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
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-05 11:14:05	ga_ls9c_ard_3-2-1_109073_2021-11-05_final.stac-item
2021-11-09 10:36:36	ga_ls9c_ard_3-2-1_103073_2021-11-09_final.stac-item
2021-11-10 11:16:34	ga_ls9c_ard_3-2-1_110073_2021-11-10_final.stac-item
2021-11-12 10:57:49	ga_ls9c_ard_3-2-1_106073_2021-11-12_final.stac-item
2021-11-14 10:39:04	ga_ls9c_ard_3-2-1_103073_2021-11-14_final.stac-item
2021-11-22 11:02:44	ga_ls9c_ard_3-2-1_107073_2021-11-22_final.stac-item
2021-12-06 10:48:36	ga_ls9c_ard_3-2-1_105072_2021-12-06_final.stac-item
2021-12-13 10:55:06	ga_ls9c_ard_3-2-1_106073_2021-12-13_final.stac-item
2021-12-15 10:42:19	ga_ls9c_ard_3-2-1_104072_2021-12-15_final.stac-item
2021-12-15 10:42:43	ga_ls9c_ard_3-2-1_104073_2021-12-15_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-22 10:48:29	ga_ls9c_ard_3-2-1_105072_2021-12-22_final.stac-item
2021-12-29 10:54:40	ga_ls9c_ard_3-2-1_106072_2021-12-29_final.stac-item
2022-01-16 10:42:16	ga_ls9c_ard_3-2-1_104072_2022-01-16_final.stac-item
2022-01-16 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-01-16_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-02-01 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-02-01_final.stac-item
2022-02-15 10:54:35	ga_ls9c_ard_3-2-1_106072_2022-02-15_final.stac-item
2022-02-17 10:42:12	ga_ls9c_ard_3-2-1_104072_2022-02-17_final.stac-item
2022-03-21 10:42:01	ga_ls9c_ard_3-2-1_104072_2022-03-21_final.stac-item
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final.stac-item
2022-04-02 09:28:12	ga_ls9c_ard_3-2-1_092073_2022-04-01_final.stac-item
2022-04-22 10:41:46	ga_ls9c_ard_3-2-1_104072_2022-04-22_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-08 10:41:42	ga_ls9c_ard_3-2-1_104072_2022-05-08_final.stac-item
2022-05-15 10:47:48	ga_ls9c_ard_3-2-1_105072_2022-05-15_final.stac-item
2022-05-22 10:53:54	ga_ls9c_ard_3-2-1_106072_2022-05-22_final.stac-item
2022-05-27 11:12:50	ga_ls9c_ard_3-2-1_109073_2022-05-27_final.stac-item
2022-05-29 11:00:29	ga_ls9c_ard_3-2-1_107073_2022-05-29_final.stac-item
2022-06-07 10:53:55	ga_ls9c_ard_3-2-1_106072_2022-06-07_final.stac-item
2022-06-09 10:41:34	ga_ls9c_ard_3-2-1_104072_2022-06-09_final.stac-item
2022-06-12 11:12:54	ga_ls9c_ard_3-2-1_109073_2022-06-12_final.stac-item
2022-06-14 11:00:34	ga_ls9c_ard_3-2-1_107073_2022-06-14_final.stac-item
2022-06-25 10:41:55	ga_ls9c_ard_3-2-1_104072_2022-06-25_final.stac-item
2022-06-25 10:42:19	ga_ls9c_ard_3-2-1_104073_2022-06-25_final.stac-item
2022-06-28 09:34:19	ga_ls9c_ard_3-2-1_093073_2022-06-28_final.stac-item
2022-06-28 11:13:12	ga_ls9c_ard_3-2-1_109073_2022-06-28_final.stac-item
2022-06-30 11:00:51	ga_ls9c_ard_3-2-1_107073_2022-06-30_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-07 09:28:07	ga_ls9c_ard_3-2-1_092073_2022-07-06_final.stac-item
2022-07-09 10:54:37	ga_ls9c_ard_3-2-1_106073_2022-07-09_final.stac-item
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final.stac-item
2022-07-14 11:13:07	ga_ls9c_ard_3-2-1_109073_2022-07-14_final.stac-item
2022-07-23 09:28:12	ga_ls9c_ard_3-2-1_092073_2022-07-22_final.stac-item
2022-07-25 10:54:21	ga_ls9c_ard_3-2-1_106072_2022-07-25_final.stac-item
2022-07-27 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-07-27_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-03 10:48:18	ga_ls9c_ard_3-2-1_105072_2022-08-03_final.stac-item
2022-08-05 10:36:21	ga_ls9c_ard_3-2-1_103073_2022-08-05_final.stac-item
2022-08-08 09:28:24	ga_ls9c_ard_3-2-1_092073_2022-08-07_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-08-15 11:13:31	ga_ls9c_ard_3-2-1_109073_2022-08-15_final.stac-item
2022-08-26 10:54:37	ga_ls9c_ard_3-2-1_106072_2022-08-26_final.stac-item
2022-08-28 10:42:16	ga_ls9c_ard_3-2-1_104072_2022-08-28_final.stac-item
2022-08-28 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-08-28_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-08-31 11:13:34	ga_ls9c_ard_3-2-1_109073_2022-08-31_final.stac-item
2022-09-06 10:36:28	ga_ls9c_ard_3-2-1_103073_2022-09-06_final.stac-item
2022-09-07 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-09-07_final.stac-item
2022-09-11 10:54:38	ga_ls9c_ard_3-2-1_106072_2022-09-11_final.stac-item
2022-09-29 10:42:47	ga_ls9c_ard_3-2-1_104073_2022-09-29_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-06 10:48:33	ga_ls9c_ard_3-2-1_105072_2022-10-06_final.stac-item
2022-10-09 09:41:00	ga_ls9c_ard_3-2-1_094073_2022-10-09_final.stac-item
2022-10-13 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-10-13_final.stac-item
2022-10-15 10:42:52	ga_ls9c_ard_3-2-1_104073_2022-10-15_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-20 11:01:25	ga_ls9c_ard_3-2-1_107073_2022-10-20_final.stac-item
2022-10-27 09:28:43	ga_ls9c_ard_3-2-1_092073_2022-10-26_final.stac-item
2022-11-25 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-25_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 09:28:43	ga_ls9c_ard_3-2-1_092073_2022-12-13_final.stac-item
2022-12-21 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-12-21_final.stac-item
2022-12-28 09:41:03	ga_ls9c_ard_3-2-1_094073_2022-12-28_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-22 11:13:38	ga_ls9c_ard_3-2-1_109073_2023-01-22_final.stac-item
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final.stac-item
2023-02-07 09:34:57	ga_ls9c_ard_3-2-1_093073_2023-02-07_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-04-05 09:28:13	ga_ls9c_ard_3-2-1_092073_2023-04-04_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-06-17 11:00:17	ga_ls9c_ard_3-2-1_107073_2023-06-17_final.stac-item
2023-06-21 10:35:34	ga_ls9c_ard_3-2-1_103073_2023-06-21_final.stac-item
2023-06-28 10:41:49	ga_ls9c_ard_3-2-1_104073_2023-06-28_final.stac-item
2023-07-01 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-07-01_final.stac-item
2023-07-03 11:00:28	ga_ls9c_ard_3-2-1_107073_2023-07-03_final.stac-item
2023-07-12 10:54:22	ga_ls9c_ard_3-2-1_106073_2023-07-12_final.stac-item
2023-07-17 11:12:56	ga_ls9c_ard_3-2-1_109073_2023-07-17_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-18 11:13:05	ga_ls9c_ard_3-2-1_109073_2023-08-18_final.stac-item
2023-09-03 11:13:17	ga_ls9c_ard_3-2-1_109073_2023-09-03_final.stac-item
2023-09-19 11:13:24	ga_ls9c_ard_3-2-1_109073_2023-09-19_final.stac-item
2023-10-05 11:13:26	ga_ls9c_ard_3-2-1_109073_2023-10-05_final.stac-item
2023-10-21 11:13:35	ga_ls9c_ard_3-2-1_109073_2023-10-21_final.stac-item
2023-11-06 11:13:29	ga_ls9c_ard_3-2-1_109073_2023-11-06_final.stac-item
2024-01-09 11:13:35	ga_ls9c_ard_3-2-1_109073_2024-01-09_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