Dataset description for CCDC v4.

catalog/GOOGLE/GOOGLE_GLOBAL_CCDC_V4.jsonnet

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+local id = 'GOOGLE/GLOBAL_CCDC/V4';
+local subdir = 'GOOGLE';
+
+local ee_const = import 'earthengine_const.libsonnet';
+local ee = import 'earthengine.libsonnet';
+local spdx = import 'spdx.libsonnet';
+
+local license = spdx.cc_by_4_0;
+
+local basename = std.strReplace(id, '/', '_');
+local base_filename = basename + '.json';
+local self_ee_catalog_url = ee_const.ee_catalog_url + basename;
+
+{
+  'gee:user_uploaded': true,
+  stac_version: ee_const.stac_version,
+  type: ee_const.stac_type.collection,
+  stac_extensions: [
+    ee_const.ext_eo,
+    ee_const.ext_ver,
+  ],
+  id: id,
+  title: 'Google Global Landsat-based CCDC Segments (1984-2024)',
+  version: 'V4',
+  'gee:type': ee_const.gee_type.image_collection,
+  description: |||
+    This collection contains precomputed results from running the
+    Continuous Change Detection and Classification (CCDC) algorithm on
+    40 years of Landsat surface reflectance data. CCDC is a break-point
+    finding algorithm that uses harmonic fitting with a dynamic RMSE
+    threshold to detect breakpoints in time-series data.
+
+    The dataset was created from the Landsat 4, 5, 7, and 8 Collection-1, Tier-1,
+    surface reflectance time series, using all daytime images between 1984-01-01
+    and 2024-12-31. Each image was preprocessed to mask pixels identified as
+    cloud, shadow, or snow (according to the 'pixel_qa' band), saturated pixels,
+    and pixels with an atmospheric opacity > 300 (as identified by the
+    'sr_atmos_opacity' and 'sr_aerosol' bands). Pixels repeated in
+    north/south scene overlap were deduplicated. The results were
+    output in 2-degree tiles for all landmasses between -60° and +85° latitude.
+    The images are suitable to simply mosaic() into one global image.
+
+    The CCDC algorithm was run with the following algorithm parameters:
+
+    * tmaskBands: ['green', 'swir']
+    * minObservations: 6
+    * chiSquareProbability: 0.99
+    * minNumOfYearsScaler: 1.33
+    * dateFormat: 1 (fractional year)
+    * lambda: 0.002
+    * maxIterations: 10000
+
+    Each pixel in the output is encoded using variable length arrays.  The outer
+    length of each array (axis 0) corresponds to the number of breakpoints
+    found at that location. The coefs bands contain 2-D arrays, where each inner
+    array contains the scaling factors for the 8 terms in the linear harmonic
+    model, in the order: [offset, t, cos(ωt), sin(ωt), cos(2ωt),
+    sin(2ωt), cos(3ωt), sin(3ωt)], where ω = 2Π.  The
+    models are scale to produce refelectance units (0.0 - 1.0) for the optical
+    bands and degrees (K) / 100.0 for the thermal band.
+
+    Note that since the output bands are arrays and can only be downsampled
+    using a SAMPLE pyramiding policy. At lower zoom levels, the
+    results are usually no longer representative of the full-resolution data,
+    and, for instance, tile boundaries can be seen due to the downsampled masks.
+    It's therefore not recommended to use this dataset at resolutions less than
+    240m/pixel.
+
+  |||,
+  license: license.id,
+  links: ee.standardLinks(subdir, id),
+  'gee:categories': ['landuse-landcover'],
+  keywords: [
+    'change_detection',
+    'google',
+    'landcover',
+    'landsat_derived',
+    'landuse',
+  ],
+  providers: [
+    ee.producer_provider('Google', 'https://earthengine.google.com/'),
+    ee.host_provider(self_ee_catalog_url),
+  ],
+  extent: ee.extent(
+    -180, -60, 180, 72, '1999-01-01T00:00:00Z', '2020-01-01T00:00:00Z'),
+  summaries: {
+    gsd: [
+      30,
+    ],
+    'eo:bands': [
+      {
+        name: 'tStart',
+        description: '1-D Array containing the date of the start of each segment (fractional year).',
+      },
+      {
+        name: 'tEnd',
+        description: '1-D Array containing the date of the end of each segment (fractional year).',
+      },
+      {
+        name: 'tBreak',
+        description: '1-D Array containing the date of the detected breakpoint of each segment (fractional year).',
+      },
+      {
+        name: 'numObs',
+        description: '1-D Array containing the number of observations found in each segment.',
+      },
+      {
+        name: 'changeProb',
+        description: 'A pseudo-probability of the detected breakpoint being real.',
+      },
+      {
+        name: 'BLUE_coefs',
+        description: '2-D array containing harmonic model coefficients for the blue band, for each segment.'
+      },
+      {
+        name: 'GREEN_coefs',
+        description: '2-D array containing harmonic model coefficients for the green band, for each segment.'
+      },
+      {
+        name: 'RED_coefs',
+        description: '2-D array containing harmonic model coefficients for the red band, for each segment.'
+      },
+      {
+        name: 'NIR_coefs',
+        description: '2-D array containing harmonic model coefficients for the near-infrared band, for each segment.'
+      },
+      {
+        name: 'SWIR1_coefs',
+        description: '2-D array containing harmonic model coefficients for the shortwave-infrared (1.55μm-1.75μm) band, for each segment.'
+      },
+      {
+        name: 'SWIR2_coefs',
+        description: '2-D array containing harmonic model coefficients for the shortwave-infrared (2.09μm-2.35μm) band, for each segment.'
+      },
+      {
+        name: 'TEMP_coefs',
+        description: '2-D array containing harmonic model coefficients for the thermal band, for each segment.'
+      },
+      {
+        name: 'BLUE_rmse',
+        description: '1-D array containing the RMSE of the model for the blue band, for each segment.'
+      },
+      {
+        name: 'GREEN_rmse',
+        description: '1-D array containing the RMSE of the model for the green band, for each segment.'
+      },
+      {
+        name: 'RED_rmse',
+        description: '1-D array containing the RMSE of the model for the red band, for each segment.'
+      },
+      {
+        name: 'NIR_rmse',
+        description: '1-D array containing the RMSE of the model for the near-infrared band, for each segment.'
+      },
+      {
+        name: 'SWIR1_rmse',
+        description: '1-D array containing the RMSE of the model for the the shortwave-infrared (1.55μm-1.75μm) band, for each segment.'
+      },
+      {
+        name: 'SWIR2_rmse',
+        description: '1-D array containing the RMSE of the model for the shortwave-infrared (2.09μm-2.35μm) band, for each segment.'
+      },
+      {
+        name: 'TEMP_rmse',
+        description: '1-D array containing the RMSE of the model for the thermal band, for each segment.'
+      },
+      {
+        name: 'BLUE_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the blue band, for each segment.'
+      },
+      {
+        name: 'GREEN_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the green band, for each segment.'
+      },
+      {
+        name: 'RED_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the red band, for each segment.'
+      },
+      {
+        name: 'NIR_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the near-infrared band, for each segment.'
+      },
+      {
+        name: 'SWIR1_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the shortwave-infrared-1 (1.55μm-1.75μm) band, for each segment.'
+      },
+      {
+        name: 'SWIR2_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the shortwave-infrared-2 (2.09μm-2.35μm) band, for each segment.'
+      },
+      {
+        name: 'TEMP_magnitude',
+        description: '1-D array containing the magnitude of the detected breakpoint for the thermal band, for each segment.'
+      },
+    ],
+    'gee:visualizations': [
+      {
+        display_name: 'Global CCDC',
+        lookat: {
+          lat: 36,
+          lon: -116,
+          zoom: 10,
+        },
+        image_visualization: {
+          band_vis: {
+            min: [
+              0,
+            ],
+            max: [
+              1,
+            ],
+            bands: [
+              'RED_coefs',
+              'GREEN_coefs',
+              'BLUE_coefs'
+            ],
+          },
+        },
+      },
+    ],
+  },
+  'gee:terms_of_use': ee.gee_terms_of_use(license),
+}

examples/GOOGLE/GOOGLE_GLOBAL_CCDC_V4.js

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+var ccdc = ee.ImageCollection("projects/CCDC/v4");
+var break0 = ccdc.select('tBreak').mosaic().arrayGet(0);
+
+// Point to center
+var lon = -123.296;
+var lat = 43.8246;
+
+Map.setOptions('SATELLITE');
+Map.setCenter(lon, lat, 13);
+Map.addLayer(break0.selfMask(), {min: 1984, max: 2024, palette: 'red,green,blue'}, 'break0');

examples/GOOGLE/GOOGLE_GLOBAL_CCDC_V4_preview.js

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+var ccdc = ee.ImageCollection('projects/CCDC/v4');
+var break0 = ccdc.select('tBreak').mosaic().arrayGet(0);
+
+// Point to center
+var lon = -123.296;
+var lat = 43.8246;
+Map.setCenter(lon, lat, 13);
+
+// Degrees in EPSG:3857
+var delta = 0.043;
+// Width and Height of the Thumbail image.
+var pixels = 256;
+
+var areaOfInterest = ee.Geometry.Rectangle(
+    [lon - delta, lat - delta, lon + delta, lat + delta], null, false);
+
+var parameters = {
+  dimensions: [pixels, pixels],
+  region: areaOfInterest,
+  crs: 'EPSG:3857',
+  format: 'png'
+};
+
+var thumbComposite = break0.selfMask().visualize(
+    {min: 1984, max: 2024, palette: 'red,green,blue'});
+print(ui.Thumbnail({image: thumbComposite, params: parameters}));