Merge pull request #1227 from leandroleal:main

PiperOrigin-RevId: 703517436

catalog/catalog.jsonnet

@@ -126,5 +126,6 @@ local self_url = base_url + base_filename;
     ee.link.child_catalog('ngis-cat', base_url),
     ee.link.child_catalog('planet-nicfi', base_url),
     ee.link.child_catalog('sat-io', base_url),
+    ee.link.child_catalog('global-pasture-watch', base_url),
   ],
 }

catalog/global-pasture-watch/catalog.jsonnet

@@ -0,0 +1,28 @@
+local id = 'global-pasture-watch';
+local subdir = id;
+
+local description = importstr 'description.md';
+local ee_const = import 'earthengine_const.libsonnet';
+local ee = import 'earthengine.libsonnet';
+
+local basename = 'catalog';
+local base_filename = basename + '.json';
+local base_url = ee_const.catalog_base + subdir + '/';
+local parent_url = ee_const.catalog_base + 'catalog.json';
+local self_url = base_url + base_filename;
+
+{
+  stac_version: ee_const.stac_version,
+  type: ee_const.stac_type.catalog,
+  id: id,
+  title: id,
+  description: description,
+  links: [
+    ee.link.root(),
+    ee.link.parent(parent_url),
+    ee.link.self_link(self_url),
+    ee.link.child_collection('projects_global-pasture-watch_assets_ggc-30m_v1_grassland_c', base_url),
+    ee.link.child_collection('projects_global-pasture-watch_assets_ggc-30m_v1_cultiv-grassland_p', base_url),
+    ee.link.child_collection('projects_global-pasture-watch_assets_ggc-30m_v1_nat-semi-grassland_p', base_url),
+  ],
+}

catalog/global-pasture-watch/description.md

@@ -0,0 +1 @@
+The Land & Carbon Lab, convened by the World Resources Institute (WRI) and the Bezos Earth Fund, established the Global Pasture Watch research consortium. The consortium, which is made up of experts in geospatial monitoring, machine learning, ecology and agriculture across some of the world's leading research institutions, is developing global products for grasslands and livestock grazing in the 21st century.

catalog/global-pasture-watch/ggc-30m_v1.md

@@ -0,0 +1,56 @@
+Produced by Land &
+Carbon Lab Global Pasture Watch initiative, the mapped grassland extent
+includes any land cover type, which contains at least 30% of dry or wet
+low vegetation, dominated by grasses and forbs (less than 3 meters) 
+and a:
+
+- maximum of 50% tree canopy cover (greater than 5 meters),
+- maximum of 70% of other woody vegetation (scrubs and open shrubland), and
+- maximum of 50% active cropland cover in mosaic landscapes of cropland
+ & other vegetation.
+
+The grassland extent is classified into two classes:
+- **Cultivated grassland**: Areas where grasses and other forage plants have
+been intentionally planted and managed, as well as areas of native 
+grassland-type vegetation where they clearly exhibit active and
+heavy management for specific human-directed uses, such as directed
+grazing of livestock.
+- **Natural/Semi-natural grassland**: Relatively undisturbed native
+grasslands/short-height vegetation, such as steppes and tundra, 
+as well as areas that have experienced varying degrees of human 
+activity in the past, which may contain a mix of native and 
+introduced species due to historical land use and natural processes. 
+In general, they exhibit natural-looking patterns of varied vegetation 
+and clearly ordered hydrological relationships throughout the landscape.
+
+The implemented methodology considered [GLAD Landsat ARD-2 images 
+](https://glad.umd.edu/ard) (processed into cloud-free bi-monthly 
+aggregates, see [Consoli et al, 2024](https://doi.org/10.7717/peerj.18585)
+), accompanied by climatic, landform and proximity covariates, 
+spatiotemporal machine learning (per-class Random Forest) and over 
+2.3 million reference samples (visually interpreted in Very High 
+Resolution imagery). Custom probability thresholds (based on five-fold 
+spatial cross-validation and balanced precision and recall values) 
+were used to derive dominant class maps, 0.32 and 0.42 for 
+cultivated and natural/semi-natural grassland probability thresholds, respectively.
+
+**Limitations:** Grassland extent is partly under-predicted in southeastern
+Africa (Zimbabwe and Mozambique) and in eastern Australia (shrublands and
+woodlands of the Mulga ecoregion). Cropland is misclassified as grassland
+in parts of northern Africa, the Arabian Peninsula, Western Australia, 
+New Zealand, the center of Bolivia, and Mato Grosso state (Brazil). Due 
+to the Landsat 7 SLC failure, regular stripes of grassland probabilities 
+are visible at parcel-level, particularly in the year 2012. The usage of 
+coarser resolution layers (accessibility maps and MODIS products) 
+introduced curvilinear macroscopic errors (due to the downscaling 
+strategy based on cubicspline) in Uruguay, Southwest Argentina, South 
+of Angola and in the Sahel region in Africa. Users need to be aware 
+of the limitations and known issues; whilst considering them 
+carefully to ensure appropriate use of maps at this initial prediction 
+stage. GPW is working actively to collect systematic feedback [Geo-Wiki 
+platform](https://www.geo-wiki.org), validate the current version 
+and improve future versions of the dataset.
+
+**For more information see [Parente et. al, 2024](http://doi.org/10.1038/s41597-024-04139-6),
+[Zenodo](https://zenodo.org/records/13890401) and 
+[https://github.com/wri/global-pasture-watch](https://github.com/wri/global-pasture-watch)**

catalog/global-pasture-watch/projects_global-pasture-watch_assets_ggc-30m_v1_cultiv-grassland_p.jsonnet

@@ -0,0 +1,111 @@
+local id = 'projects/global-pasture-watch/assets/ggc-30m/v1/cultiv-grassland_p';
+local subdir = 'global-pasture-watch';
+local version = '1';
+
+local ee_const = import 'earthengine_const.libsonnet';
+local ee = import 'earthengine.libsonnet';
+local spdx = import 'spdx.libsonnet';
+local units = import 'units.libsonnet';
+local ggc30m_v1 = importstr 'ggc-30m_v1.md';
+local license = spdx.cc_by_4_0;
+
+local basename = std.strReplace(id, '/', '_');
+local self_ee_catalog_url = ee_const.ee_catalog_url + basename;
+
+{
+  id: id,
+  title: 'GPW Annual Probabilities of Cultivated Grasslands v' + version,
+  version: version,
+  description: |||
+    This dataset provides global annual probability maps of cultivated
+    grassland from 2000 to 2022 at 30-m spatial resolution. 
+  ||| + ggc30m_v1,
+  keywords: [
+    'land',
+    'landcover',
+    'landuse',
+    'global',
+    'vegetation'
+  ],
+
+  providers: [
+    ee.producer_provider('Land and Carbon Lab Global Pasture Watch', 'https://landcarbonlab.org/data/global-grassland-and-livestock-monitoring'),
+    ee.host_provider(self_ee_catalog_url),
+  ],
+  extent: ee.extent_global('2000-01-01T00:00:00Z', '2023-01-01T00:00:00Z'),
+  summaries: {
+    'eo:bands': [
+      {
+        name: 'probability',
+        description: 'Cultivated grassland probability value derived through Random Forest.',
+        gsd: 30
+      }
+    ],
+    probability: {minimum: 0, maximum: 100, 'gee:estimated_range': false},
+    'gee:visualizations': [
+      {
+        display_name: 'Cultivated grassland probability value',
+        lookat: {lon: -55.50, lat: -12.20, zoom: 4},
+        image_visualization: {
+          band_vis: {
+            min: [0],
+            max: [100],
+            palette: [
+              'f5f5f5',
+              'fdaf27',
+              'ae7947',
+              '3a2200'
+            ],
+            bands: ['probability'],
+          }
+        },
+      }
+    ],
+    'gee:schema': [
+      {
+        name: 'version',
+        description: 'Product version',
+        type: ee_const.var_type.int
+      },
+    ],
+  },
+
+  'gee:interval': {
+    type: 'cadence',
+    unit: 'year',
+    interval: 1,
+  },
+
+  'sci:doi': '10.5281/zenodo.13890401',
+  'sci:citation': |||
+    Parente, L., Sloat, L., Mesquita, V., et al. (2024) 
+    Global Pasture Watch - Annual grassland class and extent 
+    maps at 30-m spatial resolution (2000—2022) (Version v1) 
+    [Data set]. Zenodo
+    [doi:https://doi.org/10.5281/zenodo.13890401](https://doi.org/10.5281/zenodo.13890401)
+  |||,
+  'sci:publications': [
+    {
+      citation: |||
+        Parente, L., Sloat, L., Mesquita, V., et al. (2024).
+        Annual 30-m maps of global grassland class and extent (2000–2022) 
+        based on spatiotemporal Machine Learning, Scientific Data.
+        [doi: http://doi.org/10.1038/s41597-024-04139-6](http://doi.org/10.1038/s41597-024-04139-6)
+      |||,
+      doi: '10.1038/s41597-024-04139-6',
+    }
+  ],
+  'gee:terms_of_use': ee.gee_terms_of_use(license),
+  // TODO(google): Remove gee:status when the dataset is ready.
+  'gee:status': 'beta',
+  'gee:type': ee_const.gee_type.image_collection,
+  license: license.id,
+  links: ee.standardLinks(subdir, id),
+  type: ee_const.stac_type.collection,
+  stac_version: ee_const.stac_version,
+  stac_extensions: [
+    ee_const.ext_eo,
+    ee_const.ext_sci,
+    ee_const.ext_ver,
+  ],
+}

catalog/global-pasture-watch/projects_global-pasture-watch_assets_ggc-30m_v1_grassland_c.jsonnet

@@ -0,0 +1,115 @@
+local id = 'projects/global-pasture-watch/assets/ggc-30m/v1/grassland_c';
+local subdir = 'global-pasture-watch';
+local version = '1';
+
+local ee_const = import 'earthengine_const.libsonnet';
+local ee = import 'earthengine.libsonnet';
+local spdx = import 'spdx.libsonnet';
+local units = import 'units.libsonnet';
+local ggc30m_v1 = importstr 'ggc-30m_v1.md';
+local license = spdx.cc_by_4_0;
+
+local basename = std.strReplace(id, '/', '_');
+local self_ee_catalog_url = ee_const.ee_catalog_url + basename;
+
+{
+  id: id,
+  title: 'GPW Annual Dominant Class of Crasslands v' + version,
+  version: version,
+  description: |||
+    This dataset provides global annual dominant class maps of grasslands 
+    (cultivated and natural/semi-natural) from 2000 to 2022 at 30-m spatial 
+    resolution. 
+  ||| + ggc30m_v1,
+  keywords: [
+    'land',
+    'landcover',
+    'landuse',
+    'global',
+    'vegetation'
+  ],
+
+  providers: [
+    ee.producer_provider('Land and Carbon Lab Global Pasture Watch', 'https://landcarbonlab.org/data/global-grassland-and-livestock-monitoring'),
+    ee.host_provider(self_ee_catalog_url),
+  ],
+  extent: ee.extent_global('2000-01-01T00:00:00Z', '2023-01-01T00:00:00Z'),
+  summaries: {
+    'eo:bands': [
+      {
+        name: 'dominant_class',
+        description: 'Dominant class derived through Random Forest and probability maps.',
+        gsd: 30,
+        'gee:classes': [
+          {value: 0, color: 'ffffff', description: 'Other'},
+          {value: 1, color: 'ff9916', description: 'Cultivated grassland '},
+          {value: 2, color: 'ffcd73', description: 'Natural/Semi-natural grassland'},
+        ],
+      }
+    ],
+    dominant_class: {minimum: 0, maximum: 2, 'gee:estimated_range': false},
+    'gee:visualizations': [
+      {
+        display_name: 'Dominant grassland class',
+        lookat: {lon: -55.50, lat: -12.20, zoom: 4},
+        image_visualization: {
+          band_vis: {
+            min: [0],
+            max: [2],
+            palette: [
+              'ffffff',
+              'ff9916',
+              'ffcd73'
+            ],
+            bands: ['dominant_class'],
+          }
+        },
+      }
+    ],
+    'gee:schema': [
+      {
+        name: 'version',
+        description: 'Product version',
+        type: ee_const.var_type.int
+      },
+    ],
+  },
+  'gee:interval': {
+    type: 'cadence',
+    unit: 'year',
+    interval: 1,
+  },
+
+  'sci:doi': '10.5281/zenodo.13890401',
+  'sci:citation': |||
+    Parente, L., Sloat, L., Mesquita, V., et al. (2024) 
+    Global Pasture Watch - Annual grassland class and extent 
+    maps at 30-m spatial resolution (2000—2022) (Version v1) 
+    [Data set]. Zenodo
+    [doi:https://doi.org/10.5281/zenodo.13890401](https://doi.org/10.5281/zenodo.13890401)
+  |||,
+  'sci:publications': [
+    {
+      citation: |||
+        Parente, L., Sloat, L., Mesquita, V., et al. (2024).
+        Annual 30-m maps of global grassland class and extent (2000–2022) 
+        based on spatiotemporal Machine Learning, Scientific Data.
+        [doi: http://doi.org/10.1038/s41597-024-04139-6](http://doi.org/10.1038/s41597-024-04139-6)
+      |||,
+      doi: '10.1038/s41597-024-04139-6',
+    }
+  ],
+  'gee:terms_of_use': ee.gee_terms_of_use(license),
+  // TODO(google): Remove gee:status when the dataset is ready.
+  'gee:status': 'beta',
+  'gee:type': ee_const.gee_type.image_collection,
+  license: license.id,
+  links: ee.standardLinks(subdir, id),
+  type: ee_const.stac_type.collection,
+  stac_version: ee_const.stac_version,
+  stac_extensions: [
+    ee_const.ext_eo,
+    ee_const.ext_sci,
+    ee_const.ext_ver,
+  ],
+}