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
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-05 11:14:05	ga_ls9c_ard_3-2-1_109073_2021-11-05_final.stac-item
2021-11-09 10:36:36	ga_ls9c_ard_3-2-1_103073_2021-11-09_final.stac-item
2021-11-10 11:16:34	ga_ls9c_ard_3-2-1_110073_2021-11-10_final.stac-item
2021-11-12 09:18:45	ga_ls9c_ard_3-2-1_091072_2021-11-11_final.stac-item
2021-11-12 10:57:49	ga_ls9c_ard_3-2-1_106073_2021-11-12_final.stac-item
2021-11-14 10:39:04	ga_ls9c_ard_3-2-1_103073_2021-11-14_final.stac-item
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-11-22 11:02:44	ga_ls9c_ard_3-2-1_107073_2021-11-22_final.stac-item
2021-12-06 10:48:36	ga_ls9c_ard_3-2-1_105072_2021-12-06_final.stac-item
2021-12-15 10:42:19	ga_ls9c_ard_3-2-1_104072_2021-12-15_final.stac-item
2021-12-22 10:48:29	ga_ls9c_ard_3-2-1_105072_2021-12-22_final.stac-item
2021-12-29 10:54:40	ga_ls9c_ard_3-2-1_106072_2021-12-29_final.stac-item
2022-01-16 10:42:16	ga_ls9c_ard_3-2-1_104072_2022-01-16_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-02-01 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-02-01_final.stac-item
2022-02-15 10:54:35	ga_ls9c_ard_3-2-1_106072_2022-02-15_final.stac-item
2022-02-17 10:42:12	ga_ls9c_ard_3-2-1_104072_2022-02-17_final.stac-item
2022-03-21 10:42:01	ga_ls9c_ard_3-2-1_104072_2022-03-21_final.stac-item
2022-03-26 09:21:38	ga_ls9c_ard_3-2-1_091072_2022-03-25_final.stac-item
2022-04-22 10:41:46	ga_ls9c_ard_3-2-1_104072_2022-04-22_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-08 10:41:42	ga_ls9c_ard_3-2-1_104072_2022-05-08_final.stac-item
2022-05-15 10:47:48	ga_ls9c_ard_3-2-1_105072_2022-05-15_final.stac-item
2022-05-22 10:53:54	ga_ls9c_ard_3-2-1_106072_2022-05-22_final.stac-item
2022-06-07 10:53:55	ga_ls9c_ard_3-2-1_106072_2022-06-07_final.stac-item
2022-06-09 10:41:34	ga_ls9c_ard_3-2-1_104072_2022-06-09_final.stac-item
2022-06-12 11:12:54	ga_ls9c_ard_3-2-1_109073_2022-06-12_final.stac-item
2022-06-25 10:41:55	ga_ls9c_ard_3-2-1_104072_2022-06-25_final.stac-item
2022-06-30 11:00:51	ga_ls9c_ard_3-2-1_107073_2022-06-30_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-23 09:28:12	ga_ls9c_ard_3-2-1_092073_2022-07-22_final.stac-item
2022-07-25 10:54:21	ga_ls9c_ard_3-2-1_106072_2022-07-25_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-03 10:48:18	ga_ls9c_ard_3-2-1_105072_2022-08-03_final.stac-item
2022-08-08 11:07:17	ga_ls9c_ard_3-2-1_108073_2022-08-08_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-08-26 10:54:37	ga_ls9c_ard_3-2-1_106072_2022-08-26_final.stac-item
2022-08-28 10:42:16	ga_ls9c_ard_3-2-1_104072_2022-08-28_final.stac-item
2022-09-02 09:21:55	ga_ls9c_ard_3-2-1_091072_2022-09-01_final.stac-item
2022-09-11 10:54:38	ga_ls9c_ard_3-2-1_106072_2022-09-11_final.stac-item
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2022-10-06 10:48:33	ga_ls9c_ard_3-2-1_105072_2022-10-06_final.stac-item
2023-02-16 11:07:12	ga_ls9c_ard_3-2-1_108072_2023-02-16_final.stac-item
2023-03-13 11:00:43	ga_ls9c_ard_3-2-1_107072_2023-03-13_final.stac-item
2023-04-05 11:06:42	ga_ls9c_ard_3-2-1_108072_2023-04-05_final.stac-item
2023-06-21 10:35:34	ga_ls9c_ard_3-2-1_103073_2023-06-21_final.stac-item
2023-07-01 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-07-01_final.stac-item
2023-07-19 11:00:10	ga_ls9c_ard_3-2-1_107072_2023-07-19_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-07-26 11:06:21	ga_ls9c_ard_3-2-1_108072_2023-07-26_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-07-28 10:54:01	ga_ls9c_ard_3-2-1_106072_2023-07-28_final.stac-item
2023-08-04 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-08-04_final.stac-item
2023-08-11 11:06:31	ga_ls9c_ard_3-2-1_108072_2023-08-11_final.stac-item
2023-08-13 10:54:10	ga_ls9c_ard_3-2-1_106072_2023-08-13_final.stac-item
2023-08-20 11:00:22	ga_ls9c_ard_3-2-1_107072_2023-08-20_final.stac-item
2023-08-27 11:06:39	ga_ls9c_ard_3-2-1_108072_2023-08-27_final.stac-item
2023-08-29 10:54:18	ga_ls9c_ard_3-2-1_106072_2023-08-29_final.stac-item
2023-09-05 11:00:33	ga_ls9c_ard_3-2-1_107072_2023-09-05_final.stac-item
2023-09-12 11:06:49	ga_ls9c_ard_3-2-1_108072_2023-09-12_final.stac-item
2023-09-14 10:54:28	ga_ls9c_ard_3-2-1_106072_2023-09-14_final.stac-item
2023-09-21 11:00:38	ga_ls9c_ard_3-2-1_107072_2023-09-21_final.stac-item
2023-09-28 11:06:44	ga_ls9c_ard_3-2-1_108072_2023-09-28_final.stac-item
2023-10-07 11:00:41	ga_ls9c_ard_3-2-1_107072_2023-10-07_final.stac-item
2023-10-14 11:06:58	ga_ls9c_ard_3-2-1_108072_2023-10-14_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-23 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-10-23_final.stac-item
2023-10-30 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-10-30_final.stac-item
2023-11-08 11:00:44	ga_ls9c_ard_3-2-1_107072_2023-11-08_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-24 11:00:52	ga_ls9c_ard_3-2-1_107072_2023-11-24_final.stac-item
2023-12-01 11:07:03	ga_ls9c_ard_3-2-1_108072_2023-12-01_final.stac-item
2023-12-03 10:54:40	ga_ls9c_ard_3-2-1_106072_2023-12-03_final.stac-item
2023-12-10 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-12-10_final.stac-item
2023-12-17 11:07:04	ga_ls9c_ard_3-2-1_108072_2023-12-17_final.stac-item
2023-12-19 10:54:43	ga_ls9c_ard_3-2-1_106072_2023-12-19_final.stac-item
2023-12-26 11:00:54	ga_ls9c_ard_3-2-1_107072_2023-12-26_final.stac-item
2024-01-02 11:07:01	ga_ls9c_ard_3-2-1_108072_2024-01-02_final.stac-item
2024-01-11 11:00:50	ga_ls9c_ard_3-2-1_107072_2024-01-11_final.stac-item
2024-01-18 11:07:01	ga_ls9c_ard_3-2-1_108072_2024-01-18_final.stac-item
2024-01-27 11:00:49	ga_ls9c_ard_3-2-1_107072_2024-01-27_final.stac-item
2024-02-03 11:07:03	ga_ls9c_ard_3-2-1_108072_2024-02-03_final.stac-item
2024-02-05 10:54:42	ga_ls9c_ard_3-2-1_106072_2024-02-05_final.stac-item
2024-02-12 11:00:51	ga_ls9c_ard_3-2-1_107072_2024-02-12_final.stac-item
2024-02-19 11:06:55	ga_ls9c_ard_3-2-1_108072_2024-02-19_final.stac-item
2024-02-28 11:00:42	ga_ls9c_ard_3-2-1_107072_2024-02-28_final.stac-item
2024-03-06 11:06:56	ga_ls9c_ard_3-2-1_108072_2024-03-06_final.stac-item
2024-03-15 11:00:43	ga_ls9c_ard_3-2-1_107072_2024-03-15_final.stac-item
2024-03-22 11:06:53	ga_ls9c_ard_3-2-1_108072_2024-03-22_final.stac-item
2024-03-31 11:00:35	ga_ls9c_ard_3-2-1_107072_2024-03-31_final.stac-item
2024-04-07 11:06:44	ga_ls9c_ard_3-2-1_108072_2024-04-07_final.stac-item
2024-04-16 11:00:26	ga_ls9c_ard_3-2-1_107072_2024-04-16_final.stac-item
2024-04-23 11:06:24	ga_ls9c_ard_3-2-1_108072_2024-04-23_final.stac-item
2024-05-02 11:00:10	ga_ls9c_ard_3-2-1_107072_2024-05-02_final.stac-item
2024-05-09 11:06:21	ga_ls9c_ard_3-2-1_108072_2024-05-09_final.stac-item
2024-05-18 11:00:02	ga_ls9c_ard_3-2-1_107072_2024-05-18_nrt.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