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
2021-11-03 09:53:22	ga_ls9c_ard_3-2-1_096071_2021-11-03_final.stac-item
2021-11-07 10:54:33	ga_ls9c_ard_3-2-1_106071_2021-11-07_final.stac-item
2021-11-12 10:57:01	ga_ls9c_ard_3-2-1_106071_2021-11-12_final.stac-item
2021-11-16 10:19:31	ga_ls9c_ard_3-2-1_100071_2021-11-16_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2021-12-08_final.stac-item
2021-12-13 10:54:18	ga_ls9c_ard_3-2-1_106071_2021-12-13_final.stac-item
2021-12-14 09:58:40	ga_ls9c_ard_3-2-1_097071_2021-12-14_final.stac-item
2021-12-17 10:29:32	ga_ls9c_ard_3-2-1_102071_2021-12-17_final.stac-item
2021-12-26 10:23:23	ga_ls9c_ard_3-2-1_101071_2021-12-26_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-08 09:52:27	ga_ls9c_ard_3-2-1_096071_2022-01-08_final.stac-item
2022-01-09 10:35:42	ga_ls9c_ard_3-2-1_103071_2022-01-09_final.stac-item
2022-01-14 10:54:13	ga_ls9c_ard_3-2-1_106071_2022-01-14_final.stac-item
2022-01-16 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-01-16_final.stac-item
2022-01-21 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-21_final.stac-item
2022-01-31 09:58:38	ga_ls9c_ard_3-2-1_097071_2022-01-31_final.stac-item
2022-03-05 10:41:39	ga_ls9c_ard_3-2-1_104071_2022-03-05_final.stac-item
2022-03-25 10:16:52	ga_ls9c_ard_3-2-1_100071_2022-03-25_final.stac-item
2022-04-17 10:22:54	ga_ls9c_ard_3-2-1_101071_2022-04-17_final.stac-item
2022-04-20 10:53:46	ga_ls9c_ard_3-2-1_106071_2022-04-20_final.stac-item
2022-04-21 09:58:07	ga_ls9c_ard_3-2-1_097071_2022-04-21_final.stac-item
2022-05-28 10:16:25	ga_ls9c_ard_3-2-1_100071_2022-05-28_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-06-02 10:34:58	ga_ls9c_ard_3-2-1_103071_2022-06-02_final.stac-item
2022-06-07 10:53:31	ga_ls9c_ard_3-2-1_106071_2022-06-07_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-14 10:59:46	ga_ls9c_ard_3-2-1_107071_2022-06-14_final.stac-item
2022-06-20 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-06-20_final.stac-item
2022-06-23 10:53:49	ga_ls9c_ard_3-2-1_106071_2022-06-23_final.stac-item
2022-06-30 11:00:03	ga_ls9c_ard_3-2-1_107071_2022-06-30_final.stac-item
2022-07-03 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-03_final.stac-item
2022-07-04 10:35:19	ga_ls9c_ard_3-2-1_103071_2022-07-04_final.stac-item
2022-07-06 10:22:56	ga_ls9c_ard_3-2-1_101071_2022-07-06_final.stac-item
2022-07-09 10:53:49	ga_ls9c_ard_3-2-1_106071_2022-07-09_final.stac-item
2022-07-10 09:58:12	ga_ls9c_ard_3-2-1_097071_2022-07-10_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-15 10:16:42	ga_ls9c_ard_3-2-1_100071_2022-07-15_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-25 10:53:57	ga_ls9c_ard_3-2-1_106071_2022-07-25_final.stac-item
2022-07-26 09:58:21	ga_ls9c_ard_3-2-1_097071_2022-07-26_final.stac-item
2022-08-04 09:52:17	ga_ls9c_ard_3-2-1_096071_2022-08-04_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-14 10:29:27	ga_ls9c_ard_3-2-1_102071_2022-08-14_final.stac-item
2022-08-19 10:48:01	ga_ls9c_ard_3-2-1_105071_2022-08-19_final.stac-item
2022-08-20 09:52:24	ga_ls9c_ard_3-2-1_096071_2022-08-20_final.stac-item
2022-08-23 10:23:19	ga_ls9c_ard_3-2-1_101071_2022-08-23_final.stac-item
2022-08-26 10:54:13	ga_ls9c_ard_3-2-1_106071_2022-08-26_final.stac-item
2022-08-27 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-08-27_final.stac-item
2022-08-28 10:41:52	ga_ls9c_ard_3-2-1_104071_2022-08-28_final.stac-item
2022-09-01 10:17:08	ga_ls9c_ard_3-2-1_100071_2022-09-01_final.stac-item
2022-09-02 11:00:24	ga_ls9c_ard_3-2-1_107071_2022-09-02_final.stac-item
2022-09-06 10:35:40	ga_ls9c_ard_3-2-1_103071_2022-09-06_final.stac-item
2022-09-08 10:23:18	ga_ls9c_ard_3-2-1_101071_2022-09-08_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-09-15_final.stac-item
2022-09-27 10:54:21	ga_ls9c_ard_3-2-1_106071_2022-09-27_final.stac-item
2022-09-28 09:58:43	ga_ls9c_ard_3-2-1_097071_2022-09-28_final.stac-item
2022-10-03 10:17:16	ga_ls9c_ard_3-2-1_100071_2022-10-03_final.stac-item
2022-10-07 09:52:32	ga_ls9c_ard_3-2-1_096071_2022-10-07_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-17 10:29:43	ga_ls9c_ard_3-2-1_102071_2022-10-17_final.stac-item
2022-10-26 10:23:32	ga_ls9c_ard_3-2-1_101071_2022-10-26_final.stac-item
2022-10-29 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-10-29_final.stac-item
2022-10-30 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-10-30_final.stac-item
2022-11-04 10:17:18	ga_ls9c_ard_3-2-1_100071_2022-11-04_final.stac-item
2022-11-05 11:00:35	ga_ls9c_ard_3-2-1_107071_2022-11-05_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-16 10:42:06	ga_ls9c_ard_3-2-1_104071_2022-11-16_final.stac-item
2022-11-20 10:17:22	ga_ls9c_ard_3-2-1_100071_2022-11-20_final.stac-item
2022-11-25 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-11-25_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-06 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-22 10:17:19	ga_ls9c_ard_3-2-1_100071_2022-12-22_final.stac-item
2022-12-29 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-12-29_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-26 10:48:12	ga_ls9c_ard_3-2-1_105071_2023-01-26_final.stac-item
2023-02-06 10:29:46	ga_ls9c_ard_3-2-1_102071_2023-02-06_final.stac-item
2023-02-11 10:48:19	ga_ls9c_ard_3-2-1_105071_2023-02-11_final.stac-item
2023-03-08 10:41:48	ga_ls9c_ard_3-2-1_104071_2023-03-08_final.stac-item
2023-06-17 10:59:29	ga_ls9c_ard_3-2-1_107071_2023-06-17_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-07-12 10:53:35	ga_ls9c_ard_3-2-1_106071_2023-07-12_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_2023-07-16_final.stac-item
2023-07-19 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-07-19_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-08-04 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-08-04_final.stac-item
2023-08-06 10:47:33	ga_ls9c_ard_3-2-1_105071_2023-08-06_final.stac-item
2023-08-13 10:53:46	ga_ls9c_ard_3-2-1_106071_2023-08-13_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-09-08 09:52:12	ga_ls9c_ard_3-2-1_096071_2023-09-08_final.stac-item
2023-09-15 09:58:27	ga_ls9c_ard_3-2-1_097071_2023-09-15_final.stac-item
2023-09-21 11:00:14	ga_ls9c_ard_3-2-1_107071_2023-09-21_final.stac-item
2023-10-07 11:00:17	ga_ls9c_ard_3-2-1_107071_2023-10-07_final.stac-item
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-11-08 11:00:20	ga_ls9c_ard_3-2-1_107071_2023-11-08_final.stac-item
2023-11-24 11:00:28	ga_ls9c_ard_3-2-1_107071_2023-11-24_final.stac-item
2024-01-04 10:54:14	ga_ls9c_ard_3-2-1_106071_2024-01-04_final.stac-item
2024-01-27 11:00:25	ga_ls9c_ard_3-2-1_107071_2024-01-27_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