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
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-12-11 11:09:05	ga_ls9c_ard_3-2-1_108077_2021-12-11_final.stac-item
2021-12-27 11:09:26	ga_ls9c_ard_3-2-1_108078_2021-12-27_final.stac-item
2022-01-10 09:42:52	ga_ls9c_ard_3-2-1_094078_2022-01-10_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-02-20 09:38:11	ga_ls9c_ard_3-2-1_093082_2022-02-20_final.stac-item
2022-03-05 10:44:51	ga_ls9c_ard_3-2-1_104079_2022-03-05_final.stac-item
2022-03-12 10:47:26	ga_ls9c_ard_3-2-1_105070_2022-03-12_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-03-27 10:08:52	ga_ls9c_ard_3-2-1_098082_2022-03-27_final.stac-item
2022-03-29 11:33:00	ga_ls9c_ard_3-2-1_112076_2022-03-29_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_final.stac-item
2022-04-08 10:31:59	ga_ls9c_ard_3-2-1_102078_2022-04-08_final.stac-item
2022-04-12 10:08:49	ga_ls9c_ard_3-2-1_098082_2022-04-12_final.stac-item
2022-05-04 11:08:52	ga_ls9c_ard_3-2-1_108078_2022-05-04_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-05-20 11:08:39	ga_ls9c_ard_3-2-1_108078_2022-05-20_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-21 11:08:54	ga_ls9c_ard_3-2-1_108078_2022-06-21_final.stac-item
2022-07-10 11:39:04	ga_ls9c_ard_3-2-1_113076_2022-07-10_final.stac-item
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final.stac-item
2022-07-24 10:14:40	ga_ls9c_ard_3-2-1_099081_2022-07-24_final.stac-item
2022-08-09 10:14:52	ga_ls9c_ard_3-2-1_099081_2022-08-09_final.stac-item
2022-08-20 09:54:24	ga_ls9c_ard_3-2-1_096076_2022-08-20_final.stac-item
2022-08-22 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-08-22_final.stac-item
2022-09-15 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-09-15_final.stac-item
2022-09-15 10:33:09	ga_ls9c_ard_3-2-1_102080_2022-09-15_final.stac-item
2022-09-19 10:08:51	ga_ls9c_ard_3-2-1_098081_2022-09-19_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-10-01 10:31:13	ga_ls9c_ard_3-2-1_102075_2022-10-01_final.stac-item
2022-10-07 11:33:49	ga_ls9c_ard_3-2-1_112077_2022-10-07_final.stac-item
2022-10-08 10:39:00	ga_ls9c_ard_3-2-1_103079_2022-10-08_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-10-26 10:23:08	ga_ls9c_ard_3-2-1_101070_2022-10-26_final.stac-item
2022-10-30 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-10-30_final.stac-item
2022-11-04 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-11-04_final.stac-item
2022-11-07 10:52:38	ga_ls9c_ard_3-2-1_105082_2022-11-07_final.stac-item
2022-11-12 11:09:12	ga_ls9c_ard_3-2-1_108077_2022-11-12_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-12-05 09:40:03	ga_ls9c_ard_3-2-1_093086_2022-12-05_final.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-17 11:40:53	ga_ls9c_ard_3-2-1_113079_2022-12-17_final.stac-item
2022-12-30 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-30_final.stac-item
2023-01-03 10:41:17	ga_ls9c_ard_3-2-1_104069_2023-01-03_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-31 11:09:12	ga_ls9c_ard_3-2-1_108077_2023-01-31_final.stac-item
2023-02-03 10:04:02	ga_ls9c_ard_3-2-1_097084_2023-02-03_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-03-01 10:38:54	ga_ls9c_ard_3-2-1_103079_2023-03-01_final.stac-item
2023-03-02 09:42:52	ga_ls9c_ard_3-2-1_094078_2023-03-02_final.stac-item
2023-03-07 11:40:38	ga_ls9c_ard_3-2-1_113079_2023-03-07_final.stac-item
2023-03-08 10:44:59	ga_ls9c_ard_3-2-1_104079_2023-03-08_final.stac-item
2023-03-08 10:45:47	ga_ls9c_ard_3-2-1_104081_2023-03-08_final.stac-item
2023-03-25 09:48:27	ga_ls9c_ard_3-2-1_095077_2023-03-25_final.stac-item
2023-04-07 09:18:14	ga_ls9c_ard_3-2-1_090079_2023-04-06_final.stac-item
2023-04-27 10:31:03	ga_ls9c_ard_3-2-1_102076_2023-04-27_final.stac-item
2023-05-03 11:32:44	ga_ls9c_ard_3-2-1_112076_2023-05-03_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-13 10:30:54	ga_ls9c_ard_3-2-1_102076_2023-05-13_final.stac-item
2023-05-13 10:32:05	ga_ls9c_ard_3-2-1_102079_2023-05-13_final.stac-item
2023-05-19 09:53:45	ga_ls9c_ard_3-2-1_096076_2023-05-19_final.stac-item
2023-05-21 09:42:33	ga_ls9c_ard_3-2-1_094079_2023-05-21_final.stac-item
2023-05-22 10:26:12	ga_ls9c_ard_3-2-1_101080_2023-05-22_final.stac-item
2023-05-28 09:49:28	ga_ls9c_ard_3-2-1_095081_2023-05-28_final.stac-item
2023-05-29 10:30:44	ga_ls9c_ard_3-2-1_102076_2023-05-29_final.stac-item
2023-05-29 10:31:56	ga_ls9c_ard_3-2-1_102079_2023-05-29_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-20 09:53:54	ga_ls9c_ard_3-2-1_096077_2023-06-20_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-07-06 09:53:43	ga_ls9c_ard_3-2-1_096076_2023-07-06_final.stac-item
2023-07-06 11:33:00	ga_ls9c_ard_3-2-1_112077_2023-07-06_final.stac-item
2023-07-15 11:27:41	ga_ls9c_ard_3-2-1_111079_2023-07-15_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-20 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-07-20_final.stac-item
2023-07-22 09:53:46	ga_ls9c_ard_3-2-1_096076_2023-07-22_final.stac-item
2023-07-22 11:33:51	ga_ls9c_ard_3-2-1_112079_2023-07-22_final.stac-item
2023-07-25 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-25_final.stac-item
2023-07-29 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-07-29_final.stac-item
2023-08-12 10:14:29	ga_ls9c_ard_3-2-1_099081_2023-08-12_final.stac-item
2023-10-14 11:08:58	ga_ls9c_ard_3-2-1_108077_2023-10-14_final.stac-item
2023-10-14 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-10-14_final.stac-item
2023-10-17 10:00:12	ga_ls9c_ard_3-2-1_097075_2023-10-17_final.stac-item
2023-10-17 10:03:00	ga_ls9c_ard_3-2-1_097082_2023-10-17_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-10-19 09:49:27	ga_ls9c_ard_3-2-1_095079_2023-10-19_final.stac-item
2023-10-24 10:08:46	ga_ls9c_ard_3-2-1_098081_2023-10-24_final.stac-item
2023-10-26 09:54:24	ga_ls9c_ard_3-2-1_096076_2023-10-26_final.stac-item
2023-10-28 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-28_final.stac-item
2023-11-04 09:48:56	ga_ls9c_ard_3-2-1_095078_2023-11-04_final.stac-item
2023-11-04 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-11-04_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_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