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
2021-11-15 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-12-25 09:42:54	ga_ls9c_ard_3-2-1_094078_2021-12-25_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-01-07 10:52:28	ga_ls9c_ard_3-2-1_105082_2022-01-07_final.stac-item
2022-01-10 09:42:52	ga_ls9c_ard_3-2-1_094078_2022-01-10_final.stac-item
2022-01-12 11:08:59	ga_ls9c_ard_3-2-1_108077_2022-01-12_final.stac-item
2022-02-11 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-02-11_final.stac-item
2022-02-13 11:09:21	ga_ls9c_ard_3-2-1_108078_2022-02-13_final.stac-item
2022-02-18 11:28:15	ga_ls9c_ard_3-2-1_111079_2022-02-18_final.stac-item
2022-02-25 11:33:33	ga_ls9c_ard_3-2-1_112077_2022-02-25_final.stac-item
2022-03-06 09:48:25	ga_ls9c_ard_3-2-1_095077_2022-03-06_final.stac-item
2022-03-06 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-03-06_final.stac-item
2022-03-12 10:50:38	ga_ls9c_ard_3-2-1_105078_2022-03-12_final.stac-item
2022-04-07 11:28:00	ga_ls9c_ard_3-2-1_111079_2022-04-07_final.stac-item
2022-04-16 11:21:20	ga_ls9c_ard_3-2-1_110078_2022-04-16_final.stac-item
2022-04-16 11:21:44	ga_ls9c_ard_3-2-1_110079_2022-04-16_final.stac-item
2022-04-24 10:31:01	ga_ls9c_ard_3-2-1_102076_2022-04-24_final.stac-item
2022-04-30 11:33:36	ga_ls9c_ard_3-2-1_112078_2022-04-30_final.stac-item
2022-04-30 11:34:00	ga_ls9c_ard_3-2-1_112079_2022-04-30_final.stac-item
2022-05-09 11:26:57	ga_ls9c_ard_3-2-1_111077_2022-05-09_final.stac-item
2022-05-11 11:15:22	ga_ls9c_ard_3-2-1_109079_2022-05-11_final.stac-item
2022-05-15 10:49:48	ga_ls9c_ard_3-2-1_105077_2022-05-15_final.stac-item
2022-05-18 11:21:27	ga_ls9c_ard_3-2-1_110079_2022-05-18_final.stac-item
2022-05-25 11:27:35	ga_ls9c_ard_3-2-1_111079_2022-05-25_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-22 10:14:31	ga_ls9c_ard_3-2-1_099081_2022-06-22_final.stac-item
2022-06-26 11:27:10	ga_ls9c_ard_3-2-1_111077_2022-06-26_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-05 11:21:22	ga_ls9c_ard_3-2-1_110078_2022-07-05_final.stac-item
2022-07-09 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-07-09_final.stac-item
2022-07-12 09:49:01	ga_ls9c_ard_3-2-1_095079_2022-07-12_final.stac-item
2022-07-16 11:02:47	ga_ls9c_ard_3-2-1_107078_2022-07-16_final.stac-item
2022-07-19 11:34:32	ga_ls9c_ard_3-2-1_112080_2022-07-19_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-07-25 10:58:45	ga_ls9c_ard_3-2-1_106083_2022-07-25_final.stac-item
2022-07-28 09:49:13	ga_ls9c_ard_3-2-1_095079_2022-07-28_final.stac-item
2022-07-29 10:31:17	ga_ls9c_ard_3-2-1_102076_2022-07-29_final.stac-item
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final.stac-item
2022-08-04 09:54:41	ga_ls9c_ard_3-2-1_096077_2022-08-04_final.stac-item
2022-08-14 10:31:27	ga_ls9c_ard_3-2-1_102076_2022-08-14_final.stac-item
2022-09-01 11:58:25	ga_ls9c_ard_3-2-1_116077_2022-09-01_final.stac-item
2022-09-14 09:48:41	ga_ls9c_ard_3-2-1_095077_2022-09-14_final.stac-item
2022-09-14 09:49:05	ga_ls9c_ard_3-2-1_095078_2022-09-14_final.stac-item
2022-09-17 11:58:29	ga_ls9c_ard_3-2-1_116077_2022-09-17_final.stac-item
2022-09-21 11:33:24	ga_ls9c_ard_3-2-1_112076_2022-09-21_final.stac-item
2022-09-23 11:21:51	ga_ls9c_ard_3-2-1_110078_2022-09-23_final.stac-item
2022-09-25 11:09:06	ga_ls9c_ard_3-2-1_108077_2022-09-25_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-07 11:33:49	ga_ls9c_ard_3-2-1_112077_2022-10-07_final.stac-item
2022-10-16 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-10-16_final.stac-item
2022-10-25 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-10-25_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-28 11:09:10	ga_ls9c_ard_3-2-1_108077_2022-11-28_final.stac-item
2022-12-13 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-12-13_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2023-01-13 09:43:02	ga_ls9c_ard_3-2-1_094078_2023-01-13_final.stac-item
2023-02-11 10:51:06	ga_ls9c_ard_3-2-1_105078_2023-02-11_final.stac-item
2023-02-15 10:27:08	ga_ls9c_ard_3-2-1_101080_2023-02-15_final.stac-item
2023-02-27 10:50:52	ga_ls9c_ard_3-2-1_105078_2023-02-27_final.stac-item
2023-03-08 10:45:47	ga_ls9c_ard_3-2-1_104081_2023-03-08_final.stac-item
2023-03-09 11:27:49	ga_ls9c_ard_3-2-1_111078_2023-03-09_final.stac-item
2023-03-16 11:33:13	ga_ls9c_ard_3-2-1_112076_2023-03-16_final.stac-item
2023-03-18 09:42:45	ga_ls9c_ard_3-2-1_094078_2023-03-18_final.stac-item
2023-03-19 10:26:49	ga_ls9c_ard_3-2-1_101080_2023-03-19_final.stac-item
2023-03-22 10:58:05	ga_ls9c_ard_3-2-1_106081_2023-03-22_final.stac-item
2023-03-25 09:49:15	ga_ls9c_ard_3-2-1_095079_2023-03-25_final.stac-item
2023-03-25 11:27:20	ga_ls9c_ard_3-2-1_111077_2023-03-25_final.stac-item
2023-04-11 10:31:09	ga_ls9c_ard_3-2-1_102076_2023-04-11_final.stac-item
2023-04-17 11:32:55	ga_ls9c_ard_3-2-1_112076_2023-04-17_final.stac-item
2023-04-17 11:34:07	ga_ls9c_ard_3-2-1_112079_2023-04-17_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 09:54:15	ga_ls9c_ard_3-2-1_096077_2023-05-03_final.stac-item
2023-05-03 11:32:44	ga_ls9c_ard_3-2-1_112076_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
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-13 10:30:54	ga_ls9c_ard_3-2-1_102076_2023-05-13_final.stac-item
2023-05-14 09:36:28	ga_ls9c_ard_3-2-1_093079_2023-05-14_final.stac-item
2023-05-19 09:53:45	ga_ls9c_ard_3-2-1_096076_2023-05-19_final.stac-item
2023-05-19 09:54:09	ga_ls9c_ard_3-2-1_096077_2023-05-19_final.stac-item
2023-05-19 09:54:33	ga_ls9c_ard_3-2-1_096078_2023-05-19_final.stac-item
2023-05-19 11:32:38	ga_ls9c_ard_3-2-1_112076_2023-05-19_final.stac-item
2023-05-19 11:33:26	ga_ls9c_ard_3-2-1_112078_2023-05-19_final.stac-item
2023-05-21 09:42:09	ga_ls9c_ard_3-2-1_094078_2023-05-21_final.stac-item
2023-05-21 09:42:33	ga_ls9c_ard_3-2-1_094079_2023-05-21_final.stac-item
2023-05-28 11:27:33	ga_ls9c_ard_3-2-1_111079_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
2023-06-04 09:53:38	ga_ls9c_ard_3-2-1_096076_2023-06-04_final.stac-item
2023-06-04 11:32:31	ga_ls9c_ard_3-2-1_112076_2023-06-04_final.stac-item
2023-06-14 10:31:48	ga_ls9c_ard_3-2-1_102079_2023-06-14_final.stac-item
2023-06-20 09:53:54	ga_ls9c_ard_3-2-1_096077_2023-06-20_final.stac-item
2023-07-06 11:32:36	ga_ls9c_ard_3-2-1_112076_2023-07-06_final.stac-item
2023-07-22 11:32:39	ga_ls9c_ard_3-2-1_112076_2023-07-22_final.stac-item
2023-07-26 11:10:20	ga_ls9c_ard_3-2-1_108082_2023-07-26_final.stac-item
2023-08-07 09:53:56	ga_ls9c_ard_3-2-1_096076_2023-08-07_final.stac-item
2023-08-07 09:54:20	ga_ls9c_ard_3-2-1_096077_2023-08-07_final.stac-item
2023-08-09 09:42:23	ga_ls9c_ard_3-2-1_094078_2023-08-09_final.stac-item
2023-08-09 09:42:47	ga_ls9c_ard_3-2-1_094079_2023-08-09_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_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