Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-11-02 10:53:16	ga_ls9c_ard_3-2-1_106074_2021-11-02_final.stac-item
2021-12-05 10:09:44	ga_ls9c_ard_3-2-1_098083_2021-12-05_final.stac-item
2021-12-17 10:28:44	ga_ls9c_ard_3-2-1_102069_2021-12-17_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-19 10:22:22	ga_ls9c_ard_3-2-1_100084_2021-12-19_final.stac-item
2022-01-05 09:25:33	ga_ls9c_ard_3-2-1_091081_2022-01-04_final.stac-item
2022-01-16 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-01-16_final.stac-item
2022-01-30 09:20:10	ga_ls9c_ard_3-2-1_090083_2022-01-29_final.stac-item
2022-02-19 10:28:14	ga_ls9c_ard_3-2-1_102068_2022-02-19_final.stac-item
2022-03-04 09:57:11	ga_ls9c_ard_3-2-1_097068_2022-03-04_final.stac-item
2022-03-06 09:47:38	ga_ls9c_ard_3-2-1_095075_2022-03-06_final.stac-item
2022-03-19 10:53:35	ga_ls9c_ard_3-2-1_106070_2022-03-19_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-23 10:29:14	ga_ls9c_ard_3-2-1_102071_2022-03-23_final.stac-item
2022-03-26 09:26:25	ga_ls9c_ard_3-2-1_091084_2022-03-25_final.stac-item
2022-04-11 09:28:22	ga_ls9c_ard_3-2-1_091089_2022-04-10_final.stac-item
2022-04-16 11:19:44	ga_ls9c_ard_3-2-1_110074_2022-04-16_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-05-13 11:00:59	ga_ls9c_ard_3-2-1_107074_2022-05-13_final.stac-item
2022-06-12 09:36:25	ga_ls9c_ard_3-2-1_093079_2022-06-12_final.stac-item
2022-06-14 09:25:41	ga_ls9c_ard_3-2-1_091083_2022-06-13_final.stac-item
2022-06-15 10:04:58	ga_ls9c_ard_3-2-1_098073_2022-06-15_final.stac-item
2022-06-23 09:21:19	ga_ls9c_ard_3-2-1_090087_2022-06-22_final.stac-item
2022-06-28 09:36:43	ga_ls9c_ard_3-2-1_093079_2022-06-28_final.stac-item
2022-07-05 09:44:52	ga_ls9c_ard_3-2-1_094084_2022-07-05_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-07-21 11:19:49	ga_ls9c_ard_3-2-1_110074_2022-07-21_final.stac-item
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-26 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-08-25_final.stac-item
2022-09-09 11:09:46	ga_ls9c_ard_3-2-1_108079_2022-09-09_final.stac-item
2022-09-11 10:56:14	ga_ls9c_ard_3-2-1_106076_2022-09-11_final.stac-item
2022-09-12 10:01:49	ga_ls9c_ard_3-2-1_097079_2022-09-12_final.stac-item
2022-09-14 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-09-14_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-25 09:29:01	ga_ls9c_ard_3-2-1_092074_2022-09-24_final.stac-item
2022-10-05 10:08:05	ga_ls9c_ard_3-2-1_098079_2022-10-05_final.stac-item
2022-10-11 11:07:09	ga_ls9c_ard_3-2-1_108072_2022-10-11_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-31 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-10-31_final.stac-item
2022-11-06 10:08:10	ga_ls9c_ard_3-2-1_098079_2022-11-06_final.stac-item
2022-11-10 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-11-10_final.stac-item
2022-12-07 09:22:07	ga_ls9c_ard_3-2-1_091072_2022-12-06_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_final.stac-item
2022-12-23 11:05:45	ga_ls9c_ard_3-2-1_107084_2022-12-23_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2023-01-02 11:38:54	ga_ls9c_ard_3-2-1_113074_2023-01-02_final.stac-item
2023-01-08 11:02:37	ga_ls9c_ard_3-2-1_107076_2023-01-08_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-12 10:21:50	ga_ls9c_ard_3-2-1_100083_2023-03-12_final.stac-item
2023-03-15 09:10:40	ga_ls9c_ard_3-2-1_089075_2023-03-14_final.stac-item
2023-04-22 11:51:27	ga_ls9c_ard_3-2-1_115076_2023-04-22_final.stac-item
2023-05-14 09:39:39	ga_ls9c_ard_3-2-1_093087_2023-05-14_final.stac-item
2023-05-16 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-05-15_final.stac-item
2023-05-31 10:17:58	ga_ls9c_ard_3-2-1_100075_2023-05-31_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-10 10:54:35	ga_ls9c_ard_3-2-1_106074_2023-06-10_final.stac-item
2023-06-18 10:09:03	ga_ls9c_ard_3-2-1_098084_2023-06-18_final.stac-item
2023-06-26 09:20:01	ga_ls9c_ard_3-2-1_090085_2023-06-25_final.stac-item
2023-07-01 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-07-01_final.stac-item
2023-07-03 09:26:22	ga_ls9c_ard_3-2-1_091085_2023-07-02_final.stac-item
2023-07-08 09:40:11	ga_ls9c_ard_3-2-1_094073_2023-07-08_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-15 09:50:24	ga_ls9c_ard_3-2-1_095083_2023-07-15_final.stac-item
2023-07-24 11:19:29	ga_ls9c_ard_3-2-1_110074_2023-07-24_final.stac-item
2023-08-15 10:42:36	ga_ls9c_ard_3-2-1_104074_2023-08-15_final.stac-item
2023-09-05 09:26:03	ga_ls9c_ard_3-2-1_091083_2023-09-04_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-06 11:46:37	ga_ls9c_ard_3-2-1_114079_2023-09-06_final.stac-item
2023-10-13 10:26:05	ga_ls9c_ard_3-2-1_101078_2023-10-13_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-16 10:53:49	ga_ls9c_ard_3-2-1_106070_2023-10-16_final.stac-item
2023-10-22 10:21:56	ga_ls9c_ard_3-2-1_100083_2023-10-22_final.stac-item
2023-10-30 11:07:19	ga_ls9c_ard_3-2-1_108073_2023-10-30_final.stac-item
2023-11-06 09:40:11	ga_ls9c_ard_3-2-1_093087_2023-11-06_final.stac-item
2023-11-11 11:36:02	ga_ls9c_ard_3-2-1_112083_2023-11-11_final.stac-item
2023-11-16 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-11-16_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-24 11:05:39	ga_ls9c_ard_3-2-1_107084_2023-11-24_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_2023-11-25_final.stac-item
2023-12-24 11:13:40	ga_ls9c_ard_3-2-1_109073_2023-12-24_final.stac-item
2023-12-24 11:15:40	ga_ls9c_ard_3-2-1_109078_2023-12-24_final.stac-item
2024-01-05 10:03:47	ga_ls9c_ard_3-2-1_097084_2024-01-05_final.stac-item
2024-01-05 11:37:53	ga_ls9c_ard_3-2-1_113072_2024-01-05_final.stac-item
2024-01-16 11:20:35	ga_ls9c_ard_3-2-1_110075_2024-01-16_final.stac-item
2024-01-26 11:58:49	ga_ls9c_ard_3-2-1_116078_2024-01-26_final.stac-item
2024-02-10 09:38:44	ga_ls9c_ard_3-2-1_093083_2024-02-10_final.stac-item
2024-02-12 09:27:09	ga_ls9c_ard_3-2-1_091085_2024-02-11_final.stac-item
2024-02-28 09:28:36	ga_ls9c_ard_3-2-1_091089_2024-02-27_final.stac-item
2024-03-01 09:13:52	ga_ls9c_ard_3-2-1_089083_2024-02-29_final.stac-item
2024-03-31 09:26:53	ga_ls9c_ard_3-2-1_091085_2024-03-30_final.stac-item
2024-04-02 09:12:31	ga_ls9c_ard_3-2-1_089080_2024-04-01_final.stac-item
2024-04-05 09:41:25	ga_ls9c_ard_3-2-1_094075_2024-04-05_final.stac-item
2024-04-25 10:53:13	ga_ls9c_ard_3-2-1_106070_2024-04-25_final.stac-item
2024-04-28 11:29:18	ga_ls9c_ard_3-2-1_111083_2024-04-28_final.stac-item
2024-05-03 11:45:25	ga_ls9c_ard_3-2-1_114077_2024-05-03_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years