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
2021-11-03 11:33:37	ga_ls9c_ard_3-2-1_112075_2021-11-03_final.stac-item
2021-11-14 10:40:40	ga_ls9c_ard_3-2-1_103077_2021-11-14_final.stac-item
2021-11-17 09:26:28	ga_ls9c_ard_3-2-1_091085_2021-11-16_final.stac-item
2021-12-08 10:38:36	ga_ls9c_ard_3-2-1_103078_2021-12-08_final.stac-item
2021-12-09 09:44:34	ga_ls9c_ard_3-2-1_094082_2021-12-09_final.stac-item
2021-12-15 10:45:30	ga_ls9c_ard_3-2-1_104080_2021-12-15_final.stac-item
2021-12-16 11:27:57	ga_ls9c_ard_3-2-1_111078_2021-12-16_final.stac-item
2021-12-30 11:41:56	ga_ls9c_ard_3-2-1_113082_2021-12-30_final.stac-item
2022-01-04 11:58:28	ga_ls9c_ard_3-2-1_116077_2022-01-04_final.stac-item
2022-01-09 10:35:42	ga_ls9c_ard_3-2-1_103071_2022-01-09_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-20 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-01-20_final.stac-item
2022-01-23 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-23_final.stac-item
2022-01-28 09:30:56	ga_ls9c_ard_3-2-1_092079_2022-01-28_final.stac-item
2022-01-29 10:14:59	ga_ls9c_ard_3-2-1_099081_2022-01-29_final.stac-item
2022-02-02 09:47:52	ga_ls9c_ard_3-2-1_095075_2022-02-02_final.stac-item
2022-02-15 10:56:35	ga_ls9c_ard_3-2-1_106077_2022-02-15_final.stac-item
2022-02-21 11:58:19	ga_ls9c_ard_3-2-1_116077_2022-02-21_final.stac-item
2022-02-24 10:47:54	ga_ls9c_ard_3-2-1_105071_2022-02-24_final.stac-item
2022-02-27 11:22:21	ga_ls9c_ard_3-2-1_110080_2022-02-27_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-10 11:02:59	ga_ls9c_ard_3-2-1_107078_2022-03-10_final.stac-item
2022-03-29 09:55:19	ga_ls9c_ard_3-2-1_096079_2022-03-29_final.stac-item
2022-04-05 11:39:11	ga_ls9c_ard_3-2-1_113076_2022-04-05_final.stac-item
2022-04-13 10:47:41	ga_ls9c_ard_3-2-1_105071_2022-04-13_final.stac-item
2022-04-14 09:55:14	ga_ls9c_ard_3-2-1_096079_2022-04-14_final.stac-item
2022-05-29 09:23:59	ga_ls9c_ard_3-2-1_091079_2022-05-28_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-05-31 10:47:44	ga_ls9c_ard_3-2-1_105072_2022-05-31_final.stac-item
2022-06-10 09:47:33	ga_ls9c_ard_3-2-1_095076_2022-06-10_final.stac-item
2022-06-13 10:20:05	ga_ls9c_ard_3-2-1_100080_2022-06-13_final.stac-item
2022-06-14 09:25:17	ga_ls9c_ard_3-2-1_091082_2022-06-13_final.stac-item
2022-06-14 11:00:10	ga_ls9c_ard_3-2-1_107072_2022-06-14_final.stac-item
2022-06-15 10:05:46	ga_ls9c_ard_3-2-1_098075_2022-06-15_final.stac-item
2022-06-16 10:50:38	ga_ls9c_ard_3-2-1_105079_2022-06-16_final.stac-item
2022-06-28 09:38:19	ga_ls9c_ard_3-2-1_093083_2022-06-28_final.stac-item
2022-07-08 10:14:34	ga_ls9c_ard_3-2-1_099081_2022-07-08_final.stac-item
2022-07-11 10:40:39	ga_ls9c_ard_3-2-1_104069_2022-07-11_final.stac-item
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final.stac-item
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final.stac-item
2022-08-02 10:03:49	ga_ls9c_ard_3-2-1_098069_2022-08-02_final.stac-item
2022-08-04 09:53:05	ga_ls9c_ard_3-2-1_096073_2022-08-04_final.stac-item
2022-08-06 09:43:08	ga_ls9c_ard_3-2-1_094079_2022-08-06_final.stac-item
2022-08-20 11:35:41	ga_ls9c_ard_3-2-1_112082_2022-08-20_final.stac-item
2022-08-22 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-08-22_final.stac-item
2022-08-23 10:26:30	ga_ls9c_ard_3-2-1_101079_2022-08-23_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-12 10:03:49	ga_ls9c_ard_3-2-1_097084_2022-09-12_final.stac-item
2022-09-13 10:43:29	ga_ls9c_ard_3-2-1_104075_2022-09-13_final.stac-item
2022-10-10 10:25:28	ga_ls9c_ard_3-2-1_101076_2022-10-10_final.stac-item
2022-10-20 11:05:49	ga_ls9c_ard_3-2-1_107084_2022-10-20_final.stac-item
2022-10-24 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-10-24_final.stac-item
2022-10-27 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-10-27_final.stac-item
2022-11-03 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-11-03_final.stac-item
2022-11-05 11:04:10	ga_ls9c_ard_3-2-1_107080_2022-11-05_final.stac-item
2022-11-09 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-09_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-12 11:07:13	ga_ls9c_ard_3-2-1_108072_2022-11-12_final.stac-item
2022-11-20 10:20:58	ga_ls9c_ard_3-2-1_100080_2022-11-20_final.stac-item
2022-11-21 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-11-21_final.stac-item
2022-11-25 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-25_final.stac-item
2022-12-07 11:04:36	ga_ls9c_ard_3-2-1_107081_2022-12-07_final.stac-item
2022-12-12 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-12-12_final.stac-item
2022-12-17 11:40:05	ga_ls9c_ard_3-2-1_113077_2022-12-17_final.stac-item
2022-12-21 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-12-21_final.stac-item
2022-12-24 10:05:44	ga_ls9c_ard_3-2-1_098073_2022-12-24_final.stac-item
2022-12-28 11:21:56	ga_ls9c_ard_3-2-1_110078_2022-12-28_final.stac-item
2022-12-30 09:32:18	ga_ls9c_ard_3-2-1_092082_2022-12-30_final.stac-item
2023-01-02 11:39:42	ga_ls9c_ard_3-2-1_113076_2023-01-02_final.stac-item
2023-01-10 09:12:57	ga_ls9c_ard_3-2-1_089080_2023-01-09_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-19 10:44:44	ga_ls9c_ard_3-2-1_104078_2023-01-19_final.stac-item
2023-01-19 10:45:56	ga_ls9c_ard_3-2-1_104081_2023-01-19_final.stac-item
2023-01-23 10:21:38	ga_ls9c_ard_3-2-1_100082_2023-01-23_final.stac-item
2023-02-02 09:20:22	ga_ls9c_ard_3-2-1_090083_2023-02-01_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-02-07 09:37:45	ga_ls9c_ard_3-2-1_093080_2023-02-07_final.stac-item
2023-02-15 10:26:44	ga_ls9c_ard_3-2-1_101079_2023-02-15_final.stac-item
2023-02-18 09:19:06	ga_ls9c_ard_3-2-1_090080_2023-02-17_final.stac-item
2023-02-18 10:57:59	ga_ls9c_ard_3-2-1_106080_2023-02-18_final.stac-item
2023-02-19 11:39:14	ga_ls9c_ard_3-2-1_113075_2023-02-19_final.stac-item
2023-03-12 10:20:15	ga_ls9c_ard_3-2-1_100079_2023-03-12_final.stac-item
2023-03-20 09:29:35	ga_ls9c_ard_3-2-1_092076_2023-03-19_final.stac-item
2023-03-22 09:19:36	ga_ls9c_ard_3-2-1_090082_2023-03-21_final.stac-item
2023-03-24 10:43:42	ga_ls9c_ard_3-2-1_104076_2023-03-24_final.stac-item
2023-04-09 10:43:33	ga_ls9c_ard_3-2-1_104076_2023-04-09_final.stac-item
2023-04-14 11:00:49	ga_ls9c_ard_3-2-1_107073_2023-04-14_final.stac-item
2023-05-03 09:55:51	ga_ls9c_ard_3-2-1_096081_2023-05-03_final.stac-item
2023-05-21 11:20:38	ga_ls9c_ard_3-2-1_110077_2023-05-21_final.stac-item
2023-05-22 10:25:48	ga_ls9c_ard_3-2-1_101079_2023-05-22_final.stac-item
2023-06-03 10:49:40	ga_ls9c_ard_3-2-1_105077_2023-06-03_final.stac-item
2023-06-11 10:01:44	ga_ls9c_ard_3-2-1_097081_2023-06-11_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-07-10 09:30:14	ga_ls9c_ard_3-2-1_092079_2023-07-10_final.stac-item
2023-07-10 11:09:31	ga_ls9c_ard_3-2-1_108080_2023-07-10_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-09-08 11:35:29	ga_ls9c_ard_3-2-1_112082_2023-09-08_final.stac-item
2023-09-09 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-09_final.stac-item
2023-09-09 10:37:53	ga_ls9c_ard_3-2-1_103077_2023-09-09_final.stac-item
2023-09-10 11:24:20	ga_ls9c_ard_3-2-1_110085_2023-09-10_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years