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
2021-11-07 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-19 10:42:43	ga_ls9c_ard_3-2-1_104076_2021-11-19_final.stac-item
2021-12-09 11:23:03	ga_ls9c_ard_3-2-1_110081_2021-12-09_final.stac-item
2021-12-16 11:27:33	ga_ls9c_ard_3-2-1_111077_2021-12-16_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-20 09:24:21	ga_ls9c_ard_3-2-1_091078_2021-12-19_final.stac-item
2021-12-22 09:14:24	ga_ls9c_ard_3-2-1_089084_2021-12-21_final.stac-item
2021-12-22 10:51:41	ga_ls9c_ard_3-2-1_105080_2021-12-22_final.stac-item
2021-12-28 10:12:13	ga_ls9c_ard_3-2-1_099074_2021-12-28_final.stac-item
2022-02-25 11:36:20	ga_ls9c_ard_3-2-1_112084_2022-02-25_final.stac-item
2022-03-05 10:43:39	ga_ls9c_ard_3-2-1_104076_2022-03-05_final.stac-item
2022-03-23 10:31:38	ga_ls9c_ard_3-2-1_102077_2022-03-23_final.stac-item
2022-03-28 10:48:09	ga_ls9c_ard_3-2-1_105072_2022-03-28_final.stac-item
2022-03-30 10:36:11	ga_ls9c_ard_3-2-1_103073_2022-03-30_final.stac-item
2022-04-16 09:46:03	ga_ls9c_ard_3-2-1_094087_2022-04-16_final.stac-item
2022-04-17 10:24:54	ga_ls9c_ard_3-2-1_101076_2022-04-17_final.stac-item
2022-04-30 11:35:36	ga_ls9c_ard_3-2-1_112083_2022-04-30_final.stac-item
2022-05-15 10:46:36	ga_ls9c_ard_3-2-1_105069_2022-05-15_final.stac-item
2022-06-04 10:23:49	ga_ls9c_ard_3-2-1_101074_2022-06-04_final.stac-item
2022-06-04 10:26:13	ga_ls9c_ard_3-2-1_101080_2022-06-04_final.stac-item
2022-06-07 10:56:19	ga_ls9c_ard_3-2-1_106078_2022-06-07_final.stac-item
2022-06-20 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-06-20_final.stac-item
2022-06-21 11:06:31	ga_ls9c_ard_3-2-1_108072_2022-06-21_final.stac-item
2022-07-07 09:29:18	ga_ls9c_ard_3-2-1_092076_2022-07-06_final.stac-item
2022-07-29 10:32:29	ga_ls9c_ard_3-2-1_102079_2022-07-29_final.stac-item
2022-07-30 09:36:29	ga_ls9c_ard_3-2-1_093078_2022-07-30_final.stac-item
2022-07-31 10:20:33	ga_ls9c_ard_3-2-1_100080_2022-07-31_final.stac-item
2022-08-01 11:05:25	ga_ls9c_ard_3-2-1_107084_2022-08-01_final.stac-item
2022-08-03 10:46:18	ga_ls9c_ard_3-2-1_105067_2022-08-03_final.stac-item
2022-08-04 11:33:34	ga_ls9c_ard_3-2-1_112077_2022-08-04_final.stac-item
2022-08-07 10:25:13	ga_ls9c_ard_3-2-1_101076_2022-08-07_final.stac-item
2022-08-12 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-08-12_final.stac-item
2022-08-15 11:16:43	ga_ls9c_ard_3-2-1_109081_2022-08-15_final.stac-item
2022-08-18 10:06:21	ga_ls9c_ard_3-2-1_098075_2022-08-18_final.stac-item
2022-08-28 10:41:04	ga_ls9c_ard_3-2-1_104069_2022-08-28_final.stac-item
2022-08-28 10:44:39	ga_ls9c_ard_3-2-1_104078_2022-08-28_final.stac-item
2022-09-17 10:18:48	ga_ls9c_ard_3-2-1_100075_2022-09-17_final.stac-item
2022-09-19 11:45:21	ga_ls9c_ard_3-2-1_114075_2022-09-19_final.stac-item
2022-09-19 11:46:57	ga_ls9c_ard_3-2-1_114079_2022-09-19_final.stac-item
2022-09-23 09:42:34	ga_ls9c_ard_3-2-1_094077_2022-09-23_final.stac-item
2022-10-29 09:19:08	ga_ls9c_ard_3-2-1_090080_2022-10-28_final.stac-item
2022-10-29 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-10-29_final.stac-item
2022-11-01 11:24:07	ga_ls9c_ard_3-2-1_111068_2022-11-01_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-19 11:17:47	ga_ls9c_ard_3-2-1_109083_2022-11-19_final.stac-item
2022-11-28 09:32:17	ga_ls9c_ard_3-2-1_092082_2022-11-28_final.stac-item
2022-11-29 10:12:45	ga_ls9c_ard_3-2-1_099075_2022-11-29_final.stac-item
2022-12-21 09:37:15	ga_ls9c_ard_3-2-1_093079_2022-12-21_final.stac-item
2022-12-21 11:16:08	ga_ls9c_ard_3-2-1_109079_2022-12-21_final.stac-item
2022-12-31 10:16:45	ga_ls9c_ard_3-2-1_099085_2022-12-31_final.stac-item
2023-01-12 10:38:16	ga_ls9c_ard_3-2-1_103077_2023-01-12_final.stac-item
2023-01-13 11:22:19	ga_ls9c_ard_3-2-1_110079_2023-01-13_final.stac-item
2023-01-13 11:23:07	ga_ls9c_ard_3-2-1_110081_2023-01-13_final.stac-item
2023-01-17 10:56:20	ga_ls9c_ard_3-2-1_106076_2023-01-17_final.stac-item
2023-01-21 10:29:57	ga_ls9c_ard_3-2-1_102072_2023-01-21_final.stac-item
2023-02-01 11:53:40	ga_ls9c_ard_3-2-1_115080_2023-02-01_final.stac-item
2023-02-07 11:15:26	ga_ls9c_ard_3-2-1_109077_2023-02-07_final.stac-item
2023-02-11 09:10:37	ga_ls9c_ard_3-2-1_089074_2023-02-10_final.stac-item
2023-02-12 11:35:09	ga_ls9c_ard_3-2-1_112080_2023-02-12_final.stac-item
2023-02-14 09:46:17	ga_ls9c_ard_3-2-1_094086_2023-02-14_final.stac-item
2023-02-16 09:33:06	ga_ls9c_ard_3-2-1_092084_2023-02-16_final.stac-item
2023-02-17 11:51:14	ga_ls9c_ard_3-2-1_115074_2023-02-17_final.stac-item
2023-02-19 10:00:21	ga_ls9c_ard_3-2-1_097075_2023-02-19_final.stac-item
2023-02-23 09:39:07	ga_ls9c_ard_3-2-1_093084_2023-02-23_final.stac-item
2023-03-15 10:48:21	ga_ls9c_ard_3-2-1_105072_2023-03-15_final.stac-item
2023-03-20 11:06:04	ga_ls9c_ard_3-2-1_108070_2023-03-20_final.stac-item
2023-03-29 09:28:26	ga_ls9c_ard_3-2-1_091089_2023-03-28_final.stac-item
2023-04-10 11:27:35	ga_ls9c_ard_3-2-1_111078_2023-04-10_final.stac-item
2023-04-13 11:57:39	ga_ls9c_ard_3-2-1_116076_2023-04-13_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-05-02 09:13:49	ga_ls9c_ard_3-2-1_089084_2023-05-01_final.stac-item
2023-05-02 10:50:18	ga_ls9c_ard_3-2-1_105078_2023-05-02_final.stac-item
2023-05-03 09:55:03	ga_ls9c_ard_3-2-1_096079_2023-05-03_final.stac-item
2023-05-04 10:37:54	ga_ls9c_ard_3-2-1_103078_2023-05-04_final.stac-item
2023-05-20 10:34:36	ga_ls9c_ard_3-2-1_103070_2023-05-20_final.stac-item
2023-05-25 09:18:34	ga_ls9c_ard_3-2-1_090081_2023-05-24_final.stac-item
2023-06-02 11:46:05	ga_ls9c_ard_3-2-1_114079_2023-06-02_final.stac-item
2023-06-12 10:42:59	ga_ls9c_ard_3-2-1_104076_2023-06-12_final.stac-item
2023-06-17 11:01:53	ga_ls9c_ard_3-2-1_107077_2023-06-17_final.stac-item
2023-06-20 11:33:11	ga_ls9c_ard_3-2-1_112078_2023-06-20_final.stac-item
2023-06-20 11:34:47	ga_ls9c_ard_3-2-1_112082_2023-06-20_final.stac-item
2023-06-24 09:28:47	ga_ls9c_ard_3-2-1_092076_2023-06-23_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-18 10:20:30	ga_ls9c_ard_3-2-1_100081_2023-07-18_final.stac-item
2023-07-24 11:22:41	ga_ls9c_ard_3-2-1_110082_2023-07-24_final.stac-item
2023-07-29 10:00:25	ga_ls9c_ard_3-2-1_097077_2023-07-29_final.stac-item
2023-08-07 09:53:08	ga_ls9c_ard_3-2-1_096074_2023-08-07_final.stac-item
2023-08-09 11:21:40	ga_ls9c_ard_3-2-1_110079_2023-08-09_final.stac-item
2023-08-12 11:52:58	ga_ls9c_ard_3-2-1_115080_2023-08-12_final.stac-item
2023-08-13 09:17:40	ga_ls9c_ard_3-2-1_090078_2023-08-12_final.stac-item
2023-08-14 10:02:08	ga_ls9c_ard_3-2-1_097081_2023-08-14_final.stac-item
2023-08-17 10:29:02	ga_ls9c_ard_3-2-1_102071_2023-08-17_final.stac-item
2023-08-23 11:34:31	ga_ls9c_ard_3-2-1_112080_2023-08-23_final.stac-item
2023-08-25 11:18:35	ga_ls9c_ard_3-2-1_110071_2023-08-25_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-27 10:37:15	ga_ls9c_ard_3-2-1_103075_2023-10-27_final.stac-item
2023-11-18 11:39:03	ga_ls9c_ard_3-2-1_113075_2023-11-18_final.stac-item
2023-11-27 11:35:46	ga_ls9c_ard_3-2-1_112082_2023-11-27_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