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
2021-12-06 10:52:11	ga_ls9c_ard_3-2-1_105081_2021-12-06_final.stac-item
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2021-12-27 09:32:33	ga_ls9c_ard_3-2-1_092083_2021-12-27_final.stac-item
2021-12-27 11:10:38	ga_ls9c_ard_3-2-1_108081_2021-12-27_final.stac-item
2021-12-29 10:53:05	ga_ls9c_ard_3-2-1_106068_2021-12-29_final.stac-item
2021-12-31 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-31_final.stac-item
2022-01-07 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-07_final.stac-item
2022-01-10 09:40:52	ga_ls9c_ard_3-2-1_094073_2022-01-10_final.stac-item
2022-01-13 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-01-13_final.stac-item
2022-01-14 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-01-14_final.stac-item
2022-01-15 10:04:11	ga_ls9c_ard_3-2-1_097085_2022-01-15_final.stac-item
2022-01-17 11:25:56	ga_ls9c_ard_3-2-1_111073_2022-01-17_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-05 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-02-05_final.stac-item
2022-02-08 10:50:03	ga_ls9c_ard_3-2-1_105076_2022-02-08_final.stac-item
2022-02-13 09:32:28	ga_ls9c_ard_3-2-1_092083_2022-02-13_final.stac-item
2022-02-27 09:44:16	ga_ls9c_ard_3-2-1_094082_2022-02-27_final.stac-item
2022-03-02 10:15:56	ga_ls9c_ard_3-2-1_099084_2022-03-02_final.stac-item
2022-03-07 10:33:17	ga_ls9c_ard_3-2-1_102081_2022-03-07_final.stac-item
2022-03-10 09:26:06	ga_ls9c_ard_3-2-1_091083_2022-03-09_final.stac-item
2022-03-31 09:44:10	ga_ls9c_ard_3-2-1_094082_2022-03-31_final.stac-item
2022-03-31 11:19:51	ga_ls9c_ard_3-2-1_110074_2022-03-31_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-18 11:08:33	ga_ls9c_ard_3-2-1_108077_2022-04-18_final.stac-item
2022-04-23 09:51:21	ga_ls9c_ard_3-2-1_095085_2022-04-23_final.stac-item
2022-04-24 10:30:13	ga_ls9c_ard_3-2-1_102074_2022-04-24_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-29 09:25:11	ga_ls9c_ard_3-2-1_091082_2022-05-28_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-07-25 10:55:57	ga_ls9c_ard_3-2-1_106076_2022-07-25_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-17 11:02:22	ga_ls9c_ard_3-2-1_107076_2022-08-17_final.stac-item
2022-09-07 09:46:26	ga_ls9c_ard_3-2-1_094087_2022-09-07_final.stac-item
2022-09-16 11:14:01	ga_ls9c_ard_3-2-1_109074_2022-09-16_final.stac-item
2022-09-22 10:39:47	ga_ls9c_ard_3-2-1_103081_2022-09-22_final.stac-item
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-09-29 10:45:59	ga_ls9c_ard_3-2-1_104081_2022-09-29_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-11 11:10:44	ga_ls9c_ard_3-2-1_108081_2022-10-11_final.stac-item
2022-10-15 10:41:40	ga_ls9c_ard_3-2-1_104070_2022-10-15_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-10-18 11:14:34	ga_ls9c_ard_3-2-1_109075_2022-10-18_final.stac-item
2022-11-05 11:05:22	ga_ls9c_ard_3-2-1_107083_2022-11-05_final.stac-item
2022-11-15 10:02:02	ga_ls9c_ard_3-2-1_097079_2022-11-15_final.stac-item
2022-11-16 10:41:42	ga_ls9c_ard_3-2-1_104070_2022-11-16_final.stac-item
2022-11-21 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-11-21_final.stac-item
2022-11-22 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-11-22_final.stac-item
2022-11-25 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-11-25_final.stac-item
2022-11-29 10:16:20	ga_ls9c_ard_3-2-1_099084_2022-11-29_final.stac-item
2022-12-03 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-12-03_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-06 10:22:32	ga_ls9c_ard_3-2-1_100084_2022-12-06_final.stac-item
2022-12-18 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-12-18_final.stac-item
2022-12-24 10:06:32	ga_ls9c_ard_3-2-1_098075_2022-12-24_final.stac-item
2022-12-30 09:35:29	ga_ls9c_ard_3-2-1_092090_2022-12-30_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-02-05 09:47:18	ga_ls9c_ard_3-2-1_095073_2023-02-05_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-10 10:03:51	ga_ls9c_ard_3-2-1_098068_2023-02-10_final.stac-item
2023-02-20 10:46:23	ga_ls9c_ard_3-2-1_104082_2023-02-20_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-03-02 11:20:33	ga_ls9c_ard_3-2-1_110075_2023-03-02_final.stac-item
2023-03-06 09:21:18	ga_ls9c_ard_3-2-1_090086_2023-03-05_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-10 10:33:23	ga_ls9c_ard_3-2-1_102081_2023-03-10_final.stac-item
2023-03-13 11:02:43	ga_ls9c_ard_3-2-1_107077_2023-03-13_final.stac-item
2023-03-27 11:14:08	ga_ls9c_ard_3-2-1_109075_2023-03-27_final.stac-item
2023-04-03 09:40:35	ga_ls9c_ard_3-2-1_094073_2023-04-03_final.stac-item
2023-04-05 11:10:17	ga_ls9c_ard_3-2-1_108081_2023-04-05_final.stac-item
2023-04-11 10:27:58	ga_ls9c_ard_3-2-1_102068_2023-04-11_final.stac-item
2023-04-14 11:03:37	ga_ls9c_ard_3-2-1_107080_2023-04-14_final.stac-item
2023-04-28 11:13:54	ga_ls9c_ard_3-2-1_109075_2023-04-28_final.stac-item
2023-04-30 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-04-30_final.stac-item
2023-04-30 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-04-30_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-11 10:44:28	ga_ls9c_ard_3-2-1_104079_2023-05-11_final.stac-item
2023-05-30 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-05-30_final.stac-item
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final.stac-item
2023-06-03 10:49:40	ga_ls9c_ard_3-2-1_105077_2023-06-03_final.stac-item
2023-06-08 11:07:46	ga_ls9c_ard_3-2-1_108076_2023-06-08_final.stac-item
2023-06-10 10:55:23	ga_ls9c_ard_3-2-1_106076_2023-06-10_final.stac-item
2023-06-10 10:55:47	ga_ls9c_ard_3-2-1_106077_2023-06-10_final.stac-item
2023-06-18 10:09:27	ga_ls9c_ard_3-2-1_098085_2023-06-18_final.stac-item
2023-07-01 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-07-01_final.stac-item
2023-07-04 10:05:39	ga_ls9c_ard_3-2-1_098075_2023-07-04_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-11 10:15:54	ga_ls9c_ard_3-2-1_099085_2023-07-11_final.stac-item
2023-07-30 10:44:29	ga_ls9c_ard_3-2-1_104079_2023-07-30_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-03 11:57:31	ga_ls9c_ard_3-2-1_116076_2023-08-03_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-18 10:04:10	ga_ls9c_ard_3-2-1_097085_2023-11-18_final.stac-item
2023-11-20 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-11-20_final.stac-item
2023-11-24 09:23:34	ga_ls9c_ard_3-2-1_091076_2023-11-23_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