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 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-11-19 10:43:07	ga_ls9c_ard_3-2-1_104077_2021-11-19_final.stac-item
2021-11-24 10:43:11	ga_ls9c_ard_3-2-1_104071_2021-11-24_final.stac-item
2021-12-13 10:56:41	ga_ls9c_ard_3-2-1_106077_2021-12-13_final.stac-item
2021-12-23 09:53:16	ga_ls9c_ard_3-2-1_096073_2021-12-23_final.stac-item
2021-12-24 10:39:20	ga_ls9c_ard_3-2-1_103080_2021-12-24_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2022-01-03 09:36:19	ga_ls9c_ard_3-2-1_093077_2022-01-03_final.stac-item
2022-01-12 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-01-12_final.stac-item
2022-01-21 11:03:37	ga_ls9c_ard_3-2-1_107079_2022-01-21_final.stac-item
2022-02-05 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-02-05_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-11 10:08:10	ga_ls9c_ard_3-2-1_098080_2022-03-11_final.stac-item
2022-03-24 09:36:24	ga_ls9c_ard_3-2-1_093078_2022-03-24_final.stac-item
2022-03-31 09:45:21	ga_ls9c_ard_3-2-1_094085_2022-03-31_final.stac-item
2022-04-03 10:12:40	ga_ls9c_ard_3-2-1_099076_2022-04-03_final.stac-item
2022-04-06 10:41:57	ga_ls9c_ard_3-2-1_104072_2022-04-06_final.stac-item
2022-04-09 09:36:45	ga_ls9c_ard_3-2-1_093079_2022-04-09_final.stac-item
2022-04-14 09:56:26	ga_ls9c_ard_3-2-1_096082_2022-04-14_final.stac-item
2022-04-16 09:45:15	ga_ls9c_ard_3-2-1_094085_2022-04-16_final.stac-item
2022-04-20 09:19:40	ga_ls9c_ard_3-2-1_090083_2022-04-19_final.stac-item
2022-04-28 10:06:17	ga_ls9c_ard_3-2-1_098076_2022-04-28_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-09 09:50:04	ga_ls9c_ard_3-2-1_095082_2022-05-09_final.stac-item
2022-05-16 09:52:58	ga_ls9c_ard_3-2-1_096074_2022-05-16_final.stac-item
2022-05-25 09:47:06	ga_ls9c_ard_3-2-1_095075_2022-05-25_final.stac-item
2022-06-16 10:47:50	ga_ls9c_ard_3-2-1_105072_2022-06-16_final.stac-item
2022-08-16 10:20:18	ga_ls9c_ard_3-2-1_100079_2022-08-16_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-10-14 10:03:11	ga_ls9c_ard_3-2-1_097082_2022-10-14_final.stac-item
2022-10-21 10:05:48	ga_ls9c_ard_3-2-1_098073_2022-10-21_final.stac-item
2022-10-30 10:02:00	ga_ls9c_ard_3-2-1_097079_2022-10-30_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-07 10:47:50	ga_ls9c_ard_3-2-1_105070_2022-11-07_final.stac-item
2022-11-09 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-11-09_final.stac-item
2022-11-09 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-09_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-11-22 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-11-22_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2022-11-26 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-11-26_final.stac-item
2022-12-05 09:37:40	ga_ls9c_ard_3-2-1_093080_2022-12-05_final.stac-item
2022-12-07 11:03:48	ga_ls9c_ard_3-2-1_107079_2022-12-07_final.stac-item
2022-12-08 10:06:35	ga_ls9c_ard_3-2-1_098075_2022-12-08_final.stac-item
2022-12-08 11:47:04	ga_ls9c_ard_3-2-1_114079_2022-12-08_final.stac-item
2022-12-12 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-12-12_final.stac-item
2022-12-28 09:41:51	ga_ls9c_ard_3-2-1_094075_2022-12-28_final.stac-item
2022-12-30 09:32:18	ga_ls9c_ard_3-2-1_092082_2022-12-30_final.stac-item
2022-12-30 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-12-30_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-05 10:32:31	ga_ls9c_ard_3-2-1_102078_2023-01-05_final.stac-item
2023-01-08 11:03:48	ga_ls9c_ard_3-2-1_107079_2023-01-08_final.stac-item
2023-01-09 11:45:04	ga_ls9c_ard_3-2-1_114074_2023-01-09_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-15 09:31:50	ga_ls9c_ard_3-2-1_092081_2023-01-15_final.stac-item
2023-01-15 09:33:50	ga_ls9c_ard_3-2-1_092086_2023-01-15_final.stac-item
2023-01-17 10:56:44	ga_ls9c_ard_3-2-1_106077_2023-01-17_final.stac-item
2023-01-29 09:44:15	ga_ls9c_ard_3-2-1_094081_2023-01-29_final.stac-item
2023-01-31 11:10:48	ga_ls9c_ard_3-2-1_108081_2023-01-31_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-04 10:44:31	ga_ls9c_ard_3-2-1_104077_2023-02-04_final.stac-item
2023-02-05 11:29:23	ga_ls9c_ard_3-2-1_111081_2023-02-05_final.stac-item
2023-02-06 10:30:58	ga_ls9c_ard_3-2-1_102074_2023-02-06_final.stac-item
2023-02-07 09:36:33	ga_ls9c_ard_3-2-1_093077_2023-02-07_final.stac-item
2023-02-07 09:38:33	ga_ls9c_ard_3-2-1_093082_2023-02-07_final.stac-item
2023-02-08 11:59:06	ga_ls9c_ard_3-2-1_116078_2023-02-08_final.stac-item
2023-03-02 11:22:09	ga_ls9c_ard_3-2-1_110079_2023-03-02_final.stac-item
2023-03-06 10:57:47	ga_ls9c_ard_3-2-1_106080_2023-03-06_final.stac-item
2023-03-25 09:50:51	ga_ls9c_ard_3-2-1_095083_2023-03-25_final.stac-item
2023-04-24 10:03:47	ga_ls9c_ard_3-2-1_097085_2023-04-24_final.stac-item
2023-04-25 10:41:03	ga_ls9c_ard_3-2-1_104070_2023-04-25_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-02 10:47:54	ga_ls9c_ard_3-2-1_105072_2023-05-02_final.stac-item
2023-05-07 09:31:06	ga_ls9c_ard_3-2-1_092081_2023-05-07_final.stac-item
2023-05-09 10:54:02	ga_ls9c_ard_3-2-1_106072_2023-05-09_final.stac-item
2023-05-12 09:51:14	ga_ls9c_ard_3-2-1_095085_2023-05-12_final.stac-item
2023-05-12 11:29:43	ga_ls9c_ard_3-2-1_111084_2023-05-12_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-17 11:44:13	ga_ls9c_ard_3-2-1_114074_2023-05-17_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-07-26 09:31:27	ga_ls9c_ard_3-2-1_092082_2023-07-26_final.stac-item
2023-07-31 09:46:53	ga_ls9c_ard_3-2-1_095074_2023-07-31_final.stac-item
2023-08-05 10:05:29	ga_ls9c_ard_3-2-1_098074_2023-08-05_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-10-13 10:26:05	ga_ls9c_ard_3-2-1_101078_2023-10-13_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-10-23 11:04:00	ga_ls9c_ard_3-2-1_107080_2023-10-23_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_2023-10-31_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-02 11:38:58	ga_ls9c_ard_3-2-1_113075_2023-11-02_final.stac-item
2023-11-03 10:42:08	ga_ls9c_ard_3-2-1_104072_2023-11-03_final.stac-item
2023-11-04 11:28:37	ga_ls9c_ard_3-2-1_111080_2023-11-04_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-18 11:39:27	ga_ls9c_ard_3-2-1_113076_2023-11-18_final.stac-item
2023-11-19 10:43:27	ga_ls9c_ard_3-2-1_104075_2023-11-19_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