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
2021-12-25 09:43:18	ga_ls9c_ard_3-2-1_094079_2021-12-25_final.stac-item
2022-02-12 10:27:18	ga_ls9c_ard_3-2-1_101081_2022-02-12_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-08 09:36:52	ga_ls9c_ard_3-2-1_093079_2022-03-08_final.stac-item
2022-04-03 10:14:39	ga_ls9c_ard_3-2-1_099081_2022-04-03_final.stac-item
2022-06-09 10:43:57	ga_ls9c_ard_3-2-1_104078_2022-06-09_final.stac-item
2022-06-14 09:23:41	ga_ls9c_ard_3-2-1_091078_2022-06-13_final.stac-item
2022-06-17 09:53:25	ga_ls9c_ard_3-2-1_096075_2022-06-17_final.stac-item
2022-07-16 09:23:54	ga_ls9c_ard_3-2-1_091078_2022-07-15_final.stac-item
2022-07-27 10:43:37	ga_ls9c_ard_3-2-1_104076_2022-07-27_final.stac-item
2022-07-28 09:49:36	ga_ls9c_ard_3-2-1_095080_2022-07-28_final.stac-item
2022-08-04 09:53:53	ga_ls9c_ard_3-2-1_096075_2022-08-04_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-09-29 10:45:59	ga_ls9c_ard_3-2-1_104081_2022-09-29_final.stac-item
2022-10-12 10:12:20	ga_ls9c_ard_3-2-1_099074_2022-10-12_final.stac-item
2022-10-12 10:12:44	ga_ls9c_ard_3-2-1_099075_2022-10-12_final.stac-item
2022-10-21 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-10-21_final.stac-item
2022-10-30 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-10-30_final.stac-item
2022-11-07 10:51:02	ga_ls9c_ard_3-2-1_105078_2022-11-07_final.stac-item
2022-11-26 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-11-26_final.stac-item
2022-11-28 09:30:41	ga_ls9c_ard_3-2-1_092078_2022-11-28_final.stac-item
2022-12-03 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-03_final.stac-item
2022-12-03 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-03_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2022-12-19 11:28:31	ga_ls9c_ard_3-2-1_111079_2022-12-19_final.stac-item
2023-01-08 09:24:55	ga_ls9c_ard_3-2-1_091079_2023-01-07_final.stac-item
2023-01-18 10:00:18	ga_ls9c_ard_3-2-1_097075_2023-01-18_final.stac-item
2023-01-27 09:54:35	ga_ls9c_ard_3-2-1_096076_2023-01-27_final.stac-item
2023-01-27 09:56:35	ga_ls9c_ard_3-2-1_096081_2023-01-27_final.stac-item
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final.stac-item
2023-01-27 11:34:40	ga_ls9c_ard_3-2-1_112079_2023-01-27_final.stac-item
2023-01-29 11:23:08	ga_ls9c_ard_3-2-1_110081_2023-01-29_final.stac-item
2023-02-03 10:01:15	ga_ls9c_ard_3-2-1_097077_2023-02-03_final.stac-item
2023-02-03 11:39:44	ga_ls9c_ard_3-2-1_113076_2023-02-03_final.stac-item
2023-02-03 11:40:32	ga_ls9c_ard_3-2-1_113078_2023-02-03_final.stac-item
2023-02-05 11:28:59	ga_ls9c_ard_3-2-1_111080_2023-02-05_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-12 09:54:41	ga_ls9c_ard_3-2-1_096076_2023-02-12_final.stac-item
2023-02-13 10:39:08	ga_ls9c_ard_3-2-1_103079_2023-02-13_final.stac-item
2023-02-14 09:43:54	ga_ls9c_ard_3-2-1_094080_2023-02-14_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-04-23 09:19:20	ga_ls9c_ard_3-2-1_090082_2023-04-22_final.stac-item
2023-04-25 10:43:26	ga_ls9c_ard_3-2-1_104076_2023-04-25_final.stac-item
2023-04-25 10:43:50	ga_ls9c_ard_3-2-1_104077_2023-04-25_final.stac-item
2023-04-26 09:47:48	ga_ls9c_ard_3-2-1_095076_2023-04-26_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_final.stac-item
2023-07-15 09:48:48	ga_ls9c_ard_3-2-1_095079_2023-07-15_final.stac-item
2023-07-16 10:32:04	ga_ls9c_ard_3-2-1_102079_2023-07-16_final.stac-item
2023-07-18 10:18:06	ga_ls9c_ard_3-2-1_100075_2023-07-18_final.stac-item
2023-07-19 09:23:41	ga_ls9c_ard_3-2-1_091078_2023-07-18_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-21 10:50:12	ga_ls9c_ard_3-2-1_105078_2023-07-21_final.stac-item
2023-07-22 09:53:22	ga_ls9c_ard_3-2-1_096075_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
2023-07-23 10:36:38	ga_ls9c_ard_3-2-1_103075_2023-07-23_final.stac-item
2023-07-24 09:42:36	ga_ls9c_ard_3-2-1_094079_2023-07-24_final.stac-item
2023-07-24 09:43:00	ga_ls9c_ard_3-2-1_094080_2023-07-24_final.stac-item
2023-07-24 11:21:53	ga_ls9c_ard_3-2-1_110080_2023-07-24_final.stac-item
2023-07-26 09:29:27	ga_ls9c_ard_3-2-1_092077_2023-07-25_final.stac-item
2023-07-29 10:00:25	ga_ls9c_ard_3-2-1_097077_2023-07-29_final.stac-item
2023-07-29 11:38:30	ga_ls9c_ard_3-2-1_113075_2023-07-29_final.stac-item
2023-08-02 09:35:45	ga_ls9c_ard_3-2-1_093077_2023-08-02_final.stac-item
2023-08-02 09:36:57	ga_ls9c_ard_3-2-1_093080_2023-08-02_final.stac-item
2023-08-08 10:38:00	ga_ls9c_ard_3-2-1_103078_2023-08-08_final.stac-item
2023-08-08 10:38:24	ga_ls9c_ard_3-2-1_103079_2023-08-08_final.stac-item
2023-10-15 11:51:02	ga_ls9c_ard_3-2-1_115074_2023-10-15_final.stac-item
2023-10-17 10:00:12	ga_ls9c_ard_3-2-1_097075_2023-10-17_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-19 09:49:27	ga_ls9c_ard_3-2-1_095079_2023-10-19_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-25 10:50:50	ga_ls9c_ard_3-2-1_105078_2023-10-25_final.stac-item
2023-10-26 11:34:05	ga_ls9c_ard_3-2-1_112078_2023-10-26_final.stac-item
2023-10-27 10:37:15	ga_ls9c_ard_3-2-1_103075_2023-10-27_final.stac-item
2023-10-28 09:42:25	ga_ls9c_ard_3-2-1_094077_2023-10-28_final.stac-item
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-10-28 09:44:49	ga_ls9c_ard_3-2-1_094083_2023-10-28_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-10-30 09:30:26	ga_ls9c_ard_3-2-1_092078_2023-10-30_final.stac-item
2023-11-02 10:00:05	ga_ls9c_ard_3-2-1_097075_2023-11-02_final.stac-item
2023-11-02 10:00:29	ga_ls9c_ard_3-2-1_097076_2023-11-02_final.stac-item
2023-11-02 11:39:22	ga_ls9c_ard_3-2-1_113076_2023-11-02_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-03 10:44:56	ga_ls9c_ard_3-2-1_104079_2023-11-03_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-04 09:48:08	ga_ls9c_ard_3-2-1_095076_2023-11-04_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-18 10:00:10	ga_ls9c_ard_3-2-1_097075_2023-11-18_final.stac-item
2023-11-18 10:00:34	ga_ls9c_ard_3-2-1_097076_2023-11-18_final.stac-item
2023-11-18 10:00:58	ga_ls9c_ard_3-2-1_097077_2023-11-18_final.stac-item
2023-11-20 11:27:55	ga_ls9c_ard_3-2-1_111078_2023-11-20_final.stac-item
2023-11-21 10:32:43	ga_ls9c_ard_3-2-1_102079_2023-11-21_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_final.stac-item
2023-11-22 09:36:18	ga_ls9c_ard_3-2-1_093077_2023-11-22_final.stac-item
2023-11-22 11:15:59	ga_ls9c_ard_3-2-1_109079_2023-11-22_final.stac-item
2023-11-23 10:21:11	ga_ls9c_ard_3-2-1_100081_2023-11-23_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