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
2021-11-03 11:33:13	ga_ls9c_ard_3-2-1_112074_2021-11-03_final.stac-item
2021-12-06 09:16:30	ga_ls9c_ard_3-2-1_089089_2021-12-05_final.stac-item
2021-12-08 10:39:24	ga_ls9c_ard_3-2-1_103080_2021-12-08_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-25 09:40:55	ga_ls9c_ard_3-2-1_094073_2021-12-25_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-28 09:34:07	ga_ls9c_ard_3-2-1_092087_2022-01-28_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-03-26 11:05:18	ga_ls9c_ard_3-2-1_107084_2022-03-26_final.stac-item
2022-04-09 11:14:26	ga_ls9c_ard_3-2-1_109076_2022-04-09_final.stac-item
2022-05-15 10:50:59	ga_ls9c_ard_3-2-1_105080_2022-05-15_final.stac-item
2022-05-31 10:49:43	ga_ls9c_ard_3-2-1_105077_2022-05-31_final.stac-item
2022-06-18 10:33:54	ga_ls9c_ard_3-2-1_103068_2022-06-18_final.stac-item
2022-07-02 10:50:04	ga_ls9c_ard_3-2-1_105077_2022-07-02_final.stac-item
2022-07-02 10:51:16	ga_ls9c_ard_3-2-1_105080_2022-07-02_final.stac-item
2022-07-07 11:07:00	ga_ls9c_ard_3-2-1_108073_2022-07-07_final.stac-item
2022-07-13 10:28:16	ga_ls9c_ard_3-2-1_102069_2022-07-13_final.stac-item
2022-07-16 09:27:29	ga_ls9c_ard_3-2-1_091087_2022-07-15_final.stac-item
2022-07-18 10:51:15	ga_ls9c_ard_3-2-1_105080_2022-07-18_final.stac-item
2022-07-20 10:34:08	ga_ls9c_ard_3-2-1_103068_2022-07-20_final.stac-item
2022-07-25 10:57:33	ga_ls9c_ard_3-2-1_106080_2022-07-25_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-08-22 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-08-22_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-08-29 09:48:38	ga_ls9c_ard_3-2-1_095077_2022-08-29_final.stac-item
2022-09-25 11:11:05	ga_ls9c_ard_3-2-1_108082_2022-09-25_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-11 11:07:33	ga_ls9c_ard_3-2-1_108073_2022-10-11_final.stac-item
2022-10-11 11:07:57	ga_ls9c_ard_3-2-1_108074_2022-10-11_final.stac-item
2022-10-11 11:08:21	ga_ls9c_ard_3-2-1_108075_2022-10-11_final.stac-item
2022-10-12 10:11:08	ga_ls9c_ard_3-2-1_099071_2022-10-12_final.stac-item
2022-10-13 09:19:07	ga_ls9c_ard_3-2-1_090080_2022-10-12_final.stac-item
2022-10-13 10:58:24	ga_ls9c_ard_3-2-1_106081_2022-10-13_final.stac-item
2022-10-21 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-10-21_final.stac-item
2022-10-23 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-10-23_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-27 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-10-27_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-10-29 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-10-29_final.stac-item
2022-11-01 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-11-01_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-04 10:20:06	ga_ls9c_ard_3-2-1_100078_2022-11-04_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-14 10:58:03	ga_ls9c_ard_3-2-1_106080_2022-11-14_final.stac-item
2022-11-15 10:04:25	ga_ls9c_ard_3-2-1_097085_2022-11-15_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-11-28 11:10:46	ga_ls9c_ard_3-2-1_108081_2022-11-28_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_final.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_final.stac-item
2022-12-09 10:52:15	ga_ls9c_ard_3-2-1_105081_2022-12-09_final.stac-item
2022-12-12 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-12-12_final.stac-item
2022-12-16 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-12-15_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2022-12-20 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-20_final.stac-item
2022-12-27 10:39:27	ga_ls9c_ard_3-2-1_103080_2022-12-27_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-08 11:03:24	ga_ls9c_ard_3-2-1_107078_2023-01-08_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-03-06 10:58:11	ga_ls9c_ard_3-2-1_106081_2023-03-06_final.stac-item
2023-03-27 11:13:44	ga_ls9c_ard_3-2-1_109074_2023-03-27_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-26 09:49:24	ga_ls9c_ard_3-2-1_095080_2023-04-26_final.stac-item
2023-04-28 09:37:24	ga_ls9c_ard_3-2-1_093081_2023-04-28_final.stac-item
2023-04-30 11:04:42	ga_ls9c_ard_3-2-1_107083_2023-04-30_final.stac-item
2023-05-07 11:08:24	ga_ls9c_ard_3-2-1_108077_2023-05-07_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_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
2023-05-16 11:04:57	ga_ls9c_ard_3-2-1_107084_2023-05-16_final.stac-item
2023-05-18 10:49:47	ga_ls9c_ard_3-2-1_105077_2023-05-18_final.stac-item
2023-05-18 10:50:35	ga_ls9c_ard_3-2-1_105079_2023-05-18_final.stac-item
2023-05-20 10:38:35	ga_ls9c_ard_3-2-1_103080_2023-05-20_final.stac-item
2023-05-28 09:51:28	ga_ls9c_ard_3-2-1_095086_2023-05-28_final.stac-item
2023-05-30 11:14:24	ga_ls9c_ard_3-2-1_109077_2023-05-30_final.stac-item
2023-06-24 11:06:28	ga_ls9c_ard_3-2-1_108073_2023-06-24_final.stac-item
2023-06-24 11:07:16	ga_ls9c_ard_3-2-1_108075_2023-06-24_final.stac-item
2023-06-24 11:07:40	ga_ls9c_ard_3-2-1_108076_2023-06-24_final.stac-item
2023-07-01 11:14:24	ga_ls9c_ard_3-2-1_109077_2023-07-01_final.stac-item
2023-07-03 09:27:58	ga_ls9c_ard_3-2-1_091089_2023-07-02_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-17 09:33:15	ga_ls9c_ard_3-2-1_093071_2023-07-17_final.stac-item
2023-07-17 11:17:19	ga_ls9c_ard_3-2-1_109084_2023-07-17_final.stac-item
2023-07-19 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-07-19_final.stac-item
2023-07-24 11:19:29	ga_ls9c_ard_3-2-1_110074_2023-07-24_final.stac-item
2023-07-25 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-25_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-07-31 09:52:04	ga_ls9c_ard_3-2-1_095087_2023-07-31_final.stac-item
2023-08-05 11:47:10	ga_ls9c_ard_3-2-1_114081_2023-08-05_final.stac-item
2023-08-06 10:51:09	ga_ls9c_ard_3-2-1_105080_2023-08-06_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-10-30 09:32:26	ga_ls9c_ard_3-2-1_092083_2023-10-30_final.stac-item
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-11-02 10:04:05	ga_ls9c_ard_3-2-1_097085_2023-11-02_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-22 09:39:30	ga_ls9c_ard_3-2-1_093085_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