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 11:34:01	ga_ls9c_ard_3-2-1_112076_2021-11-03_final.stac-item
2021-11-05 09:40:36	ga_ls9c_ard_3-2-1_093086_2021-11-05_final.stac-item
2021-12-07 09:52:58	ga_ls9c_ard_3-2-1_096072_2021-12-07_final.stac-item
2021-12-10 10:24:38	ga_ls9c_ard_3-2-1_101074_2021-12-10_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2022-01-13 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-01-13_final.stac-item
2022-02-10 10:37:17	ga_ls9c_ard_3-2-1_103075_2022-02-10_final.stac-item
2022-02-10 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-02-10_final.stac-item
2022-05-09 09:47:40	ga_ls9c_ard_3-2-1_095076_2022-05-09_final.stac-item
2022-06-09 10:43:33	ga_ls9c_ard_3-2-1_104077_2022-06-09_final.stac-item
2022-07-07 09:30:06	ga_ls9c_ard_3-2-1_092078_2022-07-07_final.stac-item
2022-07-16 11:03:11	ga_ls9c_ard_3-2-1_107079_2022-07-16_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-08-17 09:26:17	ga_ls9c_ard_3-2-1_091083_2022-08-16_final.stac-item
2022-09-02 09:26:18	ga_ls9c_ard_3-2-1_091083_2022-09-01_final.stac-item
2022-10-24 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-10-24_final.stac-item
2022-10-28 10:15:10	ga_ls9c_ard_3-2-1_099081_2022-10-28_final.stac-item
2022-11-10 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-10_final.stac-item
2023-05-01 10:08:39	ga_ls9c_ard_3-2-1_098082_2023-05-01_final.stac-item
2023-05-01 10:09:03	ga_ls9c_ard_3-2-1_098083_2023-05-01_final.stac-item
2023-05-01 11:44:21	ga_ls9c_ard_3-2-1_114074_2023-05-01_final.stac-item
2023-05-01 11:46:44	ga_ls9c_ard_3-2-1_114080_2023-05-01_final.stac-item
2023-05-02 10:46:42	ga_ls9c_ard_3-2-1_105069_2023-05-02_final.stac-item
2023-05-02 10:48:42	ga_ls9c_ard_3-2-1_105074_2023-05-02_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 11:32:44	ga_ls9c_ard_3-2-1_112076_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
2023-05-05 09:41:52	ga_ls9c_ard_3-2-1_094077_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
2023-05-07 11:09:11	ga_ls9c_ard_3-2-1_108079_2023-05-07_final.stac-item
2023-05-08 10:10:23	ga_ls9c_ard_3-2-1_099071_2023-05-08_final.stac-item
2023-05-08 10:11:34	ga_ls9c_ard_3-2-1_099074_2023-05-08_final.stac-item
2023-05-08 10:12:46	ga_ls9c_ard_3-2-1_099077_2023-05-08_final.stac-item
2023-05-08 11:50:27	ga_ls9c_ard_3-2-1_115074_2023-05-08_final.stac-item
2023-05-09 10:54:26	ga_ls9c_ard_3-2-1_106073_2023-05-09_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-09 10:56:26	ga_ls9c_ard_3-2-1_106078_2023-05-09_final.stac-item
2023-05-10 11:38:30	ga_ls9c_ard_3-2-1_113075_2023-05-10_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 11:26:31	ga_ls9c_ard_3-2-1_111076_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
2023-05-14 09:38:03	ga_ls9c_ard_3-2-1_093083_2023-05-14_final.stac-item
2023-05-14 11:11:21	ga_ls9c_ard_3-2-1_109069_2023-05-14_final.stac-item
2023-05-14 11:14:09	ga_ls9c_ard_3-2-1_109076_2023-05-14_final.stac-item
2023-05-16 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-05-15_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-17 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-05-17_final.stac-item
2023-05-20 10:36:36	ga_ls9c_ard_3-2-1_103075_2023-05-20_final.stac-item
2023-05-20 10:37:47	ga_ls9c_ard_3-2-1_103078_2023-05-20_final.stac-item
2023-05-20 10:38:11	ga_ls9c_ard_3-2-1_103079_2023-05-20_final.stac-item
2023-09-04 10:22:04	ga_ls9c_ard_3-2-1_100084_2023-09-04_final.stac-item
2023-09-05 11:01:21	ga_ls9c_ard_3-2-1_107074_2023-09-05_final.stac-item
2023-09-08 09:55:48	ga_ls9c_ard_3-2-1_096080_2023-09-08_final.stac-item
2023-09-08 09:56:36	ga_ls9c_ard_3-2-1_096082_2023-09-08_final.stac-item
2023-09-08 11:33:05	ga_ls9c_ard_3-2-1_112076_2023-09-08_final.stac-item
2023-09-08 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-09 10:36:41	ga_ls9c_ard_3-2-1_103074_2023-09-09_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 11:20:45	ga_ls9c_ard_3-2-1_110076_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
2023-09-12 09:30:43	ga_ls9c_ard_3-2-1_092079_2023-09-12_final.stac-item
2023-09-12 09:32:19	ga_ls9c_ard_3-2-1_092083_2023-09-12_final.stac-item
2023-09-12 11:09:36	ga_ls9c_ard_3-2-1_108079_2023-09-12_final.stac-item
2023-09-17 09:50:05	ga_ls9c_ard_3-2-1_095081_2023-09-17_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-09-17 11:26:58	ga_ls9c_ard_3-2-1_111076_2023-09-17_final.stac-item
2023-09-18 10:28:57	ga_ls9c_ard_3-2-1_102070_2023-09-18_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 10:20:34	ga_ls9c_ard_3-2-1_100080_2023-09-20_final.stac-item
2023-09-21 11:01:02	ga_ls9c_ard_3-2-1_107073_2023-09-21_final.stac-item
2023-09-21 11:01:26	ga_ls9c_ard_3-2-1_107074_2023-09-21_final.stac-item
2023-09-22 10:09:48	ga_ls9c_ard_3-2-1_098084_2023-09-22_final.stac-item
2023-09-23 10:49:27	ga_ls9c_ard_3-2-1_105075_2023-09-23_final.stac-item
2023-09-23 10:51:03	ga_ls9c_ard_3-2-1_105079_2023-09-23_final.stac-item
2023-09-24 09:54:13	ga_ls9c_ard_3-2-1_096076_2023-09-24_final.stac-item
2023-09-24 09:55:01	ga_ls9c_ard_3-2-1_096078_2023-09-24_final.stac-item
2023-09-24 11:33:06	ga_ls9c_ard_3-2-1_112076_2023-09-24_final.stac-item
2023-09-26 09:40:38	ga_ls9c_ard_3-2-1_094073_2023-09-26_final.stac-item
2023-09-28 11:11:32	ga_ls9c_ard_3-2-1_108084_2023-09-28_final.stac-item
2023-09-29 10:15:08	ga_ls9c_ard_3-2-1_099082_2023-09-29_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 10:30:34	ga_ls9c_ard_3-2-1_102074_2023-10-04_final.stac-item
2023-10-04 10:32:57	ga_ls9c_ard_3-2-1_102080_2023-10-04_final.stac-item
2023-10-05 11:11:50	ga_ls9c_ard_3-2-1_109069_2023-10-05_final.stac-item
2023-10-06 10:17:49	ga_ls9c_ard_3-2-1_100073_2023-10-06_final.stac-item
2023-10-06 10:21:01	ga_ls9c_ard_3-2-1_100081_2023-10-06_final.stac-item
2023-10-08 10:09:28	ga_ls9c_ard_3-2-1_098083_2023-10-08_final.stac-item
2023-10-09 10:48:45	ga_ls9c_ard_3-2-1_105073_2023-10-09_final.stac-item
2023-10-10 09:56:44	ga_ls9c_ard_3-2-1_096082_2023-10-10_final.stac-item
2023-10-10 11:32:49	ga_ls9c_ard_3-2-1_112075_2023-10-10_final.stac-item
2023-10-10 11:34:25	ga_ls9c_ard_3-2-1_112079_2023-10-10_final.stac-item
2023-10-11 10:37:13	ga_ls9c_ard_3-2-1_103075_2023-10-11_final.stac-item
2023-10-11 10:37:37	ga_ls9c_ard_3-2-1_103076_2023-10-11_final.stac-item
2023-10-11 10:40:01	ga_ls9c_ard_3-2-1_103082_2023-10-11_final.stac-item
2023-10-12 09:42:25	ga_ls9c_ard_3-2-1_094077_2023-10-12_final.stac-item
2023-10-12 11:21:18	ga_ls9c_ard_3-2-1_110077_2023-10-12_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_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