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
2021-11-02 09:16:59	ga_ls9c_ard_3-2-1_090080_2021-11-01_final.stac-item
2021-11-10 11:19:21	ga_ls9c_ard_3-2-1_110080_2021-11-10_final.stac-item
2021-11-23 10:08:00	ga_ls9c_ard_3-2-1_098083_2021-11-23_final.stac-item
2021-12-07 11:33:03	ga_ls9c_ard_3-2-1_112075_2021-12-07_final.stac-item
2021-12-09 11:22:39	ga_ls9c_ard_3-2-1_110080_2021-12-09_final.stac-item
2021-12-11 11:09:05	ga_ls9c_ard_3-2-1_108077_2021-12-11_final.stac-item
2021-12-14 09:58:16	ga_ls9c_ard_3-2-1_097070_2021-12-14_final.stac-item
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2021-12-18 11:17:35	ga_ls9c_ard_3-2-1_109083_2021-12-18_final.stac-item
2021-12-25 11:22:35	ga_ls9c_ard_3-2-1_110080_2021-12-25_final.stac-item
2021-12-27 11:09:02	ga_ls9c_ard_3-2-1_108077_2021-12-27_final.stac-item
2021-12-30 09:58:15	ga_ls9c_ard_3-2-1_097070_2021-12-30_final.stac-item
2022-01-01 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-01-01_final.stac-item
2022-01-03 11:17:36	ga_ls9c_ard_3-2-1_109083_2022-01-03_final.stac-item
2022-01-05 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-01-04_final.stac-item
2022-01-08 09:55:38	ga_ls9c_ard_3-2-1_096079_2022-01-08_final.stac-item
2022-01-12 11:08:59	ga_ls9c_ard_3-2-1_108077_2022-01-12_final.stac-item
2022-01-15 09:58:12	ga_ls9c_ard_3-2-1_097070_2022-01-15_final.stac-item
2022-01-17 09:48:15	ga_ls9c_ard_3-2-1_095076_2022-01-17_final.stac-item
2022-01-21 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-01-20_final.stac-item
2022-01-26 11:21:23	ga_ls9c_ard_3-2-1_110077_2022-01-26_final.stac-item
2022-02-04 09:37:54	ga_ls9c_ard_3-2-1_093081_2022-02-04_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-02-20 09:37:47	ga_ls9c_ard_3-2-1_093081_2022-02-20_final.stac-item
2022-02-22 11:05:29	ga_ls9c_ard_3-2-1_107084_2022-02-22_final.stac-item
2022-02-25 11:35:09	ga_ls9c_ard_3-2-1_112081_2022-02-25_final.stac-item
2022-02-28 10:26:43	ga_ls9c_ard_3-2-1_101080_2022-02-28_final.stac-item
2022-03-21 10:44:24	ga_ls9c_ard_3-2-1_104078_2022-03-21_final.stac-item
2022-03-22 09:49:59	ga_ls9c_ard_3-2-1_095081_2022-03-22_final.stac-item
2022-03-23 10:32:02	ga_ls9c_ard_3-2-1_102078_2022-03-23_final.stac-item
2022-03-24 11:13:18	ga_ls9c_ard_3-2-1_109073_2022-03-24_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-03-29 11:35:00	ga_ls9c_ard_3-2-1_112081_2022-03-29_final.stac-item
2022-04-01 10:26:37	ga_ls9c_ard_3-2-1_101080_2022-04-01_final.stac-item
2022-04-06 10:44:21	ga_ls9c_ard_3-2-1_104078_2022-04-06_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-08 10:31:59	ga_ls9c_ard_3-2-1_102078_2022-04-08_final.stac-item
2022-04-10 10:22:00	ga_ls9c_ard_3-2-1_100084_2022-04-10_final.stac-item
2022-04-11 09:24:22	ga_ls9c_ard_3-2-1_091079_2022-04-10_final.stac-item
2022-04-14 11:34:55	ga_ls9c_ard_3-2-1_112081_2022-04-14_final.stac-item
2022-04-15 10:34:06	ga_ls9c_ard_3-2-1_103068_2022-04-15_final.stac-item
2022-04-18 09:33:15	ga_ls9c_ard_3-2-1_092086_2022-04-18_final.stac-item
2022-04-20 09:17:16	ga_ls9c_ard_3-2-1_090077_2022-04-19_final.stac-item
2022-04-21 09:57:20	ga_ls9c_ard_3-2-1_097069_2022-04-21_final.stac-item
2022-04-24 10:30:37	ga_ls9c_ard_3-2-1_102075_2022-04-24_final.stac-item
2022-04-24 10:31:49	ga_ls9c_ard_3-2-1_102078_2022-04-24_final.stac-item
2022-04-27 09:24:14	ga_ls9c_ard_3-2-1_091079_2022-04-26_final.stac-item
2022-04-28 10:09:29	ga_ls9c_ard_3-2-1_098084_2022-04-28_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-06 09:17:12	ga_ls9c_ard_3-2-1_090077_2022-05-05_final.stac-item
2022-05-09 11:29:45	ga_ls9c_ard_3-2-1_111084_2022-05-09_final.stac-item
2022-05-10 10:30:31	ga_ls9c_ard_3-2-1_102075_2022-05-10_final.stac-item
2022-05-13 09:24:06	ga_ls9c_ard_3-2-1_091079_2022-05-12_final.stac-item
2022-05-14 10:09:20	ga_ls9c_ard_3-2-1_098084_2022-05-14_final.stac-item
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_2022-05-17_final.stac-item
2022-05-18 11:17:27	ga_ls9c_ard_3-2-1_110069_2022-05-18_final.stac-item
2022-05-22 09:17:00	ga_ls9c_ard_3-2-1_090077_2022-05-21_final.stac-item
2022-05-22 09:22:12	ga_ls9c_ard_3-2-1_090090_2022-05-21_final.stac-item
2022-05-22 10:53:06	ga_ls9c_ard_3-2-1_106070_2022-05-22_final.stac-item
2022-05-25 11:29:35	ga_ls9c_ard_3-2-1_111084_2022-05-25_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-06-03 09:42:09	ga_ls9c_ard_3-2-1_094078_2022-06-03_final.stac-item
2022-06-03 11:17:26	ga_ls9c_ard_3-2-1_110069_2022-06-03_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-06-07 10:53:07	ga_ls9c_ard_3-2-1_106070_2022-06-07_final.stac-item
2022-06-08 09:57:06	ga_ls9c_ard_3-2-1_097069_2022-06-08_final.stac-item
2022-06-14 09:21:41	ga_ls9c_ard_3-2-1_091073_2022-06-13_final.stac-item
2022-06-18 10:37:54	ga_ls9c_ard_3-2-1_103078_2022-06-18_final.stac-item
2022-06-19 09:42:19	ga_ls9c_ard_3-2-1_094078_2022-06-19_final.stac-item
2022-06-19 11:17:36	ga_ls9c_ard_3-2-1_110069_2022-06-19_final.stac-item
2022-06-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-06-23_final.stac-item
2022-06-24 09:57:26	ga_ls9c_ard_3-2-1_097069_2022-06-24_final.stac-item
2022-06-28 11:17:12	ga_ls9c_ard_3-2-1_109083_2022-06-28_final.stac-item
2022-06-30 09:21:58	ga_ls9c_ard_3-2-1_091073_2022-06-29_final.stac-item
2022-07-01 10:05:37	ga_ls9c_ard_3-2-1_098074_2022-07-01_final.stac-item
2022-07-05 09:42:29	ga_ls9c_ard_3-2-1_094078_2022-07-05_final.stac-item
2022-07-09 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-07-09_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-12 09:51:48	ga_ls9c_ard_3-2-1_095086_2022-07-12_final.stac-item
2022-07-14 11:13:07	ga_ls9c_ard_3-2-1_109073_2022-07-14_final.stac-item
2022-07-17 10:05:35	ga_ls9c_ard_3-2-1_098074_2022-07-17_final.stac-item
2022-07-18 09:15:58	ga_ls9c_ard_3-2-1_089089_2022-07-17_final.stac-item
2022-07-25 10:57:33	ga_ls9c_ard_3-2-1_106080_2022-07-25_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-03 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-08-02_final.stac-item
2022-08-06 11:22:25	ga_ls9c_ard_3-2-1_110080_2022-08-06_final.stac-item
2022-08-12 09:06:31	ga_ls9c_ard_3-2-1_088080_2022-08-11_final.stac-item
2022-08-13 09:52:10	ga_ls9c_ard_3-2-1_095086_2022-08-13_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-08-20 09:53:12	ga_ls9c_ard_3-2-1_096073_2022-08-20_final.stac-item
2022-08-22 11:22:31	ga_ls9c_ard_3-2-1_110080_2022-08-22_final.stac-item
2022-09-02 09:29:06	ga_ls9c_ard_3-2-1_091090_2022-09-01_final.stac-item
2022-09-04 09:10:21	ga_ls9c_ard_3-2-1_089074_2022-09-03_final.stac-item
2022-09-05 09:53:13	ga_ls9c_ard_3-2-1_096073_2022-09-05_final.stac-item
2022-09-19 10:08:27	ga_ls9c_ard_3-2-1_098080_2022-09-19_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