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 09:39:29	ga_ls9c_ard_3-2-1_094077_2021-11-10_final.stac-item
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-11-25 09:46:28	ga_ls9c_ard_3-2-1_095076_2021-11-25_final.stac-item
2021-12-10 10:27:01	ga_ls9c_ard_3-2-1_101080_2021-12-10_final.stac-item
2022-01-07 10:50:52	ga_ls9c_ard_3-2-1_105078_2022-01-07_final.stac-item
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final.stac-item
2022-02-16 11:40:38	ga_ls9c_ard_3-2-1_113079_2022-02-16_final.stac-item
2022-02-17 10:42:12	ga_ls9c_ard_3-2-1_104072_2022-02-17_final.stac-item
2022-02-24 10:50:42	ga_ls9c_ard_3-2-1_105078_2022-02-24_final.stac-item
2022-02-27 09:42:40	ga_ls9c_ard_3-2-1_094078_2022-02-27_final.stac-item
2022-03-04 11:40:28	ga_ls9c_ard_3-2-1_113079_2022-03-04_final.stac-item
2022-03-07 10:32:53	ga_ls9c_ard_3-2-1_102080_2022-03-07_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 10:41:37	ga_ls9c_ard_3-2-1_104071_2022-03-21_final.stac-item
2022-04-16 11:22:32	ga_ls9c_ard_3-2-1_110081_2022-04-16_final.stac-item
2022-05-04 11:08:52	ga_ls9c_ard_3-2-1_108078_2022-05-04_final.stac-item
2022-05-10 10:31:43	ga_ls9c_ard_3-2-1_102078_2022-05-10_final.stac-item
2022-05-17 10:37:00	ga_ls9c_ard_3-2-1_103076_2022-05-17_final.stac-item
2022-05-18 11:23:50	ga_ls9c_ard_3-2-1_110085_2022-05-18_final.stac-item
2022-05-25 09:48:18	ga_ls9c_ard_3-2-1_095078_2022-05-25_final.stac-item
2022-05-26 10:31:34	ga_ls9c_ard_3-2-1_102078_2022-05-26_final.stac-item
2022-05-26 10:31:58	ga_ls9c_ard_3-2-1_102079_2022-05-26_final.stac-item
2022-06-01 11:33:23	ga_ls9c_ard_3-2-1_112078_2022-06-01_final.stac-item
2022-06-03 11:21:50	ga_ls9c_ard_3-2-1_110080_2022-06-03_final.stac-item
2022-06-05 11:08:17	ga_ls9c_ard_3-2-1_108077_2022-06-05_final.stac-item
2022-06-22 10:14:31	ga_ls9c_ard_3-2-1_099081_2022-06-22_final.stac-item
2022-07-05 11:22:09	ga_ls9c_ard_3-2-1_110080_2022-07-05_final.stac-item
2022-07-13 10:31:52	ga_ls9c_ard_3-2-1_102078_2022-07-13_final.stac-item
2022-07-27 10:44:01	ga_ls9c_ard_3-2-1_104077_2022-07-27_final.stac-item
2022-08-04 09:54:41	ga_ls9c_ard_3-2-1_096077_2022-08-04_final.stac-item
2022-08-09 10:16:28	ga_ls9c_ard_3-2-1_099085_2022-08-09_final.stac-item
2022-08-11 10:02:55	ga_ls9c_ard_3-2-1_097082_2022-08-11_final.stac-item
2022-08-11 11:40:13	ga_ls9c_ard_3-2-1_113078_2022-08-11_final.stac-item
2022-08-14 10:32:15	ga_ls9c_ard_3-2-1_102078_2022-08-14_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-20 09:54:48	ga_ls9c_ard_3-2-1_096077_2022-08-20_final.stac-item
2022-08-27 11:40:17	ga_ls9c_ard_3-2-1_113078_2022-08-27_final.stac-item
2022-08-30 10:31:30	ga_ls9c_ard_3-2-1_102076_2022-08-30_final.stac-item
2022-08-30 10:32:42	ga_ls9c_ard_3-2-1_102079_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
2022-09-05 09:54:48	ga_ls9c_ard_3-2-1_096077_2022-09-05_final.stac-item
2022-09-05 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-09-05_final.stac-item
2022-09-12 11:40:18	ga_ls9c_ard_3-2-1_113078_2022-09-12_final.stac-item
2022-09-13 10:43:53	ga_ls9c_ard_3-2-1_104076_2022-09-13_final.stac-item
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final.stac-item
2022-09-25 11:09:30	ga_ls9c_ard_3-2-1_108078_2022-09-25_final.stac-item
2022-09-28 11:39:36	ga_ls9c_ard_3-2-1_113076_2022-09-28_final.stac-item
2022-10-06 10:51:21	ga_ls9c_ard_3-2-1_105079_2022-10-06_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-08 10:39:00	ga_ls9c_ard_3-2-1_103079_2022-10-08_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-11-05 09:27:17	ga_ls9c_ard_3-2-1_091085_2022-11-04_final.stac-item
2022-11-15 11:40:55	ga_ls9c_ard_3-2-1_113079_2022-11-15_final.stac-item
2022-11-20 10:18:34	ga_ls9c_ard_3-2-1_100074_2022-11-20_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2023-01-13 09:43:02	ga_ls9c_ard_3-2-1_094078_2023-01-13_final.stac-item
2023-01-22 09:37:09	ga_ls9c_ard_3-2-1_093079_2023-01-22_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-02-19 11:40:49	ga_ls9c_ard_3-2-1_113079_2023-02-19_final.stac-item
2023-02-20 10:45:11	ga_ls9c_ard_3-2-1_104079_2023-02-20_final.stac-item
2023-02-21 09:49:08	ga_ls9c_ard_3-2-1_095078_2023-02-21_final.stac-item
2023-03-16 11:33:13	ga_ls9c_ard_3-2-1_112076_2023-03-16_final.stac-item
2023-03-18 09:42:45	ga_ls9c_ard_3-2-1_094078_2023-03-18_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-03-24 10:44:53	ga_ls9c_ard_3-2-1_104079_2023-03-24_final.stac-item
2023-04-09 10:45:32	ga_ls9c_ard_3-2-1_104081_2023-04-09_final.stac-item
2023-04-11 10:32:21	ga_ls9c_ard_3-2-1_102079_2023-04-11_final.stac-item
2023-04-17 09:54:26	ga_ls9c_ard_3-2-1_096077_2023-04-17_final.stac-item
2023-04-18 10:39:41	ga_ls9c_ard_3-2-1_103082_2023-04-18_final.stac-item
2023-04-26 11:27:53	ga_ls9c_ard_3-2-1_111079_2023-04-26_final.stac-item
2023-04-27 10:32:15	ga_ls9c_ard_3-2-1_102079_2023-04-27_final.stac-item
2023-05-07 11:08:00	ga_ls9c_ard_3-2-1_108076_2023-05-07_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-14 09:33:16	ga_ls9c_ard_3-2-1_093071_2023-05-14_final.stac-item
2023-05-20 10:37:00	ga_ls9c_ard_3-2-1_103076_2023-05-20_final.stac-item
2023-05-21 09:42:33	ga_ls9c_ard_3-2-1_094079_2023-05-21_final.stac-item
2023-05-26 10:02:14	ga_ls9c_ard_3-2-1_097082_2023-05-26_final.stac-item
2023-05-26 11:39:31	ga_ls9c_ard_3-2-1_113078_2023-05-26_final.stac-item
2023-05-28 11:27:33	ga_ls9c_ard_3-2-1_111079_2023-05-28_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-06-13 11:27:50	ga_ls9c_ard_3-2-1_111080_2023-06-13_final.stac-item
2023-06-18 10:08:15	ga_ls9c_ard_3-2-1_098082_2023-06-18_final.stac-item
2023-06-20 09:53:06	ga_ls9c_ard_3-2-1_096075_2023-06-20_final.stac-item
2023-06-22 11:21:37	ga_ls9c_ard_3-2-1_110080_2023-06-22_final.stac-item
2023-06-25 10:14:02	ga_ls9c_ard_3-2-1_099081_2023-06-25_final.stac-item
2023-06-26 09:18:49	ga_ls9c_ard_3-2-1_090082_2023-06-25_final.stac-item
2023-06-27 11:39:24	ga_ls9c_ard_3-2-1_113078_2023-06-27_final.stac-item
2023-07-06 09:54:07	ga_ls9c_ard_3-2-1_096077_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 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-11 10:26:44	ga_ls9c_ard_3-2-1_101080_2023-09-11_final.stac-item
2023-09-17 11:28:10	ga_ls9c_ard_3-2-1_111079_2023-09-17_final.stac-item
2023-09-18 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-09-18_final.stac-item
2023-09-22 10:08:36	ga_ls9c_ard_3-2-1_098081_2023-09-22_final.stac-item
2023-09-24 11:33:06	ga_ls9c_ard_3-2-1_112076_2023-09-24_final.stac-item
2023-09-25 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-25_final.stac-item
2023-10-01 11:39:18	ga_ls9c_ard_3-2-1_113076_2023-10-01_final.stac-item
2023-10-03 09:48:29	ga_ls9c_ard_3-2-1_095077_2023-10-03_final.stac-item
2023-10-08 10:08:40	ga_ls9c_ard_3-2-1_098081_2023-10-08_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