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
2021-11-03 09:55:45	ga_ls9c_ard_3-2-1_096077_2021-11-03_final.stac-item
2021-11-04 10:37:42	ga_ls9c_ard_3-2-1_103082_2021-11-04_final.stac-item
2021-12-08 10:37:25	ga_ls9c_ard_3-2-1_103075_2021-12-08_final.stac-item
2021-12-23 11:34:09	ga_ls9c_ard_3-2-1_112078_2021-12-23_final.stac-item
2021-12-31 10:43:30	ga_ls9c_ard_3-2-1_104075_2021-12-31_final.stac-item
2022-01-08 09:54:50	ga_ls9c_ard_3-2-1_096077_2022-01-08_final.stac-item
2022-02-04 09:38:18	ga_ls9c_ard_3-2-1_093082_2022-02-04_final.stac-item
2022-02-09 09:54:49	ga_ls9c_ard_3-2-1_096077_2022-02-09_final.stac-item
2022-02-20 11:16:16	ga_ls9c_ard_3-2-1_109080_2022-02-20_final.stac-item
2022-02-26 10:37:07	ga_ls9c_ard_3-2-1_103075_2022-02-26_final.stac-item
2022-03-05 10:43:15	ga_ls9c_ard_3-2-1_104075_2022-03-05_final.stac-item
2022-03-24 11:16:05	ga_ls9c_ard_3-2-1_109080_2022-03-24_final.stac-item
2022-04-25 11:15:52	ga_ls9c_ard_3-2-1_109080_2022-04-25_final.stac-item
2022-05-08 10:43:42	ga_ls9c_ard_3-2-1_104077_2022-05-08_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-05-27 11:15:37	ga_ls9c_ard_3-2-1_109080_2022-05-27_final.stac-item
2022-06-17 09:54:13	ga_ls9c_ard_3-2-1_096077_2022-06-17_final.stac-item
2022-06-18 10:36:42	ga_ls9c_ard_3-2-1_103075_2022-06-18_final.stac-item
2022-08-15 11:16:19	ga_ls9c_ard_3-2-1_109080_2022-08-15_final.stac-item
2022-08-30 10:31:30	ga_ls9c_ard_3-2-1_102076_2022-08-30_final.stac-item
2022-10-07 09:54:55	ga_ls9c_ard_3-2-1_096077_2022-10-07_final.stac-item
2022-10-16 11:28:31	ga_ls9c_ard_3-2-1_111079_2022-10-16_final.stac-item
2023-02-20 10:45:11	ga_ls9c_ard_3-2-1_104079_2023-02-20_final.stac-item
2023-02-20 10:45:59	ga_ls9c_ard_3-2-1_104081_2023-02-20_final.stac-item
2023-02-21 11:28:01	ga_ls9c_ard_3-2-1_111078_2023-02-21_final.stac-item
2023-02-23 09:38:19	ga_ls9c_ard_3-2-1_093082_2023-02-23_final.stac-item
2023-02-26 10:09:12	ga_ls9c_ard_3-2-1_098082_2023-02-26_final.stac-item
2023-03-09 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-03-09_final.stac-item
2023-03-18 09:44:45	ga_ls9c_ard_3-2-1_094083_2023-03-18_final.stac-item
2023-03-19 10:26:25	ga_ls9c_ard_3-2-1_101079_2023-03-19_final.stac-item
2023-03-23 10:02:51	ga_ls9c_ard_3-2-1_097082_2023-03-23_final.stac-item
2023-04-08 10:00:41	ga_ls9c_ard_3-2-1_097077_2023-04-08_final.stac-item
2023-04-08 11:39:10	ga_ls9c_ard_3-2-1_113076_2023-04-08_final.stac-item
2023-04-12 09:36:43	ga_ls9c_ard_3-2-1_093079_2023-04-12_final.stac-item
2023-04-12 11:15:36	ga_ls9c_ard_3-2-1_109079_2023-04-12_final.stac-item
2023-04-12 11:16:00	ga_ls9c_ard_3-2-1_109080_2023-04-12_final.stac-item
2023-04-19 09:44:28	ga_ls9c_ard_3-2-1_094083_2023-04-19_final.stac-item
2023-04-21 11:09:47	ga_ls9c_ard_3-2-1_108080_2023-04-21_final.stac-item
2023-05-03 09:53:28	ga_ls9c_ard_3-2-1_096075_2023-05-03_final.stac-item
2023-05-03 09:55:27	ga_ls9c_ard_3-2-1_096080_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 10:36:42	ga_ls9c_ard_3-2-1_103075_2023-05-04_final.stac-item
2023-05-04 10:37:06	ga_ls9c_ard_3-2-1_103076_2023-05-04_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-05 09:41:28	ga_ls9c_ard_3-2-1_094076_2023-05-05_final.stac-item
2023-05-05 09:44:15	ga_ls9c_ard_3-2-1_094083_2023-05-05_final.stac-item
2023-05-11 10:43:16	ga_ls9c_ard_3-2-1_104076_2023-05-11_final.stac-item
2023-05-12 09:47:38	ga_ls9c_ard_3-2-1_095076_2023-05-12_final.stac-item
2023-05-12 09:48:50	ga_ls9c_ard_3-2-1_095079_2023-05-12_final.stac-item
2023-05-12 11:27:19	ga_ls9c_ard_3-2-1_111078_2023-05-12_final.stac-item
2023-05-12 11:28:07	ga_ls9c_ard_3-2-1_111080_2023-05-12_final.stac-item
2023-05-13 10:31:41	ga_ls9c_ard_3-2-1_102078_2023-05-13_final.stac-item
2023-05-17 10:08:08	ga_ls9c_ard_3-2-1_098081_2023-05-17_final.stac-item
2023-05-19 09:53:21	ga_ls9c_ard_3-2-1_096075_2023-05-19_final.stac-item
2023-05-19 09:55:21	ga_ls9c_ard_3-2-1_096080_2023-05-19_final.stac-item
2023-05-19 11:32:14	ga_ls9c_ard_3-2-1_112075_2023-05-19_final.stac-item
2023-05-19 11:34:14	ga_ls9c_ard_3-2-1_112080_2023-05-19_final.stac-item
2023-05-20 10:36:36	ga_ls9c_ard_3-2-1_103075_2023-05-20_final.stac-item
2023-05-21 11:21:02	ga_ls9c_ard_3-2-1_110078_2023-05-21_final.stac-item
2023-06-20 09:53:06	ga_ls9c_ard_3-2-1_096075_2023-06-20_final.stac-item
2023-06-20 09:54:18	ga_ls9c_ard_3-2-1_096078_2023-06-20_final.stac-item
2023-06-20 09:54:42	ga_ls9c_ard_3-2-1_096079_2023-06-20_final.stac-item
2023-06-22 09:41:33	ga_ls9c_ard_3-2-1_094077_2023-06-22_final.stac-item
2023-06-22 09:41:57	ga_ls9c_ard_3-2-1_094078_2023-06-22_final.stac-item
2023-06-22 11:20:50	ga_ls9c_ard_3-2-1_110078_2023-06-22_final.stac-item
2023-06-29 11:26:42	ga_ls9c_ard_3-2-1_111077_2023-06-29_final.stac-item
2023-06-29 11:27:06	ga_ls9c_ard_3-2-1_111078_2023-06-29_final.stac-item
2023-07-01 11:14:47	ga_ls9c_ard_3-2-1_109078_2023-07-01_final.stac-item
2023-07-06 11:32:12	ga_ls9c_ard_3-2-1_112075_2023-07-06_final.stac-item
2023-07-07 10:36:59	ga_ls9c_ard_3-2-1_103076_2023-07-07_final.stac-item
2023-07-07 10:38:35	ga_ls9c_ard_3-2-1_103080_2023-07-07_final.stac-item
2023-07-08 09:41:47	ga_ls9c_ard_3-2-1_094077_2023-07-08_final.stac-item
2023-07-11 10:14:18	ga_ls9c_ard_3-2-1_099081_2023-07-11_final.stac-item
2023-09-06 10:08:32	ga_ls9c_ard_3-2-1_098081_2023-09-06_final.stac-item
2023-09-08 09:53:48	ga_ls9c_ard_3-2-1_096075_2023-09-08_final.stac-item
2023-09-08 09:55:24	ga_ls9c_ard_3-2-1_096079_2023-09-08_final.stac-item
2023-09-08 11:32:41	ga_ls9c_ard_3-2-1_112075_2023-09-08_final.stac-item
2023-09-09 10:37:29	ga_ls9c_ard_3-2-1_103076_2023-09-09_final.stac-item
2023-09-09 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-09_final.stac-item
2023-09-10 09:42:16	ga_ls9c_ard_3-2-1_094077_2023-09-10_final.stac-item
2023-09-10 11:21:57	ga_ls9c_ard_3-2-1_110079_2023-09-10_final.stac-item
2023-09-13 11:50:53	ga_ls9c_ard_3-2-1_115074_2023-09-13_final.stac-item
2023-09-17 11:27:46	ga_ls9c_ard_3-2-1_111078_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
2023-09-19 09:38:07	ga_ls9c_ard_3-2-1_093082_2023-09-19_final.stac-item
2023-09-19 11:15:24	ga_ls9c_ard_3-2-1_109078_2023-09-19_final.stac-item
2023-09-19 11:15:48	ga_ls9c_ard_3-2-1_109079_2023-09-19_final.stac-item
2023-09-20 11:58:16	ga_ls9c_ard_3-2-1_116077_2023-09-20_final.stac-item
2023-09-21 11:03:02	ga_ls9c_ard_3-2-1_107078_2023-09-21_final.stac-item
2023-09-25 10:37:04	ga_ls9c_ard_3-2-1_103075_2023-09-25_final.stac-item
2023-09-29 10:14:44	ga_ls9c_ard_3-2-1_099081_2023-09-29_final.stac-item
2023-10-03 09:48:05	ga_ls9c_ard_3-2-1_095076_2023-10-03_final.stac-item
2023-10-03 11:27:22	ga_ls9c_ard_3-2-1_111077_2023-10-03_final.stac-item
2023-10-04 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-10-04_final.stac-item
2023-10-05 09:37:21	ga_ls9c_ard_3-2-1_093080_2023-10-05_final.stac-item
2023-10-05 11:15:50	ga_ls9c_ard_3-2-1_109079_2023-10-05_final.stac-item
2023-10-06 10:21:01	ga_ls9c_ard_3-2-1_100081_2023-10-06_final.stac-item
2023-10-06 11:58:18	ga_ls9c_ard_3-2-1_116077_2023-10-06_final.stac-item
2023-10-10 09:53:56	ga_ls9c_ard_3-2-1_096075_2023-10-10_final.stac-item
2023-10-12 11:22:06	ga_ls9c_ard_3-2-1_110079_2023-10-12_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