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
2021-11-05 09:37:01	ga_ls9c_ard_3-2-1_093077_2021-11-05_final.stac-item
2021-11-12 10:59:24	ga_ls9c_ard_3-2-1_106077_2021-11-12_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2022-01-28 11:10:13	ga_ls9c_ard_3-2-1_108080_2022-01-28_final.stac-item
2022-03-01 09:31:53	ga_ls9c_ard_3-2-1_092082_2022-03-01_final.stac-item
2022-03-21 10:45:12	ga_ls9c_ard_3-2-1_104080_2022-03-21_final.stac-item
2022-04-04 09:19:50	ga_ls9c_ard_3-2-1_090083_2022-04-03_final.stac-item
2022-05-08 10:44:54	ga_ls9c_ard_3-2-1_104080_2022-05-08_final.stac-item
2022-05-09 09:49:16	ga_ls9c_ard_3-2-1_095080_2022-05-09_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-06-16 10:48:14	ga_ls9c_ard_3-2-1_105073_2022-06-16_final.stac-item
2022-06-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-06-23_final.stac-item
2022-07-02 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-07-02_final.stac-item
2022-07-07 09:30:30	ga_ls9c_ard_3-2-1_092079_2022-07-07_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 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-08-21 10:39:16	ga_ls9c_ard_3-2-1_103080_2022-08-21_final.stac-item
2022-09-23 09:43:22	ga_ls9c_ard_3-2-1_094079_2022-09-23_final.stac-item
2022-10-07 09:53:20	ga_ls9c_ard_3-2-1_096073_2022-10-07_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-11 11:08:45	ga_ls9c_ard_3-2-1_108076_2022-10-11_final.stac-item
2022-10-22 10:51:27	ga_ls9c_ard_3-2-1_105079_2022-10-22_final.stac-item
2022-10-27 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-10-27_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-01 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-11-01_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-09 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-09_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-19 11:16:35	ga_ls9c_ard_3-2-1_109080_2022-11-19_final.stac-item
2022-11-24 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-11-24_final.stac-item
2022-12-26 09:56:59	ga_ls9c_ard_3-2-1_096082_2022-12-26_final.stac-item
2023-01-11 09:56:12	ga_ls9c_ard_3-2-1_096080_2023-01-11_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-02-03 09:58:03	ga_ls9c_ard_3-2-1_097069_2023-02-03_final.stac-item
2023-02-03 10:00:51	ga_ls9c_ard_3-2-1_097076_2023-02-03_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-12 09:54:17	ga_ls9c_ard_3-2-1_096075_2023-02-12_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_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 09:35:49	ga_ls9c_ard_3-2-1_093077_2023-04-28_final.stac-item
2023-04-28 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-04-28_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-04-30 11:03:06	ga_ls9c_ard_3-2-1_107079_2023-04-30_final.stac-item
2023-05-28 09:48:40	ga_ls9c_ard_3-2-1_095079_2023-05-28_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-07-15 11:27:17	ga_ls9c_ard_3-2-1_111078_2023-07-15_final.stac-item
2023-07-16 10:31:16	ga_ls9c_ard_3-2-1_102077_2023-07-16_final.stac-item
2023-07-17 09:38:02	ga_ls9c_ard_3-2-1_093083_2023-07-17_final.stac-item
2023-07-17 11:11:20	ga_ls9c_ard_3-2-1_109069_2023-07-17_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-21 10:50:12	ga_ls9c_ard_3-2-1_105078_2023-07-21_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-22 09:54:58	ga_ls9c_ard_3-2-1_096079_2023-07-22_final.stac-item
2023-07-22 09:56:34	ga_ls9c_ard_3-2-1_096083_2023-07-22_final.stac-item
2023-07-23 10:36:38	ga_ls9c_ard_3-2-1_103075_2023-07-23_final.stac-item
2023-07-23 10:37:02	ga_ls9c_ard_3-2-1_103076_2023-07-23_final.stac-item
2023-07-24 09:43:00	ga_ls9c_ard_3-2-1_094080_2023-07-24_final.stac-item
2023-07-26 09:29:51	ga_ls9c_ard_3-2-1_092078_2023-07-25_final.stac-item
2023-07-26 09:31:03	ga_ls9c_ard_3-2-1_092081_2023-07-26_final.stac-item
2023-07-27 10:11:56	ga_ls9c_ard_3-2-1_099075_2023-07-27_final.stac-item
2023-07-28 10:56:25	ga_ls9c_ard_3-2-1_106078_2023-07-28_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-08-02 09:36:09	ga_ls9c_ard_3-2-1_093078_2023-08-02_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-05 11:45:34	ga_ls9c_ard_3-2-1_114077_2023-08-05_final.stac-item
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final.stac-item
2023-10-14 11:10:09	ga_ls9c_ard_3-2-1_108080_2023-10-14_final.stac-item
2023-10-15 11:51:02	ga_ls9c_ard_3-2-1_115074_2023-10-15_final.stac-item
2023-10-16 10:56:37	ga_ls9c_ard_3-2-1_106077_2023-10-16_final.stac-item
2023-10-18 10:41:52	ga_ls9c_ard_3-2-1_104071_2023-10-18_final.stac-item
2023-10-18 10:42:16	ga_ls9c_ard_3-2-1_104072_2023-10-18_final.stac-item
2023-10-18 10:43:52	ga_ls9c_ard_3-2-1_104076_2023-10-18_final.stac-item
2023-10-19 09:49:51	ga_ls9c_ard_3-2-1_095080_2023-10-19_final.stac-item
2023-10-19 11:27:56	ga_ls9c_ard_3-2-1_111078_2023-10-19_final.stac-item
2023-10-20 10:31:31	ga_ls9c_ard_3-2-1_102076_2023-10-20_final.stac-item
2023-10-20 10:33:06	ga_ls9c_ard_3-2-1_102080_2023-10-20_final.stac-item
2023-10-21 09:36:17	ga_ls9c_ard_3-2-1_093077_2023-10-21_final.stac-item
2023-10-23 09:25:55	ga_ls9c_ard_3-2-1_091082_2023-10-22_final.stac-item
2023-10-28 09:42:01	ga_ls9c_ard_3-2-1_094076_2023-10-28_final.stac-item
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-11-01 10:58:07	ga_ls9c_ard_3-2-1_106081_2023-11-01_final.stac-item
2023-11-03 10:42:08	ga_ls9c_ard_3-2-1_104072_2023-11-03_final.stac-item
2023-11-05 10:32:12	ga_ls9c_ard_3-2-1_102078_2023-11-05_final.stac-item
2023-11-05 10:33:00	ga_ls9c_ard_3-2-1_102080_2023-11-05_final.stac-item
2023-11-14 10:22:52	ga_ls9c_ard_3-2-1_101070_2023-11-14_final.stac-item
2023-11-14 10:26:51	ga_ls9c_ard_3-2-1_101080_2023-11-14_final.stac-item
2023-11-18 10:00:58	ga_ls9c_ard_3-2-1_097077_2023-11-18_final.stac-item
2023-11-18 10:02:58	ga_ls9c_ard_3-2-1_097082_2023-11-18_final.stac-item
2023-11-19 10:42:15	ga_ls9c_ard_3-2-1_104072_2023-11-19_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_final.stac-item
2023-11-20 09:48:38	ga_ls9c_ard_3-2-1_095077_2023-11-20_final.stac-item
2023-11-21 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-11-21_final.stac-item
2023-11-21 10:33:07	ga_ls9c_ard_3-2-1_102080_2023-11-21_final.stac-item
2023-11-22 11:15:36	ga_ls9c_ard_3-2-1_109078_2023-11-22_final.stac-item
2023-11-22 11:16:23	ga_ls9c_ard_3-2-1_109080_2023-11-22_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