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
2021-11-06 10:14:59	ga_ls9c_ard_3-2-1_100072_2021-11-06_final.stac-item
2021-11-07 09:19:28	ga_ls9c_ard_3-2-1_090080_2021-11-06_final.stac-item
2021-11-07 09:20:16	ga_ls9c_ard_3-2-1_090082_2021-11-06_final.stac-item
2021-11-22 11:06:43	ga_ls9c_ard_3-2-1_107083_2021-11-22_final.stac-item
2021-12-04 11:01:46	ga_ls9c_ard_3-2-1_107074_2021-12-04_final.stac-item
2021-12-06 09:15:18	ga_ls9c_ard_3-2-1_089086_2021-12-05_final.stac-item
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2021-12-28 11:51:30	ga_ls9c_ard_3-2-1_115075_2021-12-28_final.stac-item
2021-12-29 09:19:47	ga_ls9c_ard_3-2-1_090082_2021-12-28_final.stac-item
2022-01-04 10:19:11	ga_ls9c_ard_3-2-1_100076_2022-01-04_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-29 10:13:24	ga_ls9c_ard_3-2-1_099077_2022-01-29_final.stac-item
2022-02-08 09:13:10	ga_ls9c_ard_3-2-1_089081_2022-02-07_final.stac-item
2022-02-21 10:20:14	ga_ls9c_ard_3-2-1_100079_2022-02-21_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-11 11:16:34	ga_ls9c_ard_3-2-1_109082_2022-05-11_final.stac-item
2022-06-02 10:33:47	ga_ls9c_ard_3-2-1_103068_2022-06-02_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-06 10:27:44	ga_ls9c_ard_3-2-1_101083_2022-07-06_final.stac-item
2022-07-08 11:52:15	ga_ls9c_ard_3-2-1_115078_2022-07-08_final.stac-item
2022-07-26 10:03:32	ga_ls9c_ard_3-2-1_097084_2022-07-26_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-02 11:46:18	ga_ls9c_ard_3-2-1_114078_2022-08-02_final.stac-item
2022-08-08 09:34:47	ga_ls9c_ard_3-2-1_092089_2022-08-08_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-16 10:21:54	ga_ls9c_ard_3-2-1_100083_2022-08-16_final.stac-item
2022-08-25 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-08-25_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-09-09 11:07:22	ga_ls9c_ard_3-2-1_108073_2022-09-09_final.stac-item
2022-09-10 10:08:58	ga_ls9c_ard_3-2-1_099066_2022-09-10_final.stac-item
2022-09-19 10:04:04	ga_ls9c_ard_3-2-1_098069_2022-09-19_final.stac-item
2022-10-16 09:46:51	ga_ls9c_ard_3-2-1_095072_2022-10-16_final.stac-item
2022-11-12 11:06:25	ga_ls9c_ard_3-2-1_108070_2022-11-12_final.stac-item
2022-11-22 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-11-22_final.stac-item
2022-12-14 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-12-14_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-01-14 10:24:41	ga_ls9c_ard_3-2-1_101074_2023-01-14_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-01-21 10:30:21	ga_ls9c_ard_3-2-1_102073_2023-01-21_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-02-03 11:38:56	ga_ls9c_ard_3-2-1_113074_2023-02-03_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-04 10:41:19	ga_ls9c_ard_3-2-1_104069_2023-02-04_final.stac-item
2023-02-06 10:30:34	ga_ls9c_ard_3-2-1_102073_2023-02-06_final.stac-item
2023-02-09 11:01:29	ga_ls9c_ard_3-2-1_107073_2023-02-09_final.stac-item
2023-02-11 10:49:54	ga_ls9c_ard_3-2-1_105075_2023-02-11_final.stac-item
2023-03-02 11:23:45	ga_ls9c_ard_3-2-1_110083_2023-03-02_final.stac-item
2023-03-06 09:22:54	ga_ls9c_ard_3-2-1_090090_2023-03-05_final.stac-item
2023-03-07 11:38:38	ga_ls9c_ard_3-2-1_113074_2023-03-07_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-14 10:07:29	ga_ls9c_ard_3-2-1_098078_2023-03-14_final.stac-item
2023-03-28 10:21:17	ga_ls9c_ard_3-2-1_100082_2023-03-28_final.stac-item
2023-04-05 11:11:05	ga_ls9c_ard_3-2-1_108083_2023-04-05_final.stac-item
2023-04-16 09:12:46	ga_ls9c_ard_3-2-1_089081_2023-04-15_final.stac-item
2023-04-20 10:25:20	ga_ls9c_ard_3-2-1_101077_2023-04-20_final.stac-item
2023-04-21 11:07:00	ga_ls9c_ard_3-2-1_108073_2023-04-21_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final.stac-item
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final.stac-item
2023-06-23 10:24:48	ga_ls9c_ard_3-2-1_101077_2023-06-23_final.stac-item
2023-07-05 09:12:50	ga_ls9c_ard_3-2-1_089082_2023-07-04_final.stac-item
2023-07-20 10:07:20	ga_ls9c_ard_3-2-1_098079_2023-07-20_final.stac-item
2023-08-06 10:46:22	ga_ls9c_ard_3-2-1_105068_2023-08-06_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-22 09:11:57	ga_ls9c_ard_3-2-1_089079_2023-08-21_final.stac-item
2023-09-10 11:23:57	ga_ls9c_ard_3-2-1_110084_2023-09-10_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-23 10:46:16	ga_ls9c_ard_3-2-1_105067_2023-09-23_final.stac-item
2023-09-30 09:21:55	ga_ls9c_ard_3-2-1_090088_2023-09-29_final.stac-item
2023-10-01 10:03:36	ga_ls9c_ard_3-2-1_097084_2023-10-01_final.stac-item
2023-10-05 09:33:45	ga_ls9c_ard_3-2-1_093071_2023-10-05_final.stac-item
2023-10-06 10:21:49	ga_ls9c_ard_3-2-1_100083_2023-10-06_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-16 09:22:31	ga_ls9c_ard_3-2-1_090089_2023-10-15_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-20 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-11-20_final.stac-item
2023-12-10 09:23:56	ga_ls9c_ard_3-2-1_091077_2023-12-09_final.stac-item
2024-01-03 11:51:28	ga_ls9c_ard_3-2-1_115075_2024-01-03_final.stac-item
2024-01-13 09:13:12	ga_ls9c_ard_3-2-1_089081_2024-01-12_final.stac-item
2024-01-22 10:45:03	ga_ls9c_ard_3-2-1_104079_2024-01-22_final.stac-item
2024-02-21 10:56:06	ga_ls9c_ard_3-2-1_106076_2024-02-21_final.stac-item
2024-02-28 11:02:18	ga_ls9c_ard_3-2-1_107076_2024-02-28_final.stac-item
2024-03-03 10:34:25	ga_ls9c_ard_3-2-1_103068_2024-03-03_final.stac-item
2024-03-09 11:42:13	ga_ls9c_ard_3-2-1_113083_2024-03-09_final.stac-item
2024-03-22 11:06:05	ga_ls9c_ard_3-2-1_108070_2024-03-22_final.stac-item
2024-03-28 10:29:17	ga_ls9c_ard_3-2-1_102071_2024-03-28_final.stac-item
2024-03-30 10:20:54	ga_ls9c_ard_3-2-1_100081_2024-03-30_final.stac-item
2024-04-09 09:21:51	ga_ls9c_ard_3-2-1_090088_2024-04-08_final.stac-item
2024-04-10 09:59:31	ga_ls9c_ard_3-2-1_097074_2024-04-10_final.stac-item
2024-04-11 09:06:17	ga_ls9c_ard_3-2-1_088080_2024-04-10_final.stac-item
2024-04-11 09:06:41	ga_ls9c_ard_3-2-1_088081_2024-04-10_final.stac-item
2024-04-16 11:01:14	ga_ls9c_ard_3-2-1_107074_2024-04-16_final.stac-item
2024-04-23 09:34:42	ga_ls9c_ard_3-2-1_092090_2024-04-23_final.stac-item
2024-04-25 10:52:49	ga_ls9c_ard_3-2-1_106069_2024-04-25_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