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
2021-11-06 10:16:11	ga_ls9c_ard_3-2-1_100075_2021-11-06_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-21 09:24:20	ga_ls9c_ard_3-2-1_091078_2022-01-20_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-13 09:30:05	ga_ls9c_ard_3-2-1_092077_2022-02-13_final.stac-item
2022-02-14 10:14:55	ga_ls9c_ard_3-2-1_099081_2022-02-14_final.stac-item
2022-02-16 10:02:33	ga_ls9c_ard_3-2-1_097081_2022-02-16_final.stac-item
2022-02-17 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-02-17_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-04-09 09:36:45	ga_ls9c_ard_3-2-1_093079_2022-04-09_final.stac-item
2022-04-20 09:19:40	ga_ls9c_ard_3-2-1_090083_2022-04-19_final.stac-item
2022-05-23 10:02:40	ga_ls9c_ard_3-2-1_097083_2022-05-23_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-01 09:53:18	ga_ls9c_ard_3-2-1_096075_2022-06-01_final.stac-item
2022-06-15 10:05:22	ga_ls9c_ard_3-2-1_098074_2022-06-15_final.stac-item
2022-06-28 09:36:43	ga_ls9c_ard_3-2-1_093079_2022-06-28_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-07-26 10:02:20	ga_ls9c_ard_3-2-1_097081_2022-07-26_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-07 10:22:49	ga_ls9c_ard_3-2-1_101070_2022-08-07_final.stac-item
2022-08-10 09:20:03	ga_ls9c_ard_3-2-1_090083_2022-08-09_final.stac-item
2022-08-24 09:31:41	ga_ls9c_ard_3-2-1_092081_2022-08-24_final.stac-item
2022-09-05 09:53:37	ga_ls9c_ard_3-2-1_096074_2022-09-05_final.stac-item
2022-09-17 10:18:48	ga_ls9c_ard_3-2-1_100075_2022-09-17_final.stac-item
2022-10-03 10:18:04	ga_ls9c_ard_3-2-1_100073_2022-10-03_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-10-14 11:39:16	ga_ls9c_ard_3-2-1_113075_2022-10-14_final.stac-item
2022-10-25 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-10-25_final.stac-item
2022-10-25 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-10-25_final.stac-item
2022-10-28 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-10-28_final.stac-item
2022-10-31 10:45:15	ga_ls9c_ard_3-2-1_104079_2022-10-31_final.stac-item
2022-11-03 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-11-03_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-24 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-11-24_final.stac-item
2022-11-26 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-26_final.stac-item
2022-12-02 10:42:26	ga_ls9c_ard_3-2-1_104072_2022-12-02_final.stac-item
2022-12-08 10:06:35	ga_ls9c_ard_3-2-1_098075_2022-12-08_final.stac-item
2022-12-10 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-12-10_final.stac-item
2022-12-12 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-12-12_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-20 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-20_final.stac-item
2022-12-28 11:23:08	ga_ls9c_ard_3-2-1_110081_2022-12-28_final.stac-item
2023-01-08 09:26:07	ga_ls9c_ard_3-2-1_091082_2023-01-07_final.stac-item
2023-01-12 10:38:40	ga_ls9c_ard_3-2-1_103078_2023-01-12_final.stac-item
2023-01-13 11:23:07	ga_ls9c_ard_3-2-1_110081_2023-01-13_final.stac-item
2023-01-23 10:20:26	ga_ls9c_ard_3-2-1_100079_2023-01-23_final.stac-item
2023-01-29 11:22:44	ga_ls9c_ard_3-2-1_110080_2023-01-29_final.stac-item
2023-02-01 10:15:11	ga_ls9c_ard_3-2-1_099081_2023-02-01_final.stac-item
2023-02-01 10:15:35	ga_ls9c_ard_3-2-1_099082_2023-02-01_final.stac-item
2023-02-03 11:39:44	ga_ls9c_ard_3-2-1_113076_2023-02-03_final.stac-item
2023-02-09 11:04:16	ga_ls9c_ard_3-2-1_107080_2023-02-09_final.stac-item
2023-04-23 09:18:32	ga_ls9c_ard_3-2-1_090080_2023-04-22_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-30 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-04-30_final.stac-item
2023-05-02 10:50:42	ga_ls9c_ard_3-2-1_105079_2023-05-02_final.stac-item
2023-05-03 09:53:04	ga_ls9c_ard_3-2-1_096074_2023-05-03_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-06-23 10:24:00	ga_ls9c_ard_3-2-1_101075_2023-06-23_final.stac-item
2023-06-23 10:26:00	ga_ls9c_ard_3-2-1_101080_2023-06-23_final.stac-item
2023-06-28 10:41:01	ga_ls9c_ard_3-2-1_104071_2023-06-28_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-06-29 11:28:18	ga_ls9c_ard_3-2-1_111081_2023-06-29_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-06 09:52:07	ga_ls9c_ard_3-2-1_096072_2023-07-06_final.stac-item
2023-07-06 09:54:31	ga_ls9c_ard_3-2-1_096078_2023-07-06_final.stac-item
2023-07-06 09:55:43	ga_ls9c_ard_3-2-1_096081_2023-07-06_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-08-02 11:12:38	ga_ls9c_ard_3-2-1_109072_2023-08-02_final.stac-item
2023-08-05 11:45:34	ga_ls9c_ard_3-2-1_114077_2023-08-05_final.stac-item
2023-08-08 10:37:36	ga_ls9c_ard_3-2-1_103077_2023-08-08_final.stac-item
2023-10-13 10:22:54	ga_ls9c_ard_3-2-1_101070_2023-10-13_final.stac-item
2023-10-14 11:06:58	ga_ls9c_ard_3-2-1_108072_2023-10-14_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-16 10:57:01	ga_ls9c_ard_3-2-1_106078_2023-10-16_final.stac-item
2023-10-17 11:39:05	ga_ls9c_ard_3-2-1_113075_2023-10-17_final.stac-item
2023-10-19 09:51:27	ga_ls9c_ard_3-2-1_095084_2023-10-19_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-24 10:05:59	ga_ls9c_ard_3-2-1_098074_2023-10-24_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-10-29 10:25:16	ga_ls9c_ard_3-2-1_101076_2023-10-29_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-05 10:31:24	ga_ls9c_ard_3-2-1_102076_2023-11-05_final.stac-item
2023-11-14 10:27:15	ga_ls9c_ard_3-2-1_101081_2023-11-14_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_final.stac-item
2023-11-19 10:42:15	ga_ls9c_ard_3-2-1_104072_2023-11-19_final.stac-item
2023-11-20 11:29:07	ga_ls9c_ard_3-2-1_111081_2023-11-20_final.stac-item
2023-11-22 09:37:30	ga_ls9c_ard_3-2-1_093080_2023-11-22_final.stac-item
2023-11-26 10:51:42	ga_ls9c_ard_3-2-1_105080_2023-11-26_final.stac-item
2023-11-27 11:34:34	ga_ls9c_ard_3-2-1_112079_2023-11-27_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