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
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-11-23 10:04:01	ga_ls9c_ard_3-2-1_098073_2021-11-23_final.stac-item
2021-12-07 09:53:22	ga_ls9c_ard_3-2-1_096073_2021-12-07_final.stac-item
2021-12-10 10:24:14	ga_ls9c_ard_3-2-1_101073_2021-12-10_final.stac-item
2021-12-12 11:51:08	ga_ls9c_ard_3-2-1_115074_2021-12-12_final.stac-item
2021-12-16 09:47:05	ga_ls9c_ard_3-2-1_095073_2021-12-16_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-19 10:17:59	ga_ls9c_ard_3-2-1_100073_2021-12-19_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-08 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-01-08_final.stac-item
2022-01-18 10:30:19	ga_ls9c_ard_3-2-1_102073_2022-01-18_final.stac-item
2022-02-02 09:47:04	ga_ls9c_ard_3-2-1_095073_2022-02-02_final.stac-item
2022-02-03 10:30:20	ga_ls9c_ard_3-2-1_102073_2022-02-03_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-18 09:46:58	ga_ls9c_ard_3-2-1_095073_2022-02-18_final.stac-item
2022-02-24 10:48:42	ga_ls9c_ard_3-2-1_105073_2022-02-24_final.stac-item
2022-02-25 09:53:04	ga_ls9c_ard_3-2-1_096073_2022-02-25_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-03-29 09:52:56	ga_ls9c_ard_3-2-1_096073_2022-03-29_final.stac-item
2022-04-10 10:17:36	ga_ls9c_ard_3-2-1_100073_2022-04-10_final.stac-item
2022-04-14 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-04-14_final.stac-item
2022-04-21 09:58:55	ga_ls9c_ard_3-2-1_097073_2022-04-21_final.stac-item
2022-04-23 09:46:33	ga_ls9c_ard_3-2-1_095073_2022-04-23_final.stac-item
2022-04-30 09:52:44	ga_ls9c_ard_3-2-1_096073_2022-04-30_final.stac-item
2022-05-07 09:58:51	ga_ls9c_ard_3-2-1_097073_2022-05-07_final.stac-item
2022-05-10 10:29:43	ga_ls9c_ard_3-2-1_102073_2022-05-10_final.stac-item
2022-05-14 10:04:57	ga_ls9c_ard_3-2-1_098073_2022-05-14_final.stac-item
2022-05-23 09:58:40	ga_ls9c_ard_3-2-1_097073_2022-05-23_final.stac-item
2022-05-26 10:29:34	ga_ls9c_ard_3-2-1_102073_2022-05-26_final.stac-item
2022-05-27 11:13:14	ga_ls9c_ard_3-2-1_109074_2022-05-27_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-06-07 10:54:43	ga_ls9c_ard_3-2-1_106074_2022-06-07_final.stac-item
2022-06-08 09:58:42	ga_ls9c_ard_3-2-1_097073_2022-06-08_final.stac-item
2022-06-24 09:59:02	ga_ls9c_ard_3-2-1_097073_2022-06-24_final.stac-item
2022-06-26 09:46:41	ga_ls9c_ard_3-2-1_095073_2022-06-26_final.stac-item
2022-06-27 10:29:57	ga_ls9c_ard_3-2-1_102073_2022-06-27_final.stac-item
2022-06-29 10:17:35	ga_ls9c_ard_3-2-1_100073_2022-06-29_final.stac-item
2022-07-01 10:05:13	ga_ls9c_ard_3-2-1_098073_2022-07-01_final.stac-item
2022-07-03 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-07-03_final.stac-item
2022-07-10 09:59:00	ga_ls9c_ard_3-2-1_097073_2022-07-10_final.stac-item
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final.stac-item
2022-07-17 10:05:11	ga_ls9c_ard_3-2-1_098073_2022-07-17_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-08-08 09:28:48	ga_ls9c_ard_3-2-1_092074_2022-08-07_final.stac-item
2022-08-09 11:50:57	ga_ls9c_ard_3-2-1_115074_2022-08-09_final.stac-item
2022-08-10 10:55:21	ga_ls9c_ard_3-2-1_106074_2022-08-10_final.stac-item
2022-08-11 09:59:20	ga_ls9c_ard_3-2-1_097073_2022-08-11_final.stac-item
2022-08-13 09:46:59	ga_ls9c_ard_3-2-1_095073_2022-08-13_final.stac-item
2022-08-20 09:53:12	ga_ls9c_ard_3-2-1_096073_2022-08-20_final.stac-item
2022-08-23 10:24:07	ga_ls9c_ard_3-2-1_101073_2022-08-23_final.stac-item
2022-08-29 09:47:02	ga_ls9c_ard_3-2-1_095073_2022-08-29_final.stac-item
2022-09-01 10:17:56	ga_ls9c_ard_3-2-1_100073_2022-09-01_final.stac-item
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final.stac-item
2022-09-12 09:59:25	ga_ls9c_ard_3-2-1_097073_2022-09-12_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-17 10:18:01	ga_ls9c_ard_3-2-1_100073_2022-09-17_final.stac-item
2022-09-19 10:05:40	ga_ls9c_ard_3-2-1_098073_2022-09-19_final.stac-item
2022-09-21 09:53:19	ga_ls9c_ard_3-2-1_096073_2022-09-21_final.stac-item
2022-09-24 10:24:14	ga_ls9c_ard_3-2-1_101073_2022-09-24_final.stac-item
2022-09-28 09:59:31	ga_ls9c_ard_3-2-1_097073_2022-09-28_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final.stac-item
2022-10-01 10:30:25	ga_ls9c_ard_3-2-1_102073_2022-10-01_final.stac-item
2022-10-06 10:48:57	ga_ls9c_ard_3-2-1_105073_2022-10-06_final.stac-item
2022-10-10 10:24:16	ga_ls9c_ard_3-2-1_101073_2022-10-10_final.stac-item
2022-10-11 09:29:04	ga_ls9c_ard_3-2-1_092074_2022-10-10_final.stac-item
2022-10-16 09:47:15	ga_ls9c_ard_3-2-1_095073_2022-10-16_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-23 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-10-23_final.stac-item
2022-10-26 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-10-26_final.stac-item
2022-10-27 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-10-26_final.stac-item
2022-10-30 09:59:36	ga_ls9c_ard_3-2-1_097073_2022-10-30_final.stac-item
2022-11-02 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-11-02_final.stac-item
2022-11-06 10:05:46	ga_ls9c_ard_3-2-1_098073_2022-11-06_final.stac-item
2022-11-07 10:49:02	ga_ls9c_ard_3-2-1_105073_2022-11-07_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-22 10:05:48	ga_ls9c_ard_3-2-1_098073_2022-11-22_final.stac-item
2022-11-23 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-11-23_final.stac-item
2022-11-27 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-11-27_final.stac-item
2022-12-03 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-12-03_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-09 10:49:03	ga_ls9c_ard_3-2-1_105073_2022-12-09_final.stac-item
2022-12-25 10:49:00	ga_ls9c_ard_3-2-1_105073_2022-12-25_final.stac-item
2023-01-04 09:47:15	ga_ls9c_ard_3-2-1_095073_2023-01-04_final.stac-item
2023-01-09 10:05:47	ga_ls9c_ard_3-2-1_098073_2023-01-09_final.stac-item
2023-01-10 10:49:03	ga_ls9c_ard_3-2-1_105073_2023-01-10_final.stac-item
2023-01-11 09:53:25	ga_ls9c_ard_3-2-1_096073_2023-01-11_final.stac-item
2023-01-18 09:59:30	ga_ls9c_ard_3-2-1_097073_2023-01-18_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-02-03 09:59:39	ga_ls9c_ard_3-2-1_097073_2023-02-03_final.stac-item
2023-02-05 09:47:18	ga_ls9c_ard_3-2-1_095073_2023-02-05_final.stac-item
2023-03-15 10:48:45	ga_ls9c_ard_3-2-1_105073_2023-03-15_final.stac-item
2023-04-16 10:48:27	ga_ls9c_ard_3-2-1_105073_2023-04-16_final.stac-item
2023-05-02 10:48:18	ga_ls9c_ard_3-2-1_105073_2023-05-02_final.stac-item
2023-05-18 10:48:11	ga_ls9c_ard_3-2-1_105073_2023-05-18_final.stac-item
2023-06-19 10:47:56	ga_ls9c_ard_3-2-1_105073_2023-06-19_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-06-25 11:50:07	ga_ls9c_ard_3-2-1_115074_2023-06-25_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-11 11:50:23	ga_ls9c_ard_3-2-1_115074_2023-07-11_final.stac-item
2023-07-26 09:28:15	ga_ls9c_ard_3-2-1_092074_2023-07-25_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