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
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2021-12-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2021-12-08_final.stac-item
2021-12-12 10:15:02	ga_ls9c_ard_3-2-1_099081_2021-12-12_final.stac-item
2021-12-18 09:39:30	ga_ls9c_ard_3-2-1_093085_2021-12-18_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-10 09:42:04	ga_ls9c_ard_3-2-1_094076_2022-01-10_final.stac-item
2022-01-30 10:56:39	ga_ls9c_ard_3-2-1_106077_2022-01-30_final.stac-item
2022-03-22 11:29:39	ga_ls9c_ard_3-2-1_111083_2022-03-22_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-04-13 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-04-13_final.stac-item
2022-05-21 10:08:38	ga_ls9c_ard_3-2-1_099067_2022-05-21_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-15 10:04:34	ga_ls9c_ard_3-2-1_098072_2022-06-15_final.stac-item
2022-06-28 09:34:43	ga_ls9c_ard_3-2-1_093074_2022-06-28_final.stac-item
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final.stac-item
2022-07-17 10:02:47	ga_ls9c_ard_3-2-1_098067_2022-07-17_final.stac-item
2022-07-24 10:10:17	ga_ls9c_ard_3-2-1_099070_2022-07-24_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-10-05 10:05:42	ga_ls9c_ard_3-2-1_098073_2022-10-05_final.stac-item
2022-10-16 09:46:27	ga_ls9c_ard_3-2-1_095071_2022-10-16_final.stac-item
2022-10-16 09:51:38	ga_ls9c_ard_3-2-1_095084_2022-10-16_final.stac-item
2022-10-28 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-10-28_final.stac-item
2022-10-30 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-10-30_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-09 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-09_final.stac-item
2022-11-12 09:31:07	ga_ls9c_ard_3-2-1_092079_2022-11-12_final.stac-item
2022-11-12 11:10:48	ga_ls9c_ard_3-2-1_108081_2022-11-12_final.stac-item
2022-11-16 10:41:18	ga_ls9c_ard_3-2-1_104069_2022-11-16_final.stac-item
2022-11-19 11:13:48	ga_ls9c_ard_3-2-1_109073_2022-11-19_final.stac-item
2022-11-20 10:18:10	ga_ls9c_ard_3-2-1_100073_2022-11-20_final.stac-item
2022-11-25 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-11-25_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-05 11:15:21	ga_ls9c_ard_3-2-1_109077_2022-12-05_final.stac-item
2022-12-16 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-12-15_final.stac-item
2022-12-17 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-12-17_final.stac-item
2022-12-18 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-12-18_final.stac-item
2022-12-31 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-12-31_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_2022-12-31_final.stac-item
2023-01-08 11:02:13	ga_ls9c_ard_3-2-1_107075_2023-01-08_final.stac-item
2023-01-13 11:23:31	ga_ls9c_ard_3-2-1_110082_2023-01-13_final.stac-item
2023-01-17 09:21:50	ga_ls9c_ard_3-2-1_090087_2023-01-16_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-07 11:13:26	ga_ls9c_ard_3-2-1_109072_2023-02-07_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-09 11:01:53	ga_ls9c_ard_3-2-1_107074_2023-02-09_final.stac-item
2023-02-10 11:46:44	ga_ls9c_ard_3-2-1_114078_2023-02-10_final.stac-item
2023-02-14 09:46:41	ga_ls9c_ard_3-2-1_094087_2023-02-14_final.stac-item
2023-03-11 11:13:28	ga_ls9c_ard_3-2-1_109073_2023-03-11_final.stac-item
2023-04-21 11:10:59	ga_ls9c_ard_3-2-1_108083_2023-04-21_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-02 10:46:19	ga_ls9c_ard_3-2-1_105068_2023-05-02_final.stac-item
2023-05-02 10:48:18	ga_ls9c_ard_3-2-1_105073_2023-05-02_final.stac-item
2023-05-05 09:40:40	ga_ls9c_ard_3-2-1_094074_2023-05-05_final.stac-item
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final.stac-item
2023-05-05 11:18:21	ga_ls9c_ard_3-2-1_110071_2023-05-05_final.stac-item
2023-05-09 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-05-08_final.stac-item
2023-05-13 10:30:30	ga_ls9c_ard_3-2-1_102075_2023-05-13_final.stac-item
2023-05-18 09:11:42	ga_ls9c_ard_3-2-1_089079_2023-05-17_final.stac-item
2023-05-18 09:13:41	ga_ls9c_ard_3-2-1_089084_2023-05-17_final.stac-item
2023-05-18 09:16:05	ga_ls9c_ard_3-2-1_089090_2023-05-17_final.stac-item
2023-05-20 10:37:23	ga_ls9c_ard_3-2-1_103077_2023-05-20_final.stac-item
2023-05-31 10:20:22	ga_ls9c_ard_3-2-1_100081_2023-05-31_final.stac-item
2023-06-19 10:46:20	ga_ls9c_ard_3-2-1_105069_2023-06-19_final.stac-item
2023-06-22 11:18:02	ga_ls9c_ard_3-2-1_110071_2023-06-22_final.stac-item
2023-06-29 09:50:37	ga_ls9c_ard_3-2-1_095084_2023-06-29_final.stac-item
2023-07-02 10:21:35	ga_ls9c_ard_3-2-1_100084_2023-07-02_final.stac-item
2023-07-06 09:56:31	ga_ls9c_ard_3-2-1_096083_2023-07-06_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-24 11:20:17	ga_ls9c_ard_3-2-1_110076_2023-07-24_final.stac-item
2023-07-24 11:23:05	ga_ls9c_ard_3-2-1_110083_2023-07-24_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-07-29 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-07-29_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-11 09:32:49	ga_ls9c_ard_3-2-1_092085_2023-08-11_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-19 11:27:08	ga_ls9c_ard_3-2-1_111076_2023-10-19_final.stac-item
2023-10-23 09:27:07	ga_ls9c_ard_3-2-1_091085_2023-10-22_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-10-30 09:32:26	ga_ls9c_ard_3-2-1_092083_2023-10-30_final.stac-item
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-18 10:01:46	ga_ls9c_ard_3-2-1_097079_2023-11-18_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-11-21 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-11-21_final.stac-item
2023-11-24 11:00:04	ga_ls9c_ard_3-2-1_107070_2023-11-24_final.stac-item
2023-11-25 10:03:15	ga_ls9c_ard_3-2-1_098067_2023-11-25_final.stac-item
2023-11-25 11:45:44	ga_ls9c_ard_3-2-1_114076_2023-11-25_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