Update ga_ls8cls9c_gm #1184
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| [ | ||
| {'v3.1.0': 'projects/geoscience-aus-cat/assets/ga_ls8c_nbart_gm_cyear_3'}, | ||
| {'v4.0.0': 'projects/geoscience-aus-cat/assets/ga_ls8cls9c_gm_cyear_3'}, | ||
| ] | ||
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| local id = 'projects/geoscience-aus-cat/assets/ga_ls8cls9c_gm_cyear_3'; | ||
| local subdir = 'geoscience-aus-cat'; | ||
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| local ee_const = import 'earthengine_const.libsonnet'; | ||
| local ee = import 'earthengine.libsonnet'; | ||
| local spdx = import 'spdx.libsonnet'; | ||
| local units = import 'units.libsonnet'; | ||
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| local license = spdx.cc_by_4_0; | ||
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| local versions = import 'versions.libsonnet'; | ||
| local version_table = import 'projects_geoscience-aus-cat_assets_ga_ls8c_nbart_gm_change_versions.libsonnet'; | ||
| local version_config = versions(subdir, version_table, id); | ||
| local version = version_config.version; | ||
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| local basename = std.strReplace(id, '/', '_'); | ||
| local base_filename = basename + '.json'; | ||
| local self_ee_catalog_url = ee_const.ee_catalog_url + basename; | ||
| local catalog_subdir_url = ee_const.catalog_base + subdir + '/'; | ||
| local parent_url = catalog_subdir_url + 'catalog.json'; | ||
| local self_url = catalog_subdir_url + base_filename; | ||
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| { | ||
| stac_version: ee_const.stac_version, | ||
| type: ee_const.stac_type.collection, | ||
| stac_extensions: [ | ||
| ee_const.ext_eo, | ||
| ee_const.ext_sci, | ||
| ee_const.ext_ver, | ||
| ], | ||
| id: id, | ||
| version: version, | ||
| title: 'DEA Geometric Median and Median Absolute Deviation - Landsat 8 and 9 ' + version, | ||
| 'gee:type': ee_const.gee_type.image_collection, | ||
| description: ||| | ||
| This product provides statistical tools to exploit the time series of Landsat 8 and 9 data available in Digital Earth Australia, providing annual images of general conditions and how much an area changes for a given year. For calendar years 2022 onwards, Landsat 8 and 9 are combined to offer improved performance than the standalone Landsat 8, due to using a larger number of observations. | ||
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| The geometric median part of the product provides an "average" cloud-free image over the given year. The geometric median image is calculated with a multi-dimensional median, using all the spectral measurements from the satellite imagery at the same time in order to maintain the relationships among the measurements. | ||
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| The median absolute deviation part of the product uses three measures of variance, each of which provides a "second order" high dimensional statistical composite for the given year. The three variance measures show how much an area varies from the "average" in terms of "distance" based on factors such as brightness and spectra: | ||
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| * Euclidean distance (EMAD) | ||
| * Cosine (spectral) distance (SMAD) | ||
| * Bray Curtis dissimilarity (BCMAD) | ||
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| Together, they provide information on variance in the landscape over the given year and are useful for change detection applications. | ||
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| For more information, please see the [DEA Geometric Median and Median Absolute Deviation Landsat](https://knowledge.dea.ga.gov.au/data/product/dea-geometric-median-and-median-absolute-deviation-landsat/) | ||
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| More information on what has changed between the versions can be found in the [changelog](https://knowledge.dea.ga.gov.au/data/product/dea-geometric-median-and-median-absolute-deviation-landsat/?tab=history#v4.0.0) | ||
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| This product is part of the [Digital Earth Australia Program](https://www.dea.ga.gov.au/) | ||
| |||, | ||
| license: license.id, | ||
| links: ee.standardLinks(subdir, id) + [ | ||
| ee.link.license(license.reference), | ||
| { | ||
| rel: ee_const.rel.cite_as, | ||
| href: 'https://doi.org/10.1109/TGRS.2017.2723896', | ||
| type: ee_const.media_type.html, | ||
| }, | ||
| { | ||
| rel: ee_const.rel.cite_as, | ||
| href: 'https://doi.org/10.1109/IGARSS.2018.8518312', | ||
| type: ee_const.media_type.html, | ||
| }, | ||
| { | ||
| rel: ee_const.rel.source, | ||
| href: 'https://data.dea.ga.gov.au/?prefix=derivative/ga_ls8cls9c_gm_cyear_3/', | ||
| }, | ||
| ], | ||
| keywords: [ | ||
| 'australia', | ||
| 'ga', | ||
| 'landsat_derived', | ||
| ], | ||
| providers: [ | ||
| ee.producer_provider( | ||
| 'Geoscience Australia', | ||
| 'https://knowledge.dea.ga.gov.au/data/product/dea-geometric-median-and-median-absolute-deviation-landsat/'), | ||
| ee.processor_provider('NGIS', 'https://ngis.com.au/'), | ||
| ee.host_provider(self_ee_catalog_url), | ||
| ], | ||
| extent: ee.extent( | ||
| 108.81, -44.41, 157.82, -9.13, | ||
| '2013-01-01T00:00:00Z', null), | ||
| summaries: { | ||
| gsd: [25], | ||
| 'eo:bands': [ | ||
| { | ||
| name: 'nbart_blue', | ||
| description: ||| | ||
| Band blue surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '0.452-0.512 μm', | ||
| }, | ||
| { | ||
| name: 'nbart_green', | ||
| description: ||| | ||
| Band green surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '0.533-0.590 μm', | ||
| }, | ||
| { | ||
| name: 'nbart_red', | ||
| description: ||| | ||
| Band red surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '0.636-0.673 μm', | ||
| }, | ||
| { | ||
| name: 'nbart_nir', | ||
| description: ||| | ||
| Band near infrared surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '0.851-0.879 μm', | ||
| }, | ||
| { | ||
| name: 'nbart_swir_1', | ||
| description: ||| | ||
| Band shortwave infrared 1 surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '1.566-1.651 μm', | ||
| }, | ||
| { | ||
| name: 'nbart_swir_2', | ||
| description: ||| | ||
| Band shortwave infrared 2 surface reflectance geometric median. | ||
| |||, | ||
| 'gee:wavelength': '2.107-2.294 μm', | ||
| }, | ||
| { | ||
| name: 'edev', | ||
| description: ||| | ||
| The Median Absolute Deviation using Euclidean distance (EMAD). EMAD is more sensitive to changes in target brightness. | ||
| |||, | ||
| }, | ||
| { | ||
| name: 'sdev', | ||
| description: ||| | ||
| The Median Absolute Deviation using Cosine (spectral) distance (SMAD). SMAD is more sensitive to change in target spectral response. | ||
| |||, | ||
| }, | ||
| { | ||
| name: 'bcdev', | ||
| description: ||| | ||
| The Median Absolute Deviation using Bray Curtis dissimilarity (BCMAD). BCMAD is more sensitive to the distribution of the observation values through time. | ||
| |||, | ||
| }, | ||
| { | ||
| name: 'count', | ||
| description: ||| | ||
| The number of the available pixels used for calculation per calendar year. | ||
| |||, | ||
| }, | ||
| ], | ||
| nbart_blue: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| nbart_green: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| nbart_red: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| nbart_nir: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| nbart_swir_1: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| nbart_swir_2: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| edev: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| sdev: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| bcdev: {minimum: 0, maximum: 10000, 'gee:estimated_range': true}, | ||
| count: {minimum: 0, maximum: 400, 'gee:estimated_range': true}, | ||
| 'gee:visualizations': [ | ||
| { | ||
| display_name: 'Geomedians', | ||
| lookat: {lon: 133.88, lat: -23.70, zoom: 5}, | ||
| image_visualization: { | ||
| band_vis: { | ||
| min: [0], | ||
| max: [255], | ||
| bands: ['nbart_red', 'nbart_green', 'nbart_blue'], | ||
| } | ||
| }, | ||
| }, | ||
| ], | ||
| }, | ||
| 'sci:doi': '10.1109/TGRS.2017.2723896', | ||
| 'sci:citation': ||| | ||
| Roberts, D., Mueller, N., & Mcintyre, A. (2017). High-dimensional pixel composites from earth observation time series. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6254-6264. | ||
| [doi:10.1109/TGRS.2017.2723896](https://doi.org/10.1109/TGRS.2017.2723896). | ||
| Roberts, D., Dunn, B., & Mueller, N. (2018). Open data cube products using high-dimensional statistics of time series. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 8647-8650. | ||
| [doi:10.1109/IGARSS.2018.8518312](https://doi.org/10.1109/IGARSS.2018.8518312). | ||
| |||, | ||
| 'gee:terms_of_use': ee.gee_terms_of_use(license), | ||
| } |
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| @@ -0,0 +1,27 @@ | ||
| var geomedian_ls8ls9 = ee.ImageCollection('projects/geoscience-aus-cat/assets/ga_ls8cls9c_gm_cyear_3'); | ||
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There was a problem hiding this comment. could you please make the collection publicly readable? There was a problem hiding this comment. |
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| var geometry = | ||
| /* color: #98ff00 */ | ||
| /* displayProperties: [ | ||
| { | ||
| "type": "rectangle" | ||
| } | ||
| ] */ | ||
| ee.Geometry.Polygon( | ||
| [[[121.15880998755823, -15.010654451073695], | ||
| [121.15880998755823, -18.377531570740548], | ||
| [125.81701311255823, -18.377531570740548], | ||
| [125.81701311255823, -15.010654451073695]]], null, false); | ||
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| var composite = geomedian_ls8ls9.filterBounds(geometry) | ||
| .filterDate('2018-01-01', '2019-01-01') | ||
| .mosaic(); | ||
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| var visualization = { | ||
| bands: ['nbart_red', 'nbart_green', 'nbart_blue'], | ||
| min: 0, | ||
| max: 3000 | ||
| }; | ||
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| Map.centerObject(geometry, 10); | ||
| Map.addLayer(composite, visualization, '2018 True Color Composite'); | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,39 @@ | ||
| var geomedian_ls8ls9 = ee.ImageCollection('projects/geoscience-aus-cat/assets/ga_ls8cls9c_gm_cyear_3'); | ||
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| var geometry = | ||
| /* color: #98ff00 */ | ||
| /* displayProperties: [ | ||
| { | ||
| "type": "rectangle" | ||
| } | ||
| ] */ | ||
| ee.Geometry.Polygon( | ||
| [[[121.15880998755823, -15.010654451073695], | ||
| [121.15880998755823, -18.377531570740548], | ||
| [125.81701311255823, -18.377531570740548], | ||
| [125.81701311255823, -15.010654451073695]]], null, false); | ||
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| // Width and height of the thumbnail image. | ||
| var pixels = 256; | ||
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| var composite = geomedian_ls8ls9.filterBounds(geometry) | ||
| .filterDate('2018-01-01', '2019-01-01') | ||
| .mosaic(); | ||
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| var visualization = { | ||
| bands: ['nbart_red', 'nbart_green', 'nbart_blue'], | ||
| min: 0, | ||
| max: 3000 | ||
| }; | ||
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| Map.centerObject(geometry, 10); | ||
| Map.addLayer(composite, visualization, '2018 True Color Composite'); | ||
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| var imageParams = { | ||
| dimensions: [pixels, pixels], | ||
| region: geometry, | ||
| crs: 'EPSG:3857', | ||
| format: 'png', | ||
| }; | ||
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| print(ui.Thumbnail({image: composite.visualize(visualization), params: imageParams})); | ||
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There was a problem hiding this comment. This thumbnail is partially masked out, so it won't look like a neat square. Could you either shift it to an area that's not fully masked out or use gray background like in https://github.com/google/earthengine-catalog/blob/main/examples/WM/WM_geoLab_geoBoundaries_600_ADM0_preview.js#L21 ? There was a problem hiding this comment. I changed the thumbnail area, now it should show a neat square. |
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To apply this file to dataset descriptions (to create links between them and to display a warning on the old dataset's page), you should import it into both old and new .jsonnet files. Example: https://github.com/google/earthengine-catalog/blob/main/catalog/UMD/UMD_hansen_global_forest_change_2023_v1_11.jsonnet
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Thanks Simon, I updated both the old and new .jsonnet files.
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Could you also add "version_config.version_links" to the links section in both files? See https://github.com/google/earthengine-catalog/blob/main/catalog/UMD/UMD_hansen_global_forest_change_2023_v1_11.jsonnet#L45
This is the command that will create predecessor/successor links. The checks will also ask you to add "deprecated: true" to the old dataset, as it will now have a successor.
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version_config.version_linkswas added to both files.'gee:status': 'deprecated'and[deprecated]were added to the old dataset file.