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
2021-12-05 11:47:49	ga_ls9c_ard_3-2-1_114081_2021-12-05_final.stac-item
2021-12-12 11:52:44	ga_ls9c_ard_3-2-1_115078_2021-12-12_final.stac-item
2021-12-12 11:53:31	ga_ls9c_ard_3-2-1_115080_2021-12-12_final.stac-item
2021-12-28 11:52:42	ga_ls9c_ard_3-2-1_115078_2021-12-28_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-13 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-01-13_final.stac-item
2022-01-13 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-01-13_final.stac-item
2022-01-13 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-01-13_final.stac-item
2022-01-20 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-01-20_final.stac-item
2022-01-22 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-22_final.stac-item
2022-01-29 11:52:41	ga_ls9c_ard_3-2-1_115078_2022-01-29_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-01-29 11:53:29	ga_ls9c_ard_3-2-1_115080_2022-01-29_final.stac-item
2022-02-14 11:52:37	ga_ls9c_ard_3-2-1_115078_2022-02-14_final.stac-item
2022-02-14 11:53:01	ga_ls9c_ard_3-2-1_115079_2022-02-14_final.stac-item
2022-02-14 11:53:25	ga_ls9c_ard_3-2-1_115080_2022-02-14_final.stac-item
2022-02-23 11:47:32	ga_ls9c_ard_3-2-1_114081_2022-02-23_final.stac-item
2022-03-02 11:52:25	ga_ls9c_ard_3-2-1_115078_2022-03-02_final.stac-item
2022-03-02 11:52:49	ga_ls9c_ard_3-2-1_115079_2022-03-02_final.stac-item
2022-03-02 11:53:13	ga_ls9c_ard_3-2-1_115080_2022-03-02_final.stac-item
2022-04-03 11:52:21	ga_ls9c_ard_3-2-1_115078_2022-04-03_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-19 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-04-19_final.stac-item
2022-05-05 11:52:07	ga_ls9c_ard_3-2-1_115078_2022-05-05_final.stac-item
2022-05-21 11:51:55	ga_ls9c_ard_3-2-1_115078_2022-05-21_final.stac-item
2022-06-06 11:51:56	ga_ls9c_ard_3-2-1_115078_2022-06-06_final.stac-item
2022-06-22 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-06-22_final.stac-item
2022-06-29 11:58:04	ga_ls9c_ard_3-2-1_116077_2022-06-29_final.stac-item
2022-07-08 11:52:15	ga_ls9c_ard_3-2-1_115078_2022-07-08_final.stac-item
2022-07-17 11:47:15	ga_ls9c_ard_3-2-1_114081_2022-07-17_final.stac-item
2022-07-24 11:52:22	ga_ls9c_ard_3-2-1_115078_2022-07-24_final.stac-item
2022-07-31 11:58:14	ga_ls9c_ard_3-2-1_116077_2022-07-31_final.stac-item
2022-08-09 11:52:33	ga_ls9c_ard_3-2-1_115078_2022-08-09_final.stac-item
2022-08-18 11:47:38	ga_ls9c_ard_3-2-1_114081_2022-08-18_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-09-01 11:58:25	ga_ls9c_ard_3-2-1_116077_2022-09-01_final.stac-item
2022-09-17 11:58:29	ga_ls9c_ard_3-2-1_116077_2022-09-17_final.stac-item
2022-09-26 11:52:46	ga_ls9c_ard_3-2-1_115078_2022-09-26_final.stac-item
2023-02-17 11:52:26	ga_ls9c_ard_3-2-1_115077_2023-02-17_final.stac-item
2023-02-17 11:52:50	ga_ls9c_ard_3-2-1_115078_2023-02-17_final.stac-item
2023-02-17 11:53:14	ga_ls9c_ard_3-2-1_115079_2023-02-17_final.stac-item
2023-02-17 11:53:38	ga_ls9c_ard_3-2-1_115080_2023-02-17_final.stac-item
2023-03-21 11:52:07	ga_ls9c_ard_3-2-1_115077_2023-03-21_final.stac-item
2023-03-21 11:52:31	ga_ls9c_ard_3-2-1_115078_2023-03-21_final.stac-item
2023-03-21 11:52:55	ga_ls9c_ard_3-2-1_115079_2023-03-21_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-04-13 11:57:39	ga_ls9c_ard_3-2-1_116076_2023-04-13_final.stac-item
2023-04-13 11:58:03	ga_ls9c_ard_3-2-1_116077_2023-04-13_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-04-15 11:47:16	ga_ls9c_ard_3-2-1_114081_2023-04-15_final.stac-item
2023-04-22 11:51:51	ga_ls9c_ard_3-2-1_115077_2023-04-22_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-08 11:51:39	ga_ls9c_ard_3-2-1_115077_2023-05-08_final.stac-item
2023-05-08 11:52:03	ga_ls9c_ard_3-2-1_115078_2023-05-08_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-08 11:52:51	ga_ls9c_ard_3-2-1_115080_2023-05-08_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_2023-05-15_final.stac-item
2023-05-15 11:57:48	ga_ls9c_ard_3-2-1_116077_2023-05-15_final.stac-item
2023-05-15 11:58:12	ga_ls9c_ard_3-2-1_116078_2023-05-15_final.stac-item
2023-05-17 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-05-17_final.stac-item
2023-06-18 11:46:45	ga_ls9c_ard_3-2-1_114081_2023-06-18_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-06-25 11:51:43	ga_ls9c_ard_3-2-1_115078_2023-06-25_final.stac-item
2023-06-25 11:52:07	ga_ls9c_ard_3-2-1_115079_2023-06-25_final.stac-item
2023-06-25 11:52:31	ga_ls9c_ard_3-2-1_115080_2023-06-25_final.stac-item
2023-07-02 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-07-02_final.stac-item
2023-07-02 11:57:40	ga_ls9c_ard_3-2-1_116077_2023-07-02_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-04 11:46:56	ga_ls9c_ard_3-2-1_114081_2023-07-04_final.stac-item
2023-07-11 11:51:35	ga_ls9c_ard_3-2-1_115077_2023-07-11_final.stac-item
2023-07-11 11:51:59	ga_ls9c_ard_3-2-1_115078_2023-07-11_final.stac-item
2023-07-11 11:52:23	ga_ls9c_ard_3-2-1_115079_2023-07-11_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-09-04 11:57:45	ga_ls9c_ard_3-2-1_116076_2023-09-04_final.stac-item
2023-09-04 11:58:09	ga_ls9c_ard_3-2-1_116077_2023-09-04_final.stac-item
2023-09-04 11:58:33	ga_ls9c_ard_3-2-1_116078_2023-09-04_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-09-13 11:52:04	ga_ls9c_ard_3-2-1_115077_2023-09-13_final.stac-item
2023-09-13 11:52:28	ga_ls9c_ard_3-2-1_115078_2023-09-13_final.stac-item
2023-09-13 11:52:52	ga_ls9c_ard_3-2-1_115079_2023-09-13_final.stac-item
2023-09-13 11:53:16	ga_ls9c_ard_3-2-1_115080_2023-09-13_final.stac-item
2023-09-20 11:57:52	ga_ls9c_ard_3-2-1_116076_2023-09-20_final.stac-item
2023-09-20 11:58:16	ga_ls9c_ard_3-2-1_116077_2023-09-20_final.stac-item
2023-09-20 11:58:39	ga_ls9c_ard_3-2-1_116078_2023-09-20_final.stac-item
2023-09-22 11:47:29	ga_ls9c_ard_3-2-1_114081_2023-09-22_final.stac-item
2023-09-29 11:52:01	ga_ls9c_ard_3-2-1_115077_2023-09-29_final.stac-item
2023-09-29 11:52:25	ga_ls9c_ard_3-2-1_115078_2023-09-29_final.stac-item
2023-09-29 11:52:49	ga_ls9c_ard_3-2-1_115079_2023-09-29_final.stac-item
2023-09-29 11:53:13	ga_ls9c_ard_3-2-1_115080_2023-09-29_final.stac-item
2023-10-06 11:57:54	ga_ls9c_ard_3-2-1_116076_2023-10-06_final.stac-item
2023-10-06 11:58:18	ga_ls9c_ard_3-2-1_116077_2023-10-06_final.stac-item
2023-10-06 11:58:42	ga_ls9c_ard_3-2-1_116078_2023-10-06_final.stac-item
2023-10-08 11:47:33	ga_ls9c_ard_3-2-1_114081_2023-10-08_final.stac-item
2023-10-15 11:52:14	ga_ls9c_ard_3-2-1_115077_2023-10-15_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-15 11:53:02	ga_ls9c_ard_3-2-1_115079_2023-10-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years