Merge pull request #59 from openearth/WP5_pop_stats

Sprint #1 | Population Projections (incl. stats) in STAC

current/CFHP_LAU_stats/collection.json

@@ -1052,7 +1052,7 @@
   ],
   "providers": [
     {
-      "name": "Universidad de Cantabria, Instituto de Hidráulica Ambiental de la Universidad de Cantabria 'IHCantabria'",
+      "name": "Universidad de Cantabria, Instituto de Hidr\u00c3\u00a1ulica Ambiental de la Universidad de Cantabria 'IHCantabria'",
       "roles": [
         "producer",
         "licensor"

current/catalog.json

@@ -94,12 +94,6 @@
       "type": "application/json",
       "title": "Global Coastal Transect Repository (GCTR)"
     },
-    {
-      "rel": "child",
-      "href": "./pp/collection.json",
-      "type": "application/json",
-      "title": "Population Projections"
-    },
     {
       "rel": "child",
       "href": "./ceed/collection.json",
@@ -208,6 +202,12 @@
       "type": "application/json",
       "title": "Cost-benefit analysis of coastal adaptation per floodplain"
     },
+    {
+      "rel": "child",
+      "href": "./pp/collection.json",
+      "type": "application/json",
+      "title": "Population Projections"
+    },
     {
       "rel": "child",
       "href": "./LAU_CM/collection.json",
@@ -225,6 +225,12 @@
       "href": "./NUTS2_CM/collection.json",
       "type": "application/json",
       "title": "Coastal NUTS2"
+    },
+    {
+      "rel": "child",
+      "href": "./pp_stats/collection.json",
+      "type": "application/json",
+      "title": "Population exposed to flooding per LAU"
     }
   ],
   "assets": {

current/cbca/collection.json

@@ -2,7 +2,7 @@
   "type": "Collection",
   "id": "cbca",
   "stac_version": "1.0.0",
-  "description": "Dataset describing the costs and benefits of raising coastal defenses along the European coastline aggregated per coastal NUTS2 region (provinces), in view of climate change. Variables are cost (€), benefit (€), cost-benefit ratio (cbr, -) and extra benefit of raising coastal protection (eb, m) for two different climate scenarios (RCP4.5 and RCP8.5) coupled to two types of socio-economic growth (SSP1 – sustainability and SSP5 – fossil fuel development). This dataset is part of the [LISCOAST](https://data.jrc.ec.europa.eu/collection/LISCOAST) project. See this [article](https://doi.org/10.1038/s41467-020-15665-3) for more dataset-specific information.",
+  "description": "Dataset describing the costs and benefits of raising coastal defenses along the European coastline aggregated per coastal NUTS2 region (provinces), in view of climate change. Variables are cost (\u20ac), benefit (\u20ac), cost-benefit ratio (cbr, -) and extra benefit of raising coastal protection (eb, m) for two different climate scenarios (RCP4.5 and RCP8.5) coupled to two types of socio-economic growth (SSP1 \u2013 sustainability and SSP5 \u2013 fossil fuel development). This dataset is part of the [LISCOAST](https://data.jrc.ec.europa.eu/collection/LISCOAST) project. See this [article](https://doi.org/10.1038/s41467-020-15665-3) for more dataset-specific information.",
   "links": [
     {
       "rel": "item",

current/cfhp/collection.json

@@ -486,7 +486,7 @@
       "url": "https://deltares.nl"
     },
     {
-      "name": "Universidad de Cantabria, Instituto de Hidráulica Ambiental de la Universidad de Cantabria 'IHCantabria'",
+      "name": "Universidad de Cantabria, Instituto de Hidr\u00e1ulica Ambiental de la Universidad de Cantabria 'IHCantabria'",
       "roles": [
         "producer"
       ],

current/cfr/collection.json

@@ -300,7 +300,7 @@
       "attrs": {
         "End_date": "2099-12-31",
         "Starting_date": "1980-12-31",
-        "contents": "Ensemble median Expected Annual Damage (expressed in billion €) from coastal flooding per country",
+        "contents": "Ensemble median Expected Annual Damage (expressed in billion \u20ac) from coastal flooding per country",
         "long_name": "expected annual damage",
         "units": "1e12"
       },

current/cisi/collection.json

@@ -2,7 +2,7 @@
   "type": "Collection",
   "id": "cisi",
   "stac_version": "1.0.0",
-  "description": "Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10.",
+  "description": "Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world\u2019s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10\u2009\u00d7\u20090.10.",
   "links": [
     {
       "rel": "item",

current/deltares-delta-dtm/collection.json

@@ -36611,12 +36611,12 @@
       }
     }
   },
-  "sci:citation": "Pronk, Maarten. 2024. “DeltaDTM v1.1: A Global Coastal Digital Terrain Model.” 4TU.ResearchData. https://doi.org/10.4121/21997565.V3.",
+  "sci:citation": "Pronk, Maarten. 2024. \u201cDeltaDTM v1.1: A Global Coastal Digital Terrain Model.\u201d 4TU.ResearchData. https://doi.org/10.4121/21997565.V3.",
   "sci:doi": "10.4121/21997565",
   "sci:publications": [
     {
       "doi": "10.1038/s41597-024-03091-9",
-      "citation": "Pronk, Maarten, Aljosja Hooijer, Dirk Eilander, Arjen Haag, Tjalling de Jong, Michalis Vousdoukas, Ronald Vernimmen, Hugo Ledoux, and Marieke Eleveld. 2024. “DeltaDTM: A Global Coastal Digital Terrain Model.” Scientific Data 11 (1): 273. https://doi.org/10.1038/s41597-024-03091-9."
+      "citation": "Pronk, Maarten, Aljosja Hooijer, Dirk Eilander, Arjen Haag, Tjalling de Jong, Michalis Vousdoukas, Ronald Vernimmen, Hugo Ledoux, and Marieke Eleveld. 2024. \u201cDeltaDTM: A Global Coastal Digital Terrain Model.\u201d Scientific Data 11 (1): 273. https://doi.org/10.1038/s41597-024-03091-9."
     }
   ],
   "version": "1.1",