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
2021-11-01 10:12:30	ga_ls9c_ard_3-2-1_099072_2021-11-01_final.stac-item
2021-12-04 09:22:30	ga_ls9c_ard_3-2-1_091073_2021-12-03_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-17 09:46:39	ga_ls9c_ard_3-2-1_095072_2022-01-17_final.stac-item
2022-02-21 10:17:50	ga_ls9c_ard_3-2-1_100073_2022-02-21_final.stac-item
2022-02-22 09:22:12	ga_ls9c_ard_3-2-1_091073_2022-02-21_final.stac-item
2022-03-09 10:17:44	ga_ls9c_ard_3-2-1_100073_2022-03-09_final.stac-item
2022-03-25 10:17:40	ga_ls9c_ard_3-2-1_100073_2022-03-25_final.stac-item
2022-03-31 11:19:27	ga_ls9c_ard_3-2-1_110073_2022-03-31_final.stac-item
2022-04-02 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-04-02_final.stac-item
2022-04-09 11:13:14	ga_ls9c_ard_3-2-1_109073_2022-04-09_final.stac-item
2022-04-10 10:17:36	ga_ls9c_ard_3-2-1_100073_2022-04-10_final.stac-item
2022-04-11 09:21:58	ga_ls9c_ard_3-2-1_091073_2022-04-10_final.stac-item
2022-04-13 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-04-13_final.stac-item
2022-04-20 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_final.stac-item
2022-04-26 10:17:27	ga_ls9c_ard_3-2-1_100073_2022-04-26_final.stac-item
2022-04-27 09:21:50	ga_ls9c_ard_3-2-1_091073_2022-04-26_final.stac-item
2022-04-27 11:00:43	ga_ls9c_ard_3-2-1_107073_2022-04-27_final.stac-item
2022-04-29 10:48:21	ga_ls9c_ard_3-2-1_105073_2022-04-29_final.stac-item
2022-05-04 11:06:52	ga_ls9c_ard_3-2-1_108073_2022-05-04_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-05-08 10:42:06	ga_ls9c_ard_3-2-1_104073_2022-05-08_final.stac-item
2022-05-11 11:12:58	ga_ls9c_ard_3-2-1_109073_2022-05-11_final.stac-item
2022-05-12 10:17:20	ga_ls9c_ard_3-2-1_100073_2022-05-12_final.stac-item
2022-05-13 11:00:35	ga_ls9c_ard_3-2-1_107073_2022-05-13_final.stac-item
2022-05-15 10:48:12	ga_ls9c_ard_3-2-1_105073_2022-05-15_final.stac-item
2022-05-24 10:41:56	ga_ls9c_ard_3-2-1_104073_2022-05-24_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-05-30 10:04:28	ga_ls9c_ard_3-2-1_098072_2022-05-30_final.stac-item
2022-06-01 09:52:07	ga_ls9c_ard_3-2-1_096072_2022-06-01_final.stac-item
2022-06-08 09:58:18	ga_ls9c_ard_3-2-1_097072_2022-06-08_final.stac-item
2022-06-22 10:11:19	ga_ls9c_ard_3-2-1_099073_2022-06-22_final.stac-item
2022-06-26 09:46:17	ga_ls9c_ard_3-2-1_095072_2022-06-26_final.stac-item
2022-07-01 10:04:49	ga_ls9c_ard_3-2-1_098072_2022-07-01_final.stac-item
2022-07-08 10:10:58	ga_ls9c_ard_3-2-1_099072_2022-07-08_final.stac-item
2022-07-19 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-07-19_final.stac-item
2022-07-24 10:11:29	ga_ls9c_ard_3-2-1_099073_2022-07-24_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-08-09 10:11:16	ga_ls9c_ard_3-2-1_099072_2022-08-09_final.stac-item
2022-08-09 10:11:40	ga_ls9c_ard_3-2-1_099073_2022-08-09_final.stac-item
2022-08-11 09:58:56	ga_ls9c_ard_3-2-1_097072_2022-08-11_final.stac-item
2022-08-16 10:17:54	ga_ls9c_ard_3-2-1_100073_2022-08-16_final.stac-item
2022-08-17 09:22:17	ga_ls9c_ard_3-2-1_091073_2022-08-16_final.stac-item
2022-09-01 10:17:56	ga_ls9c_ard_3-2-1_100073_2022-09-01_final.stac-item
2022-09-02 09:22:19	ga_ls9c_ard_3-2-1_091073_2022-09-01_final.stac-item
2022-09-14 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-09-14_final.stac-item
2022-09-18 09:22:24	ga_ls9c_ard_3-2-1_091073_2022-09-17_final.stac-item
2022-09-19 10:05:16	ga_ls9c_ard_3-2-1_098072_2022-09-19_final.stac-item
2022-09-26 10:11:29	ga_ls9c_ard_3-2-1_099072_2022-09-26_final.stac-item
2022-09-26 10:11:53	ga_ls9c_ard_3-2-1_099073_2022-09-26_final.stac-item
2022-09-28 09:59:07	ga_ls9c_ard_3-2-1_097072_2022-09-28_final.stac-item
2022-10-03 10:17:40	ga_ls9c_ard_3-2-1_100072_2022-10-03_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 09:22:26	ga_ls9c_ard_3-2-1_091073_2022-10-03_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-12 10:11:56	ga_ls9c_ard_3-2-1_099073_2022-10-12_final.stac-item
2022-10-21 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-10-21_final.stac-item
2022-11-04 10:17:42	ga_ls9c_ard_3-2-1_100072_2022-11-04_final.stac-item
2022-11-04 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-11-04_final.stac-item
2022-11-05 09:22:30	ga_ls9c_ard_3-2-1_091073_2022-11-04_interim.stac-item
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-24 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-24_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_nrt.stac-item
2022-12-06 10:18:08	ga_ls9c_ard_3-2-1_100073_2022-12-06_final.stac-item
2022-12-06 10:18:08	ga_ls9c_ard_3-2-1_100073_2022-12-06_nrt.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_nrt.stac-item
2022-12-23 09:22:29	ga_ls9c_ard_3-2-1_091073_2022-12-22_final.stac-item
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-08 09:22:32	ga_ls9c_ard_3-2-1_091073_2023-01-07_final.stac-item
2023-01-23 10:18:02	ga_ls9c_ard_3-2-1_100073_2023-01-23_final.stac-item
2023-01-24 09:22:26	ga_ls9c_ard_3-2-1_091073_2023-01-23_final.stac-item
2023-02-01 10:11:59	ga_ls9c_ard_3-2-1_099073_2023-02-01_final.stac-item
2023-02-09 09:22:36	ga_ls9c_ard_3-2-1_091073_2023-02-08_final.stac-item
2023-03-05 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-03-05_final.stac-item
2023-03-21 10:11:38	ga_ls9c_ard_3-2-1_099073_2023-03-21_final.stac-item
2023-04-13 10:17:34	ga_ls9c_ard_3-2-1_100073_2023-04-13_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-22 10:11:22	ga_ls9c_ard_3-2-1_099073_2023-04-22_final.stac-item
2023-04-30 09:21:49	ga_ls9c_ard_3-2-1_091073_2023-04-29_final.stac-item
2023-05-16 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-05-15_final.stac-item
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final.stac-item
2023-06-17 09:21:24	ga_ls9c_ard_3-2-1_091073_2023-06-16_final.stac-item
2023-06-27 09:58:07	ga_ls9c_ard_3-2-1_097072_2023-06-27_final.stac-item
2023-07-03 09:21:35	ga_ls9c_ard_3-2-1_091073_2023-07-02_final.stac-item
2023-07-11 10:10:42	ga_ls9c_ard_3-2-1_099072_2023-07-11_final.stac-item
2023-07-18 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-07-18_final.stac-item
2023-08-03 10:17:02	ga_ls9c_ard_3-2-1_100072_2023-08-03_final.stac-item
2023-11-16 10:11:18	ga_ls9c_ard_3-2-1_099072_2023-11-16_final.stac-item
2024-02-15 11:32:07	ga_ls9c_ard_3-2-1_112073_2024-02-15_final.stac-item
2024-03-13 11:13:29	ga_ls9c_ard_3-2-1_109073_2024-03-13_final.stac-item
2024-03-15 11:01:07	ga_ls9c_ard_3-2-1_107073_2024-03-15_final.stac-item
2024-03-24 10:54:54	ga_ls9c_ard_3-2-1_106073_2024-03-24_final.stac-item
2024-03-25 11:38:08	ga_ls9c_ard_3-2-1_113073_2024-03-25_final.stac-item
2024-04-03 11:31:52	ga_ls9c_ard_3-2-1_112073_2024-04-03_final.stac-item
2024-04-10 11:38:00	ga_ls9c_ard_3-2-1_113073_2024-04-10_final.stac-item
2024-04-26 11:37:40	ga_ls9c_ard_3-2-1_113073_2024-04-26_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