-08-20T12:12:09.554784",
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    "created": "2025-08-20T12:12:09.554784",
            
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    "description": "###The United Nations Satellite Centre (UNOSAT), 
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    "description": "###The United Nations Satellite Centre (UNOSAT), 
            
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part of UNITAR, delivers satellite analysis, training, and capacity 
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part of UNITAR, delivers satellite analysis, training, and capacity 
            
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development to UN entities and Member States. We leverage geospatial 
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development to UN entities and Member States. We leverage geospatial 
            
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technologies to support humanitarian response, sustainable 
92
technologies to support humanitarian response, sustainable 
            
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development, and resilience building worldwide.\r\n\r\n# About 
93
development, and resilience building worldwide.\r\n\r\n# About 
            
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UNOSAT\r\nThe increase in the occurrences of disasters and the high 
94
UNOSAT\r\nThe increase in the occurrences of disasters and the high 
            
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numbers of victims of conflicts are urgent issues that require 
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numbers of victims of conflicts are urgent issues that require 
            
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effective and rapid action. Satellite imagery analysis can cover large 
96
effective and rapid action. Satellite imagery analysis can cover large 
            
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areas and provide accurate information in near real-time. The ability 
97
areas and provide accurate information in near real-time. The ability 
            
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of national and regional authorities to seamlessly collect, integrate, 
98
of national and regional authorities to seamlessly collect, integrate, 
            
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analyze geospatial information in a comprehensible and easy-to-use 
99
analyze geospatial information in a comprehensible and easy-to-use 
            
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format is key to strengthening disaster and climate resilience, 
100
format is key to strengthening disaster and climate resilience, 
            
101
supporting humanitarian action, and supporting sustainable development 
101
supporting humanitarian action, and supporting sustainable development 
            
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policies. The United Nations Satellite Centre (UNOSAT) promotes 
102
policies. The United Nations Satellite Centre (UNOSAT) promotes 
            
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evidence-based decision-making for peace, security, and resilience 
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evidence-based decision-making for peace, security, and resilience 
            
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using geo-spatial information technologies.\r\n\r\n#MANDATE\r\nUNOSAT 
104
using geo-spatial information technologies.\r\n\r\n#MANDATE\r\nUNOSAT 
            
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is the United Nations Satellite Centre, it is part of the United 
105
is the United Nations Satellite Centre, it is part of the United 
            
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Nations Institute for Training and Research (UNITAR), with a mandate 
106
Nations Institute for Training and Research (UNITAR), with a mandate 
            
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to provide United Nations funds, programmes and specialized agencies 
107
to provide United Nations funds, programmes and specialized agencies 
            
108
with satellite analysis, training and capacity development, at their 
108
with satellite analysis, training and capacity development, at their 
            
109
request as well as support Member States with satellite imagery 
109
request as well as support Member States with satellite imagery 
            
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analysis over their respective territories and provide training and 
110
analysis over their respective territories and provide training and 
            
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capacity development in the use of geospatial information 
111
capacity development in the use of geospatial information 
            
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technologies.",
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technologies.",
            
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      "description": "This map illustrates satellite-detected mudflow 
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      "description": "This map illustrates satellite-detected mudflow 
            
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extent in Sao Vicente Municipality, Cabo Verde as observed from 
156
extent in Sao Vicente Municipality, Cabo Verde as observed from 
            
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Pleiades very high-resolution satellite image. ",
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Pleiades very high-resolution satellite image. ",
            
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      "modified": "2025-08-28",
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      "modified": "2025-08-28",
            
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      "name": "Flood Extent - Sao Vicente (13-16 August 2025)",
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      "name": "Flood Extent - Sao Vicente (13-16 August 2025)",
            
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      "url": 
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area affected by the flood and mudflow. About 12 km\u00b2 of land 
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area affected by the flood and mudflow. About 12 km\u00b2 of land 
            
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appears to be affected by the flood / mudflow extent. UNOSAT 
188
appears to be affected by the flood / mudflow extent. UNOSAT 
            
189
identified around 4200 affected buildings with around 12600 people 
189
identified around 4200 affected buildings with around 12600 people 
            
190
potentially affected. In addition, approximately 80 km of roads with 5 
190
potentially affected. In addition, approximately 80 km of roads with 5 
            
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      "url": 
            
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Heitage Sites  affected roads in the area affected by the floods and 
221
Heitage Sites  affected roads in the area affected by the floods and 
            
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mud-flow. Within the analyzed area of approximately 2 km\u00b2, about 
222
mud-flow. Within the analyzed area of approximately 2 km\u00b2, about 
            
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0.3 km\u00b2 of land appears to be affected by flood. UNOSAT 
223
0.3 km\u00b2 of land appears to be affected by flood. UNOSAT 
            
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identified around 300 damaged buildings and approximately 1 km of 
224
identified around 300 damaged buildings and approximately 1 km of 
            
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area affected by the flood and mudflow. About 12 km\u00b2 of land 
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area affected by the flood and mudflow. About 12 km\u00b2 of land 
            
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appears to be affected by the flood / mudflow extent. UNOSAT 
257
appears to be affected by the flood / mudflow extent. UNOSAT 
            
258
identified around 4200 affected buildings with around 12600 people 
258
identified around 4200 affected buildings with around 12600 people 
            
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potentially affected. In addition, approximately 80 km of roads with 5 
259
potentially affected. In addition, approximately 80 km of roads with 5 
            
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August 2025)",
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