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
2021-11-08 09:57:50	ga_ls9c_ard_3-2-1_097076_2021-11-08_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-16 09:48:16	ga_ls9c_ard_3-2-1_095076_2021-12-16_final.stac-item
2021-12-30 10:00:39	ga_ls9c_ard_3-2-1_097076_2021-12-30_final.stac-item
2022-01-01 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-01-01_final.stac-item
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final.stac-item
2022-01-17 09:48:15	ga_ls9c_ard_3-2-1_095076_2022-01-17_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-01-24 09:54:27	ga_ls9c_ard_3-2-1_096076_2022-01-24_final.stac-item
2022-02-02 09:48:16	ga_ls9c_ard_3-2-1_095076_2022-02-02_final.stac-item
2022-02-18 09:48:10	ga_ls9c_ard_3-2-1_095076_2022-02-18_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-02-25 09:54:16	ga_ls9c_ard_3-2-1_096076_2022-02-25_final.stac-item
2022-03-06 09:48:02	ga_ls9c_ard_3-2-1_095076_2022-03-06_final.stac-item
2022-03-22 09:47:59	ga_ls9c_ard_3-2-1_095076_2022-03-22_final.stac-item
2022-04-06 10:43:33	ga_ls9c_ard_3-2-1_104076_2022-04-06_final.stac-item
2022-04-26 11:57:32	ga_ls9c_ard_3-2-1_116076_2022-04-26_final.stac-item
2022-04-29 10:49:33	ga_ls9c_ard_3-2-1_105076_2022-04-29_final.stac-item
2022-04-30 09:53:55	ga_ls9c_ard_3-2-1_096076_2022-04-30_final.stac-item
2022-05-28 11:57:18	ga_ls9c_ard_3-2-1_116076_2022-05-28_final.stac-item
2022-06-01 09:53:42	ga_ls9c_ard_3-2-1_096076_2022-06-01_final.stac-item
2022-06-02 10:36:58	ga_ls9c_ard_3-2-1_103076_2022-06-02_final.stac-item
2022-06-06 10:12:15	ga_ls9c_ard_3-2-1_099076_2022-06-06_final.stac-item
2022-06-10 09:47:33	ga_ls9c_ard_3-2-1_095076_2022-06-10_final.stac-item
2022-06-17 09:53:49	ga_ls9c_ard_3-2-1_096076_2022-06-17_final.stac-item
2022-06-18 10:37:06	ga_ls9c_ard_3-2-1_103076_2022-06-18_final.stac-item
2022-06-20 10:24:49	ga_ls9c_ard_3-2-1_101076_2022-06-20_final.stac-item
2022-06-26 09:47:53	ga_ls9c_ard_3-2-1_095076_2022-06-26_final.stac-item
2022-06-29 11:57:40	ga_ls9c_ard_3-2-1_116076_2022-06-29_final.stac-item
2022-07-03 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-03_final.stac-item
2022-07-10 10:00:11	ga_ls9c_ard_3-2-1_097076_2022-07-10_final.stac-item
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final.stac-item
2022-07-28 09:48:01	ga_ls9c_ard_3-2-1_095076_2022-07-28_final.stac-item
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final.stac-item
2022-08-10 10:56:08	ga_ls9c_ard_3-2-1_106076_2022-08-10_final.stac-item
2022-08-11 10:00:32	ga_ls9c_ard_3-2-1_097076_2022-08-11_final.stac-item
2022-08-13 09:48:11	ga_ls9c_ard_3-2-1_095076_2022-08-13_final.stac-item
2022-08-16 11:57:59	ga_ls9c_ard_3-2-1_116076_2022-08-16_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-27 10:00:36	ga_ls9c_ard_3-2-1_097076_2022-08-27_final.stac-item
2022-08-28 10:43:51	ga_ls9c_ard_3-2-1_104076_2022-08-28_final.stac-item
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final.stac-item
2022-09-05 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-09-05_final.stac-item
2022-09-14 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-09-14_final.stac-item
2022-09-17 11:58:05	ga_ls9c_ard_3-2-1_116076_2022-09-17_final.stac-item
2022-09-21 09:54:31	ga_ls9c_ard_3-2-1_096076_2022-09-21_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-09-29 10:43:59	ga_ls9c_ard_3-2-1_104076_2022-09-29_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-15 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-15_final.stac-item
2022-10-16 09:48:26	ga_ls9c_ard_3-2-1_095076_2022-10-16_final.stac-item
2022-10-19 10:19:21	ga_ls9c_ard_3-2-1_100076_2022-10-19_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-23 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-10-23_final.stac-item
2022-10-24 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-10-24_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-10-30 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-10-30_final.stac-item
2022-11-01 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-11-01_final.stac-item
2022-11-04 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-11-04_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_nrt.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_nrt.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_nrt.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-13 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-12-13_final.stac-item
2022-12-17 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-12-17_final.stac-item
2022-12-19 09:48:26	ga_ls9c_ard_3-2-1_095076_2022-12-19_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-26 09:54:35	ga_ls9c_ard_3-2-1_096076_2022-12-26_final.stac-item
2023-01-02 10:00:49	ga_ls9c_ard_3-2-1_097076_2023-01-02_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-23 10:19:14	ga_ls9c_ard_3-2-1_100076_2023-01-23_final.stac-item
2023-01-27 09:54:35	ga_ls9c_ard_3-2-1_096076_2023-01-27_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-21 09:48:20	ga_ls9c_ard_3-2-1_095076_2023-02-21_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-21 10:12:50	ga_ls9c_ard_3-2-1_099076_2023-03-21_final.stac-item
2023-03-23 10:00:27	ga_ls9c_ard_3-2-1_097076_2023-03-23_final.stac-item
2023-04-01 09:54:08	ga_ls9c_ard_3-2-1_096076_2023-04-01_final.stac-item
2023-04-17 09:54:02	ga_ls9c_ard_3-2-1_096076_2023-04-17_final.stac-item
2023-04-20 10:24:56	ga_ls9c_ard_3-2-1_101076_2023-04-20_final.stac-item
2023-05-12 09:47:38	ga_ls9c_ard_3-2-1_095076_2023-05-12_final.stac-item
2023-06-16 11:57:06	ga_ls9c_ard_3-2-1_116076_2023-06-16_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-23 10:24:24	ga_ls9c_ard_3-2-1_101076_2023-06-23_final.stac-item
2023-06-29 09:47:25	ga_ls9c_ard_3-2-1_095076_2023-06-29_final.stac-item
2023-07-02 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-07-02_final.stac-item
2023-07-06 09:53:43	ga_ls9c_ard_3-2-1_096076_2023-07-06_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-09-04 11:57:45	ga_ls9c_ard_3-2-1_116076_2023-09-04_final.stac-item
2023-09-08 09:54:12	ga_ls9c_ard_3-2-1_096076_2023-09-08_final.stac-item
2023-09-20 11:57:52	ga_ls9c_ard_3-2-1_116076_2023-09-20_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