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
2021-11-22 11:02:20	ga_ls9c_ard_3-2-1_107072_2021-11-22_final.stac-item
2021-12-07 09:53:46	ga_ls9c_ard_3-2-1_096074_2021-12-07_final.stac-item
2021-12-07 09:54:10	ga_ls9c_ard_3-2-1_096075_2021-12-07_final.stac-item
2021-12-07 11:33:03	ga_ls9c_ard_3-2-1_112075_2021-12-07_final.stac-item
2021-12-13 10:58:17	ga_ls9c_ard_3-2-1_106081_2021-12-13_final.stac-item
2022-01-13 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-01-13_final.stac-item
2022-01-17 09:48:15	ga_ls9c_ard_3-2-1_095076_2022-01-17_final.stac-item
2022-01-31 11:40:43	ga_ls9c_ard_3-2-1_113079_2022-01-31_final.stac-item
2022-02-11 09:43:15	ga_ls9c_ard_3-2-1_094079_2022-02-11_final.stac-item
2022-03-01 09:31:53	ga_ls9c_ard_3-2-1_092082_2022-03-01_final.stac-item
2022-03-04 10:00:47	ga_ls9c_ard_3-2-1_097077_2022-03-04_final.stac-item
2022-03-21 10:45:12	ga_ls9c_ard_3-2-1_104080_2022-03-21_final.stac-item
2022-04-23 09:48:57	ga_ls9c_ard_3-2-1_095079_2022-04-23_final.stac-item
2022-05-16 09:53:45	ga_ls9c_ard_3-2-1_096076_2022-05-16_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-09 10:43:33	ga_ls9c_ard_3-2-1_104077_2022-06-09_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-06-19 09:43:06	ga_ls9c_ard_3-2-1_094080_2022-06-19_final.stac-item
2022-06-21 09:30:01	ga_ls9c_ard_3-2-1_092078_2022-06-21_final.stac-item
2022-07-15 10:20:41	ga_ls9c_ard_3-2-1_100081_2022-07-15_final.stac-item
2022-07-20 10:38:56	ga_ls9c_ard_3-2-1_103080_2022-07-20_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-07-23 11:10:41	ga_ls9c_ard_3-2-1_108082_2022-07-23_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-08 11:10:53	ga_ls9c_ard_3-2-1_108082_2022-08-08_final.stac-item
2022-08-21 10:35:40	ga_ls9c_ard_3-2-1_103071_2022-08-21_final.stac-item
2022-08-21 10:39:16	ga_ls9c_ard_3-2-1_103080_2022-08-21_final.stac-item
2022-09-01 10:18:20	ga_ls9c_ard_3-2-1_100074_2022-09-01_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_2022-09-27_final.stac-item
2022-10-03 10:18:04	ga_ls9c_ard_3-2-1_100073_2022-10-03_final.stac-item
2022-10-04 09:24:26	ga_ls9c_ard_3-2-1_091078_2022-10-03_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-08 10:37:48	ga_ls9c_ard_3-2-1_103076_2022-10-08_final.stac-item
2022-10-14 11:41:16	ga_ls9c_ard_3-2-1_113080_2022-10-14_final.stac-item
2022-10-23 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-10-23_final.stac-item
2022-10-27 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-10-27_final.stac-item
2022-11-01 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-11-01_final.stac-item
2022-11-03 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-11-03_final.stac-item
2022-11-12 11:07:13	ga_ls9c_ard_3-2-1_108072_2022-11-12_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2022-11-28 09:30:41	ga_ls9c_ard_3-2-1_092078_2022-11-28_final.stac-item
2022-11-28 09:32:41	ga_ls9c_ard_3-2-1_092083_2022-11-28_final.stac-item
2022-12-02 10:43:38	ga_ls9c_ard_3-2-1_104075_2022-12-02_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-07 11:03:48	ga_ls9c_ard_3-2-1_107079_2022-12-07_final.stac-item
2022-12-11 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-12-11_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-21 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-12-21_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2022-12-28 09:42:15	ga_ls9c_ard_3-2-1_094076_2022-12-28_final.stac-item
2023-01-05 10:33:19	ga_ls9c_ard_3-2-1_102080_2023-01-05_final.stac-item
2023-01-09 11:47:04	ga_ls9c_ard_3-2-1_114079_2023-01-09_final.stac-item
2023-01-15 09:32:38	ga_ls9c_ard_3-2-1_092083_2023-01-15_final.stac-item
2023-01-16 10:12:18	ga_ls9c_ard_3-2-1_099074_2023-01-16_final.stac-item
2023-01-22 09:38:21	ga_ls9c_ard_3-2-1_093082_2023-01-22_final.stac-item
2023-01-22 11:16:26	ga_ls9c_ard_3-2-1_109080_2023-01-22_final.stac-item
2023-01-25 10:08:06	ga_ls9c_ard_3-2-1_098079_2023-01-25_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-02 10:57:39	ga_ls9c_ard_3-2-1_106079_2023-02-02_final.stac-item
2023-02-04 10:44:55	ga_ls9c_ard_3-2-1_104078_2023-02-04_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-10 10:06:15	ga_ls9c_ard_3-2-1_098074_2023-02-10_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-03-07 11:39:02	ga_ls9c_ard_3-2-1_113075_2023-03-07_final.stac-item
2023-03-08 10:41:48	ga_ls9c_ard_3-2-1_104071_2023-03-08_final.stac-item
2023-03-08 10:43:23	ga_ls9c_ard_3-2-1_104075_2023-03-08_final.stac-item
2023-03-25 09:49:15	ga_ls9c_ard_3-2-1_095079_2023-03-25_final.stac-item
2023-04-06 10:11:28	ga_ls9c_ard_3-2-1_099073_2023-04-06_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 09:38:36	ga_ls9c_ard_3-2-1_093084_2023-04-28_final.stac-item
2023-05-11 10:42:28	ga_ls9c_ard_3-2-1_104074_2023-05-11_final.stac-item
2023-05-13 10:31:18	ga_ls9c_ard_3-2-1_102077_2023-05-13_final.stac-item
2023-05-16 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-05-15_final.stac-item
2023-05-28 09:49:04	ga_ls9c_ard_3-2-1_095080_2023-05-28_final.stac-item
2023-05-28 11:27:09	ga_ls9c_ard_3-2-1_111078_2023-05-28_final.stac-item
2023-05-30 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-05-30_final.stac-item
2023-06-19 10:46:44	ga_ls9c_ard_3-2-1_105070_2023-06-19_final.stac-item
2023-06-26 10:57:18	ga_ls9c_ard_3-2-1_106081_2023-06-26_final.stac-item
2023-07-01 09:35:07	ga_ls9c_ard_3-2-1_093076_2023-07-01_final.stac-item
2023-07-06 11:34:12	ga_ls9c_ard_3-2-1_112080_2023-07-06_final.stac-item
2023-07-19 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-07-18_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-27 10:11:56	ga_ls9c_ard_3-2-1_099075_2023-07-27_final.stac-item
2023-07-30 10:43:17	ga_ls9c_ard_3-2-1_104076_2023-07-30_final.stac-item
2023-08-04 09:24:13	ga_ls9c_ard_3-2-1_091079_2023-08-03_final.stac-item
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final.stac-item
2023-08-11 09:29:38	ga_ls9c_ard_3-2-1_092077_2023-08-10_final.stac-item
2023-08-14 11:39:25	ga_ls9c_ard_3-2-1_113077_2023-08-14_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_final.stac-item
2023-10-18 10:42:16	ga_ls9c_ard_3-2-1_104072_2023-10-18_final.stac-item
2023-10-19 11:28:44	ga_ls9c_ard_3-2-1_111080_2023-10-19_final.stac-item
2023-10-21 09:38:17	ga_ls9c_ard_3-2-1_093082_2023-10-21_final.stac-item
2023-10-23 11:03:36	ga_ls9c_ard_3-2-1_107079_2023-10-23_final.stac-item
2023-10-27 10:35:40	ga_ls9c_ard_3-2-1_103071_2023-10-27_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-03 10:42:08	ga_ls9c_ard_3-2-1_104072_2023-11-03_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