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
2021-12-09 11:23:51	ga_ls9c_ard_3-2-1_110083_2021-12-09_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2022-02-17 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-02-17_final.stac-item
2022-03-06 09:48:02	ga_ls9c_ard_3-2-1_095076_2022-03-06_final.stac-item
2022-03-08 09:37:40	ga_ls9c_ard_3-2-1_093081_2022-03-08_final.stac-item
2022-03-24 09:38:24	ga_ls9c_ard_3-2-1_093083_2022-03-24_final.stac-item
2022-05-06 09:19:36	ga_ls9c_ard_3-2-1_090083_2022-05-05_final.stac-item
2022-05-14 10:06:09	ga_ls9c_ard_3-2-1_098076_2022-05-14_final.stac-item
2022-05-24 10:41:32	ga_ls9c_ard_3-2-1_104072_2022-05-24_final.stac-item
2022-06-14 11:00:34	ga_ls9c_ard_3-2-1_107073_2022-06-14_final.stac-item
2022-06-30 09:23:57	ga_ls9c_ard_3-2-1_091078_2022-06-29_final.stac-item
2022-06-30 11:00:51	ga_ls9c_ard_3-2-1_107073_2022-06-30_final.stac-item
2022-07-07 09:31:18	ga_ls9c_ard_3-2-1_092081_2022-07-07_final.stac-item
2022-07-08 10:11:46	ga_ls9c_ard_3-2-1_099074_2022-07-08_final.stac-item
2022-07-10 10:02:59	ga_ls9c_ard_3-2-1_097083_2022-07-10_final.stac-item
2022-07-16 11:00:47	ga_ls9c_ard_3-2-1_107073_2022-07-16_final.stac-item
2022-08-06 09:40:45	ga_ls9c_ard_3-2-1_094073_2022-08-06_final.stac-item
2022-08-09 10:12:04	ga_ls9c_ard_3-2-1_099074_2022-08-09_final.stac-item
2022-08-16 10:18:42	ga_ls9c_ard_3-2-1_100075_2022-08-16_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-08-27 10:01:00	ga_ls9c_ard_3-2-1_097077_2022-08-27_final.stac-item
2022-09-05 09:52:49	ga_ls9c_ard_3-2-1_096072_2022-09-05_final.stac-item
2022-09-28 10:03:31	ga_ls9c_ard_3-2-1_097083_2022-09-28_final.stac-item
2022-10-07 09:53:20	ga_ls9c_ard_3-2-1_096073_2022-10-07_final.stac-item
2022-10-10 10:25:28	ga_ls9c_ard_3-2-1_101076_2022-10-10_final.stac-item
2022-10-16 09:50:02	ga_ls9c_ard_3-2-1_095080_2022-10-16_final.stac-item
2022-10-25 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-10-25_final.stac-item
2022-10-31 10:45:15	ga_ls9c_ard_3-2-1_104079_2022-10-31_final.stac-item
2022-11-08 09:55:01	ga_ls9c_ard_3-2-1_096077_2022-11-08_final.stac-item
2022-11-11 10:25:09	ga_ls9c_ard_3-2-1_101075_2022-11-11_final.stac-item
2022-11-12 09:30:43	ga_ls9c_ard_3-2-1_092078_2022-11-12_final.stac-item
2022-11-14 10:56:51	ga_ls9c_ard_3-2-1_106077_2022-11-14_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-04 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-04_final.stac-item
2022-12-07 09:24:31	ga_ls9c_ard_3-2-1_091078_2022-12-06_final.stac-item
2022-12-12 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-12-12_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 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-12-19_final.stac-item
2022-12-22 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-12-22_final.stac-item
2022-12-27 10:39:03	ga_ls9c_ard_3-2-1_103079_2022-12-27_final.stac-item
2022-12-28 11:23:55	ga_ls9c_ard_3-2-1_110083_2022-12-28_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2023-01-11 09:55:24	ga_ls9c_ard_3-2-1_096078_2023-01-11_final.stac-item
2023-01-13 11:22:19	ga_ls9c_ard_3-2-1_110079_2023-01-13_final.stac-item
2023-01-18 11:39:58	ga_ls9c_ard_3-2-1_113077_2023-01-18_final.stac-item
2023-01-20 09:50:17	ga_ls9c_ard_3-2-1_095081_2023-01-20_final.stac-item
2023-01-23 10:20:26	ga_ls9c_ard_3-2-1_100079_2023-01-23_final.stac-item
2023-02-01 10:15:11	ga_ls9c_ard_3-2-1_099081_2023-02-01_final.stac-item
2023-02-06 10:32:34	ga_ls9c_ard_3-2-1_102078_2023-02-06_final.stac-item
2023-02-06 10:32:58	ga_ls9c_ard_3-2-1_102079_2023-02-06_final.stac-item
2023-02-14 09:44:17	ga_ls9c_ard_3-2-1_094081_2023-02-14_final.stac-item
2023-02-24 10:20:22	ga_ls9c_ard_3-2-1_100079_2023-02-24_final.stac-item
2023-04-25 10:44:14	ga_ls9c_ard_3-2-1_104078_2023-04-25_final.stac-item
2023-04-27 10:31:27	ga_ls9c_ard_3-2-1_102077_2023-04-27_final.stac-item
2023-05-02 10:51:06	ga_ls9c_ard_3-2-1_105080_2023-05-02_final.stac-item
2023-05-03 11:34:44	ga_ls9c_ard_3-2-1_112081_2023-05-03_final.stac-item
2023-05-04 10:35:54	ga_ls9c_ard_3-2-1_103073_2023-05-04_final.stac-item
2023-05-04 10:36:18	ga_ls9c_ard_3-2-1_103074_2023-05-04_final.stac-item
2023-05-06 10:25:32	ga_ls9c_ard_3-2-1_101078_2023-05-06_final.stac-item
2023-05-09 09:19:09	ga_ls9c_ard_3-2-1_090082_2023-05-08_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-05-12 09:47:14	ga_ls9c_ard_3-2-1_095075_2023-05-12_final.stac-item
2023-05-14 09:37:39	ga_ls9c_ard_3-2-1_093082_2023-05-14_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 11:15:21	ga_ls9c_ard_3-2-1_109079_2023-05-14_final.stac-item
2023-06-20 09:52:19	ga_ls9c_ard_3-2-1_096073_2023-06-20_final.stac-item
2023-06-21 10:35:34	ga_ls9c_ard_3-2-1_103073_2023-06-21_final.stac-item
2023-06-23 10:22:01	ga_ls9c_ard_3-2-1_101070_2023-06-23_final.stac-item
2023-06-24 09:31:34	ga_ls9c_ard_3-2-1_092083_2023-06-24_final.stac-item
2023-06-24 11:10:03	ga_ls9c_ard_3-2-1_108082_2023-06-24_final.stac-item
2023-06-30 10:28:43	ga_ls9c_ard_3-2-1_102071_2023-06-30_final.stac-item
2023-07-16 10:32:28	ga_ls9c_ard_3-2-1_102080_2023-07-16_final.stac-item
2023-07-17 09:38:26	ga_ls9c_ard_3-2-1_093084_2023-07-17_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 10:04:57	ga_ls9c_ard_3-2-1_098073_2023-07-20_final.stac-item
2023-07-20 10:05:45	ga_ls9c_ard_3-2-1_098075_2023-07-20_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-24 09:41:00	ga_ls9c_ard_3-2-1_094075_2023-07-24_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-27 10:11:32	ga_ls9c_ard_3-2-1_099074_2023-07-27_final.stac-item
2023-08-04 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-08-04_final.stac-item
2023-08-06 10:47:10	ga_ls9c_ard_3-2-1_105070_2023-08-06_final.stac-item
2023-08-17 10:31:25	ga_ls9c_ard_3-2-1_102077_2023-08-17_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-14 11:10:57	ga_ls9c_ard_3-2-1_108082_2023-10-14_final.stac-item
2023-10-17 11:39:05	ga_ls9c_ard_3-2-1_113075_2023-10-17_final.stac-item
2023-10-18 10:41:52	ga_ls9c_ard_3-2-1_104071_2023-10-18_final.stac-item
2023-10-21 09:38:17	ga_ls9c_ard_3-2-1_093082_2023-10-21_final.stac-item
2023-10-26 11:32:53	ga_ls9c_ard_3-2-1_112075_2023-10-26_final.stac-item
2023-10-27 10:35:40	ga_ls9c_ard_3-2-1_103071_2023-10-27_final.stac-item
2023-10-27 10:39:15	ga_ls9c_ard_3-2-1_103080_2023-10-27_final.stac-item
2023-10-30 11:09:43	ga_ls9c_ard_3-2-1_108079_2023-10-30_final.stac-item
2023-11-02 11:39:46	ga_ls9c_ard_3-2-1_113077_2023-11-02_final.stac-item
2023-11-05 10:32:36	ga_ls9c_ard_3-2-1_102079_2023-11-05_final.stac-item
2023-11-15 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-11-15_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-19 10:41:51	ga_ls9c_ard_3-2-1_104071_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 11:15:12	ga_ls9c_ard_3-2-1_109077_2023-11-22_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