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
2021-12-07 09:54:10	ga_ls9c_ard_3-2-1_096075_2021-12-07_final.stac-item
2021-12-17 10:33:07	ga_ls9c_ard_3-2-1_102080_2021-12-17_final.stac-item
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2022-01-01 09:49:29	ga_ls9c_ard_3-2-1_095079_2022-01-01_final.stac-item
2022-01-08 11:34:07	ga_ls9c_ard_3-2-1_112078_2022-01-08_final.stac-item
2022-01-12 11:09:23	ga_ls9c_ard_3-2-1_108078_2022-01-12_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-02-24 10:51:30	ga_ls9c_ard_3-2-1_105080_2022-02-24_final.stac-item
2022-02-25 11:34:21	ga_ls9c_ard_3-2-1_112079_2022-02-25_final.stac-item
2022-03-02 10:14:44	ga_ls9c_ard_3-2-1_099081_2022-03-02_final.stac-item
2022-03-19 10:58:23	ga_ls9c_ard_3-2-1_106082_2022-03-19_final.stac-item
2022-03-21 10:45:12	ga_ls9c_ard_3-2-1_104080_2022-03-21_final.stac-item
2022-03-29 09:56:31	ga_ls9c_ard_3-2-1_096082_2022-03-29_final.stac-item
2022-04-11 09:23:58	ga_ls9c_ard_3-2-1_091078_2022-04-10_final.stac-item
2022-04-16 09:43:15	ga_ls9c_ard_3-2-1_094080_2022-04-16_final.stac-item
2022-04-16 09:44:27	ga_ls9c_ard_3-2-1_094083_2022-04-16_final.stac-item
2022-04-23 09:48:57	ga_ls9c_ard_3-2-1_095079_2022-04-23_final.stac-item
2022-06-08 09:59:54	ga_ls9c_ard_3-2-1_097076_2022-06-08_final.stac-item
2022-06-09 10:43:33	ga_ls9c_ard_3-2-1_104077_2022-06-09_final.stac-item
2022-06-14 11:02:58	ga_ls9c_ard_3-2-1_107079_2022-06-14_final.stac-item
2022-06-23 10:57:49	ga_ls9c_ard_3-2-1_106081_2022-06-23_final.stac-item
2022-06-26 09:49:05	ga_ls9c_ard_3-2-1_095079_2022-06-26_final.stac-item
2022-07-12 09:49:01	ga_ls9c_ard_3-2-1_095079_2022-07-12_final.stac-item
2022-07-17 10:06:23	ga_ls9c_ard_3-2-1_098076_2022-07-17_final.stac-item
2022-07-20 10:36:56	ga_ls9c_ard_3-2-1_103075_2022-07-20_final.stac-item
2022-08-05 10:38:21	ga_ls9c_ard_3-2-1_103078_2022-08-05_final.stac-item
2022-08-07 10:22:49	ga_ls9c_ard_3-2-1_101070_2022-08-07_final.stac-item
2022-08-28 10:43:51	ga_ls9c_ard_3-2-1_104076_2022-08-28_final.stac-item
2022-09-03 10:05:59	ga_ls9c_ard_3-2-1_098074_2022-09-03_final.stac-item
2022-09-14 09:49:52	ga_ls9c_ard_3-2-1_095080_2022-09-14_final.stac-item
2022-10-07 09:55:43	ga_ls9c_ard_3-2-1_096079_2022-10-07_final.stac-item
2022-10-07 09:56:31	ga_ls9c_ard_3-2-1_096081_2022-10-07_final.stac-item
2022-10-20 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-10-20_final.stac-item
2022-10-23 09:55:02	ga_ls9c_ard_3-2-1_096077_2022-10-23_final.stac-item
2022-10-28 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-10-28_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-01 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-11-01_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-23 10:51:27	ga_ls9c_ard_3-2-1_105079_2022-11-23_final.stac-item
2022-11-25 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-25_final.stac-item
2022-11-26 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-11-26_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-03 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-12-03_final.stac-item
2022-12-07 09:24:55	ga_ls9c_ard_3-2-1_091079_2022-12-06_final.stac-item
2022-12-13 10:24:44	ga_ls9c_ard_3-2-1_101074_2022-12-13_final.stac-item
2022-12-17 10:03:36	ga_ls9c_ard_3-2-1_097083_2022-12-17_final.stac-item
2022-12-19 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-19_final.stac-item
2022-12-23 11:02:57	ga_ls9c_ard_3-2-1_107077_2022-12-23_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2022-12-26 09:56:59	ga_ls9c_ard_3-2-1_096082_2022-12-26_final.stac-item
2022-12-26 11:34:40	ga_ls9c_ard_3-2-1_112079_2022-12-26_final.stac-item
2022-12-28 11:22:20	ga_ls9c_ard_3-2-1_110079_2022-12-28_final.stac-item
2022-12-28 11:23:55	ga_ls9c_ard_3-2-1_110083_2022-12-28_final.stac-item
2023-01-04 09:48:51	ga_ls9c_ard_3-2-1_095077_2023-01-04_final.stac-item
2023-01-05 10:33:19	ga_ls9c_ard_3-2-1_102080_2023-01-05_final.stac-item
2023-01-06 11:16:34	ga_ls9c_ard_3-2-1_109080_2023-01-06_final.stac-item
2023-01-13 09:45:01	ga_ls9c_ard_3-2-1_094083_2023-01-13_final.stac-item
2023-01-13 11:23:54	ga_ls9c_ard_3-2-1_110083_2023-01-13_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-01-15 09:30:39	ga_ls9c_ard_3-2-1_092078_2023-01-15_final.stac-item
2023-01-19 10:42:20	ga_ls9c_ard_3-2-1_104072_2023-01-19_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-24 11:04:54	ga_ls9c_ard_3-2-1_107082_2023-01-24_final.stac-item
2023-01-29 11:23:56	ga_ls9c_ard_3-2-1_110083_2023-01-29_final.stac-item
2023-02-03 10:00:51	ga_ls9c_ard_3-2-1_097076_2023-02-03_final.stac-item
2023-02-05 11:25:23	ga_ls9c_ard_3-2-1_111071_2023-02-05_final.stac-item
2023-02-09 11:05:04	ga_ls9c_ard_3-2-1_107082_2023-02-09_final.stac-item
2023-02-14 09:43:54	ga_ls9c_ard_3-2-1_094080_2023-02-14_final.stac-item
2023-03-08 10:44:11	ga_ls9c_ard_3-2-1_104077_2023-03-08_final.stac-item
2023-04-06 10:11:52	ga_ls9c_ard_3-2-1_099074_2023-04-06_final.stac-item
2023-05-08 10:11:34	ga_ls9c_ard_3-2-1_099074_2023-05-08_final.stac-item
2023-05-11 10:44:28	ga_ls9c_ard_3-2-1_104079_2023-05-11_final.stac-item
2023-05-11 10:45:16	ga_ls9c_ard_3-2-1_104081_2023-05-11_final.stac-item
2023-05-17 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-05-17_final.stac-item
2023-05-21 09:42:57	ga_ls9c_ard_3-2-1_094080_2023-05-21_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-06-04 11:32:31	ga_ls9c_ard_3-2-1_112076_2023-06-04_final.stac-item
2023-06-21 10:36:22	ga_ls9c_ard_3-2-1_103075_2023-06-21_final.stac-item
2023-06-25 10:11:14	ga_ls9c_ard_3-2-1_099074_2023-06-25_final.stac-item
2023-06-26 09:18:01	ga_ls9c_ard_3-2-1_090080_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 11:38:12	ga_ls9c_ard_3-2-1_113075_2023-06-27_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-20 10:05:45	ga_ls9c_ard_3-2-1_098075_2023-07-20_final.stac-item
2023-07-24 11:21:05	ga_ls9c_ard_3-2-1_110078_2023-07-24_final.stac-item
2023-07-26 09:29:51	ga_ls9c_ard_3-2-1_092078_2023-07-25_final.stac-item
2023-07-28 09:17:32	ga_ls9c_ard_3-2-1_090078_2023-07-27_final.stac-item
2023-07-28 10:57:37	ga_ls9c_ard_3-2-1_106081_2023-07-28_final.stac-item
2023-07-30 10:44:29	ga_ls9c_ard_3-2-1_104079_2023-07-30_final.stac-item
2023-08-08 10:38:00	ga_ls9c_ard_3-2-1_103078_2023-08-08_final.stac-item
2023-08-09 09:41:35	ga_ls9c_ard_3-2-1_094076_2023-08-09_final.stac-item
2023-08-13 09:18:28	ga_ls9c_ard_3-2-1_090080_2023-08-12_final.stac-item
2023-08-14 10:02:56	ga_ls9c_ard_3-2-1_097083_2023-08-14_final.stac-item
2023-08-15 10:41:24	ga_ls9c_ard_3-2-1_104071_2023-08-15_final.stac-item
2023-10-18 10:44:16	ga_ls9c_ard_3-2-1_104077_2023-10-18_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-23 09:25:55	ga_ls9c_ard_3-2-1_091082_2023-10-22_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-02 10:03:17	ga_ls9c_ard_3-2-1_097083_2023-11-02_final.stac-item
2023-11-15 09:30:25	ga_ls9c_ard_3-2-1_092078_2023-11-15_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