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
2021-11-10 09:42:17	ga_ls9c_ard_3-2-1_094084_2021-11-10_final.stac-item
2021-11-18 10:02:22	ga_ls9c_ard_3-2-1_097075_2021-11-18_final.stac-item
2021-12-11 11:09:28	ga_ls9c_ard_3-2-1_108078_2021-12-11_final.stac-item
2021-12-16 09:49:04	ga_ls9c_ard_3-2-1_095078_2021-12-16_final.stac-item
2021-12-27 11:09:26	ga_ls9c_ard_3-2-1_108078_2021-12-27_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_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
2022-03-05 10:44:51	ga_ls9c_ard_3-2-1_104079_2022-03-05_final.stac-item
2022-03-12 10:50:38	ga_ls9c_ard_3-2-1_105078_2022-03-12_final.stac-item
2022-03-21 10:44:48	ga_ls9c_ard_3-2-1_104079_2022-03-21_final.stac-item
2022-03-22 09:48:23	ga_ls9c_ard_3-2-1_095077_2022-03-22_final.stac-item
2022-03-26 11:02:55	ga_ls9c_ard_3-2-1_107078_2022-03-26_final.stac-item
2022-03-29 09:54:07	ga_ls9c_ard_3-2-1_096076_2022-03-29_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_final.stac-item
2022-05-15 10:49:48	ga_ls9c_ard_3-2-1_105077_2022-05-15_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-26 11:27:34	ga_ls9c_ard_3-2-1_111078_2022-06-26_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-12 11:27:30	ga_ls9c_ard_3-2-1_111078_2022-07-12_final.stac-item
2022-07-14 11:15:07	ga_ls9c_ard_3-2-1_109078_2022-07-14_final.stac-item
2022-07-19 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-19_final.stac-item
2022-07-19 11:34:32	ga_ls9c_ard_3-2-1_112080_2022-07-19_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-07-24 10:14:40	ga_ls9c_ard_3-2-1_099081_2022-07-24_final.stac-item
2022-07-28 09:49:13	ga_ls9c_ard_3-2-1_095079_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
2022-08-04 11:33:10	ga_ls9c_ard_3-2-1_112076_2022-08-04_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-13 11:27:52	ga_ls9c_ard_3-2-1_111078_2022-08-13_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-20 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-08-20_final.stac-item
2022-08-22 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-08-22_final.stac-item
2022-08-29 11:28:19	ga_ls9c_ard_3-2-1_111079_2022-08-29_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-01 11:58:25	ga_ls9c_ard_3-2-1_116077_2022-09-01_final.stac-item
2022-09-07 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-09-07_final.stac-item
2022-09-14 09:49:05	ga_ls9c_ard_3-2-1_095078_2022-09-14_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-04 11:04:55	ga_ls9c_ard_3-2-1_107082_2022-10-04_final.stac-item
2022-10-07 11:33:49	ga_ls9c_ard_3-2-1_112077_2022-10-07_final.stac-item
2022-10-09 11:18:41	ga_ls9c_ard_3-2-1_110070_2022-10-09_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-10-30 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-10-30_final.stac-item
2022-12-13 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-12-13_final.stac-item
2022-12-14 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-14_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2022-12-30 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-30_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-31 09:30:19	ga_ls9c_ard_3-2-1_092077_2023-01-31_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-23 09:38:19	ga_ls9c_ard_3-2-1_093082_2023-02-23_final.stac-item
2023-02-27 10:50:52	ga_ls9c_ard_3-2-1_105078_2023-02-27_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-08 10:44:59	ga_ls9c_ard_3-2-1_104079_2023-03-08_final.stac-item
2023-03-15 10:50:45	ga_ls9c_ard_3-2-1_105078_2023-03-15_final.stac-item
2023-05-03 11:32:44	ga_ls9c_ard_3-2-1_112076_2023-05-03_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-03 11:34:20	ga_ls9c_ard_3-2-1_112080_2023-05-03_final.stac-item
2023-05-04 10:38:42	ga_ls9c_ard_3-2-1_103080_2023-05-04_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-05-18 10:49:47	ga_ls9c_ard_3-2-1_105077_2023-05-18_final.stac-item
2023-05-19 09:53:45	ga_ls9c_ard_3-2-1_096076_2023-05-19_final.stac-item
2023-05-19 09:54:33	ga_ls9c_ard_3-2-1_096078_2023-05-19_final.stac-item
2023-05-19 11:32:38	ga_ls9c_ard_3-2-1_112076_2023-05-19_final.stac-item
2023-05-19 11:33:02	ga_ls9c_ard_3-2-1_112077_2023-05-19_final.stac-item
2023-05-21 09:42:33	ga_ls9c_ard_3-2-1_094079_2023-05-21_final.stac-item
2023-05-21 11:21:26	ga_ls9c_ard_3-2-1_110079_2023-05-21_final.stac-item
2023-05-28 09:49:28	ga_ls9c_ard_3-2-1_095081_2023-05-28_final.stac-item
2023-05-28 11:27:33	ga_ls9c_ard_3-2-1_111079_2023-05-28_final.stac-item
2023-06-04 09:53:38	ga_ls9c_ard_3-2-1_096076_2023-06-04_final.stac-item
2023-06-04 11:32:31	ga_ls9c_ard_3-2-1_112076_2023-06-04_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-20 09:53:54	ga_ls9c_ard_3-2-1_096077_2023-06-20_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_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 11:32:36	ga_ls9c_ard_3-2-1_112076_2023-07-06_final.stac-item
2023-07-06 11:33:48	ga_ls9c_ard_3-2-1_112079_2023-07-06_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-22 09:53:46	ga_ls9c_ard_3-2-1_096076_2023-07-22_final.stac-item
2023-07-22 09:54:10	ga_ls9c_ard_3-2-1_096077_2023-07-22_final.stac-item
2023-07-22 09:54:34	ga_ls9c_ard_3-2-1_096078_2023-07-22_final.stac-item
2023-07-22 11:32:39	ga_ls9c_ard_3-2-1_112076_2023-07-22_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-07-22 11:33:27	ga_ls9c_ard_3-2-1_112078_2023-07-22_final.stac-item
2023-08-08 10:38:48	ga_ls9c_ard_3-2-1_103080_2023-08-08_final.stac-item
2023-08-09 11:21:16	ga_ls9c_ard_3-2-1_110078_2023-08-09_final.stac-item
2023-08-13 10:56:33	ga_ls9c_ard_3-2-1_106078_2023-08-13_final.stac-item
2023-08-16 09:48:10	ga_ls9c_ard_3-2-1_095077_2023-08-16_final.stac-item
2023-08-16 09:48:34	ga_ls9c_ard_3-2-1_095078_2023-08-16_final.stac-item
2023-10-19 09:49:27	ga_ls9c_ard_3-2-1_095079_2023-10-19_final.stac-item
2023-10-22 10:21:09	ga_ls9c_ard_3-2-1_100081_2023-10-22_final.stac-item
2023-10-25 10:50:50	ga_ls9c_ard_3-2-1_105078_2023-10-25_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