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
2021-11-18 10:02:22	ga_ls9c_ard_3-2-1_097075_2021-11-18_final.stac-item
2021-12-16 11:28:21	ga_ls9c_ard_3-2-1_111079_2021-12-16_final.stac-item
2022-01-09 10:37:18	ga_ls9c_ard_3-2-1_103075_2022-01-09_final.stac-item
2022-01-27 10:26:57	ga_ls9c_ard_3-2-1_101080_2022-01-27_final.stac-item
2022-02-20 09:38:11	ga_ls9c_ard_3-2-1_093082_2022-02-20_final.stac-item
2022-02-24 10:50:42	ga_ls9c_ard_3-2-1_105078_2022-02-24_final.stac-item
2022-03-23 10:31:14	ga_ls9c_ard_3-2-1_102076_2022-03-23_final.stac-item
2022-03-24 11:15:41	ga_ls9c_ard_3-2-1_109079_2022-03-24_final.stac-item
2022-03-26 11:02:55	ga_ls9c_ard_3-2-1_107078_2022-03-26_final.stac-item
2022-03-28 10:50:32	ga_ls9c_ard_3-2-1_105078_2022-03-28_final.stac-item
2022-03-29 09:54:31	ga_ls9c_ard_3-2-1_096077_2022-03-29_final.stac-item
2022-04-01 10:26:37	ga_ls9c_ard_3-2-1_101080_2022-04-01_final.stac-item
2022-04-14 09:54:02	ga_ls9c_ard_3-2-1_096076_2022-04-14_final.stac-item
2022-04-14 09:54:26	ga_ls9c_ard_3-2-1_096077_2022-04-14_final.stac-item
2022-04-14 11:33:43	ga_ls9c_ard_3-2-1_112078_2022-04-14_final.stac-item
2022-04-21 11:39:00	ga_ls9c_ard_3-2-1_113076_2022-04-21_final.stac-item
2022-04-23 11:27:02	ga_ls9c_ard_3-2-1_111077_2022-04-23_final.stac-item
2022-04-25 11:15:04	ga_ls9c_ard_3-2-1_109078_2022-04-25_final.stac-item
2022-05-11 11:14:58	ga_ls9c_ard_3-2-1_109078_2022-05-11_final.stac-item
2022-05-26 10:30:46	ga_ls9c_ard_3-2-1_102076_2022-05-26_final.stac-item
2022-06-01 11:34:11	ga_ls9c_ard_3-2-1_112080_2022-06-01_final.stac-item
2022-06-17 09:54:37	ga_ls9c_ard_3-2-1_096078_2022-06-17_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-27 10:32:20	ga_ls9c_ard_3-2-1_102079_2022-06-27_final.stac-item
2022-07-10 11:39:04	ga_ls9c_ard_3-2-1_113076_2022-07-10_final.stac-item
2022-07-12 11:27:06	ga_ls9c_ard_3-2-1_111077_2022-07-12_final.stac-item
2022-07-13 10:31:04	ga_ls9c_ard_3-2-1_102076_2022-07-13_final.stac-item
2022-07-19 09:54:27	ga_ls9c_ard_3-2-1_096077_2022-07-19_final.stac-item
2022-07-21 11:21:49	ga_ls9c_ard_3-2-1_110079_2022-07-21_final.stac-item
2022-08-05 10:37:09	ga_ls9c_ard_3-2-1_103075_2022-08-05_final.stac-item
2022-08-11 11:39:25	ga_ls9c_ard_3-2-1_113076_2022-08-11_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-21 10:37:16	ga_ls9c_ard_3-2-1_103075_2022-08-21_final.stac-item
2022-08-27 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-08-27_final.stac-item
2022-08-31 11:16:21	ga_ls9c_ard_3-2-1_109080_2022-08-31_final.stac-item
2022-09-14 11:27:58	ga_ls9c_ard_3-2-1_111078_2022-09-14_final.stac-item
2022-09-15 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-09-15_final.stac-item
2022-09-22 10:40:10	ga_ls9c_ard_3-2-1_103082_2022-09-22_final.stac-item
2022-09-23 11:22:15	ga_ls9c_ard_3-2-1_110079_2022-09-23_final.stac-item
2022-10-16 11:28:07	ga_ls9c_ard_3-2-1_111078_2022-10-16_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-23 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-10-23_final.stac-item
2022-10-30 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-10-30_final.stac-item
2022-11-01 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-11-01_final.stac-item
2022-11-17 09:49:40	ga_ls9c_ard_3-2-1_095079_2022-11-17_final.stac-item
2022-11-17 11:28:33	ga_ls9c_ard_3-2-1_111079_2022-11-17_final.stac-item
2022-11-26 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-26_final.stac-item
2022-11-27 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-11-27_final.stac-item
2022-12-09 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-12-09_final.stac-item
2022-12-26 11:34:16	ga_ls9c_ard_3-2-1_112078_2022-12-26_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-02-21 09:49:32	ga_ls9c_ard_3-2-1_095079_2023-02-21_final.stac-item
2023-03-09 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-03-09_final.stac-item
2023-03-18 11:21:38	ga_ls9c_ard_3-2-1_110078_2023-03-18_final.stac-item
2023-03-18 11:22:02	ga_ls9c_ard_3-2-1_110079_2023-03-18_final.stac-item
2023-03-23 11:39:20	ga_ls9c_ard_3-2-1_113076_2023-03-23_final.stac-item
2023-04-09 10:44:44	ga_ls9c_ard_3-2-1_104079_2023-04-09_final.stac-item
2023-04-10 09:47:55	ga_ls9c_ard_3-2-1_095076_2023-04-10_final.stac-item
2023-04-17 09:54:02	ga_ls9c_ard_3-2-1_096076_2023-04-17_final.stac-item
2023-04-19 11:21:45	ga_ls9c_ard_3-2-1_110079_2023-04-19_final.stac-item
2023-04-22 10:14:33	ga_ls9c_ard_3-2-1_099081_2023-04-22_final.stac-item
2023-04-28 11:15:30	ga_ls9c_ard_3-2-1_109079_2023-04-28_final.stac-item
2023-05-05 11:21:33	ga_ls9c_ard_3-2-1_110079_2023-05-05_final.stac-item
2023-05-06 10:25:56	ga_ls9c_ard_3-2-1_101079_2023-05-06_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-11 10:44:04	ga_ls9c_ard_3-2-1_104078_2023-05-11_final.stac-item
2023-05-12 09:48:02	ga_ls9c_ard_3-2-1_095077_2023-05-12_final.stac-item
2023-05-12 09:49:14	ga_ls9c_ard_3-2-1_095080_2023-05-12_final.stac-item
2023-05-12 11:26:55	ga_ls9c_ard_3-2-1_111077_2023-05-12_final.stac-item
2023-05-13 10:32:05	ga_ls9c_ard_3-2-1_102079_2023-05-13_final.stac-item
2023-05-15 10:19:43	ga_ls9c_ard_3-2-1_100079_2023-05-15_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-05-24 10:14:12	ga_ls9c_ard_3-2-1_099081_2023-05-24_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-05-28 09:48:40	ga_ls9c_ard_3-2-1_095079_2023-05-28_final.stac-item
2023-05-28 11:27:09	ga_ls9c_ard_3-2-1_111078_2023-05-28_final.stac-item
2023-05-30 09:36:19	ga_ls9c_ard_3-2-1_093079_2023-05-30_final.stac-item
2023-06-18 10:08:15	ga_ls9c_ard_3-2-1_098082_2023-06-18_final.stac-item
2023-06-29 11:27:30	ga_ls9c_ard_3-2-1_111079_2023-06-29_final.stac-item
2023-07-02 11:57:40	ga_ls9c_ard_3-2-1_116077_2023-07-02_final.stac-item
2023-07-06 09:53:19	ga_ls9c_ard_3-2-1_096075_2023-07-06_final.stac-item
2023-07-06 09:54:07	ga_ls9c_ard_3-2-1_096077_2023-07-06_final.stac-item
2023-07-06 11:33:00	ga_ls9c_ard_3-2-1_112077_2023-07-06_final.stac-item
2023-09-06 10:08:56	ga_ls9c_ard_3-2-1_098082_2023-09-06_final.stac-item
2023-09-08 09:55:00	ga_ls9c_ard_3-2-1_096078_2023-09-08_final.stac-item
2023-09-09 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-09_final.stac-item
2023-09-10 09:42:40	ga_ls9c_ard_3-2-1_094078_2023-09-10_final.stac-item
2023-09-10 09:43:04	ga_ls9c_ard_3-2-1_094079_2023-09-10_final.stac-item
2023-09-10 11:21:33	ga_ls9c_ard_3-2-1_110078_2023-09-10_final.stac-item
2023-09-15 11:39:19	ga_ls9c_ard_3-2-1_113076_2023-09-15_final.stac-item
2023-09-17 09:49:17	ga_ls9c_ard_3-2-1_095079_2023-09-17_final.stac-item
2023-09-23 10:50:39	ga_ls9c_ard_3-2-1_105078_2023-09-23_final.stac-item
2023-09-24 11:33:54	ga_ls9c_ard_3-2-1_112078_2023-09-24_final.stac-item
2023-09-26 11:21:31	ga_ls9c_ard_3-2-1_110078_2023-09-26_final.stac-item
2023-09-27 10:26:41	ga_ls9c_ard_3-2-1_101080_2023-09-27_final.stac-item
2023-10-01 10:00:01	ga_ls9c_ard_3-2-1_097075_2023-10-01_final.stac-item
2023-10-03 11:27:46	ga_ls9c_ard_3-2-1_111078_2023-10-03_final.stac-item
2023-10-10 11:33:13	ga_ls9c_ard_3-2-1_112076_2023-10-10_final.stac-item
2023-10-10 11:34:49	ga_ls9c_ard_3-2-1_112080_2023-10-10_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