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
2021-12-06 09:10:31	ga_ls9c_ard_3-2-1_089074_2021-12-05_final.stac-item
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-22 09:10:24	ga_ls9c_ard_3-2-1_089074_2021-12-21_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-07 09:10:23	ga_ls9c_ard_3-2-1_089074_2022-01-06_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-23 09:10:23	ga_ls9c_ard_3-2-1_089074_2022-01-22_final.stac-item
2022-01-23 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-23_final.stac-item
2022-01-28 11:07:49	ga_ls9c_ard_3-2-1_108074_2022-01-28_final.stac-item
2022-02-08 09:10:22	ga_ls9c_ard_3-2-1_089074_2022-02-07_final.stac-item
2022-02-13 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-02-13_final.stac-item
2022-02-24 09:10:13	ga_ls9c_ard_3-2-1_089074_2022-02-23_final.stac-item
2022-03-01 11:07:34	ga_ls9c_ard_3-2-1_108074_2022-03-01_final.stac-item
2022-03-12 09:10:09	ga_ls9c_ard_3-2-1_089074_2022-03-11_final.stac-item
2022-03-19 10:55:11	ga_ls9c_ard_3-2-1_106074_2022-03-19_final.stac-item
2022-03-28 09:10:04	ga_ls9c_ard_3-2-1_089074_2022-03-27_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-04 10:55:07	ga_ls9c_ard_3-2-1_106074_2022-04-04_final.stac-item
2022-04-13 09:09:59	ga_ls9c_ard_3-2-1_089074_2022-04-12_final.stac-item
2022-04-18 11:07:21	ga_ls9c_ard_3-2-1_108074_2022-04-18_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-04-29 09:09:52	ga_ls9c_ard_3-2-1_089074_2022-04-28_final.stac-item
2022-04-29 10:48:45	ga_ls9c_ard_3-2-1_105074_2022-04-29_final.stac-item
2022-05-04 11:07:16	ga_ls9c_ard_3-2-1_108074_2022-05-04_final.stac-item
2022-05-06 10:54:53	ga_ls9c_ard_3-2-1_106074_2022-05-06_final.stac-item
2022-05-08 10:42:30	ga_ls9c_ard_3-2-1_104074_2022-05-08_final.stac-item
2022-05-13 11:00:59	ga_ls9c_ard_3-2-1_107074_2022-05-13_final.stac-item
2022-05-15 09:09:43	ga_ls9c_ard_3-2-1_089074_2022-05-14_final.stac-item
2022-05-15 10:48:36	ga_ls9c_ard_3-2-1_105074_2022-05-15_final.stac-item
2022-05-17 10:36:12	ga_ls9c_ard_3-2-1_103074_2022-05-17_final.stac-item
2022-05-20 11:07:03	ga_ls9c_ard_3-2-1_108074_2022-05-20_final.stac-item
2022-05-31 09:09:39	ga_ls9c_ard_3-2-1_089074_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
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-08-03 09:10:12	ga_ls9c_ard_3-2-1_089074_2022-08-02_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-10 10:55:21	ga_ls9c_ard_3-2-1_106074_2022-08-10_final.stac-item
2022-08-19 09:10:20	ga_ls9c_ard_3-2-1_089074_2022-08-18_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_final.stac-item
2022-09-02 11:01:36	ga_ls9c_ard_3-2-1_107074_2022-09-02_final.stac-item
2022-09-04 09:10:21	ga_ls9c_ard_3-2-1_089074_2022-09-03_final.stac-item
2022-09-20 09:10:27	ga_ls9c_ard_3-2-1_089074_2022-09-19_final.stac-item
2022-09-25 11:07:54	ga_ls9c_ard_3-2-1_108074_2022-09-25_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-06 10:49:21	ga_ls9c_ard_3-2-1_105074_2022-10-06_final.stac-item
2022-10-15 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-10-15_final.stac-item
2022-10-20 11:01:49	ga_ls9c_ard_3-2-1_107074_2022-10-20_final.stac-item
2022-10-22 09:10:35	ga_ls9c_ard_3-2-1_089074_2022-10-21_final.stac-item
2022-10-22 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-10-22_final.stac-item
2022-10-27 11:08:00	ga_ls9c_ard_3-2-1_108074_2022-10-27_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-11-05 11:01:47	ga_ls9c_ard_3-2-1_107074_2022-11-05_final.stac-item
2022-11-07 09:10:33	ga_ls9c_ard_3-2-1_089074_2022-11-06_final.stac-item
2022-11-07 10:49:26	ga_ls9c_ard_3-2-1_105074_2022-11-07_final.stac-item
2022-11-23 09:10:35	ga_ls9c_ard_3-2-1_089074_2022-11-22_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-09 09:10:34	ga_ls9c_ard_3-2-1_089074_2022-12-08_final.stac-item
2022-12-25 09:10:31	ga_ls9c_ard_3-2-1_089074_2022-12-24_final.stac-item
2022-12-25 10:49:24	ga_ls9c_ard_3-2-1_105074_2022-12-25_final.stac-item
2022-12-30 11:07:59	ga_ls9c_ard_3-2-1_108074_2022-12-30_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-15 11:07:56	ga_ls9c_ard_3-2-1_108074_2023-01-15_final.stac-item
2023-01-26 09:10:30	ga_ls9c_ard_3-2-1_089074_2023-01-25_final.stac-item
2023-01-26 10:49:23	ga_ls9c_ard_3-2-1_105074_2023-01-26_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-09 11:01:53	ga_ls9c_ard_3-2-1_107074_2023-02-09_final.stac-item
2023-02-11 10:49:30	ga_ls9c_ard_3-2-1_105074_2023-02-11_final.stac-item
2023-02-16 11:07:59	ga_ls9c_ard_3-2-1_108074_2023-02-16_final.stac-item
2023-02-18 10:55:35	ga_ls9c_ard_3-2-1_106074_2023-02-18_final.stac-item
2023-02-27 09:10:23	ga_ls9c_ard_3-2-1_089074_2023-02-26_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-13 11:01:31	ga_ls9c_ard_3-2-1_107074_2023-03-13_final.stac-item
2023-03-15 09:10:16	ga_ls9c_ard_3-2-1_089074_2023-03-14_final.stac-item
2023-03-15 10:49:09	ga_ls9c_ard_3-2-1_105074_2023-03-15_final.stac-item
2023-03-20 11:07:40	ga_ls9c_ard_3-2-1_108074_2023-03-20_final.stac-item
2023-03-22 10:55:17	ga_ls9c_ard_3-2-1_106074_2023-03-22_final.stac-item
2023-04-05 11:07:30	ga_ls9c_ard_3-2-1_108074_2023-04-05_final.stac-item
2023-04-16 09:09:58	ga_ls9c_ard_3-2-1_089074_2023-04-15_final.stac-item
2023-04-16 10:48:51	ga_ls9c_ard_3-2-1_105074_2023-04-16_final.stac-item
2023-04-21 11:07:23	ga_ls9c_ard_3-2-1_108074_2023-04-21_final.stac-item
2023-04-30 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-04-30_final.stac-item
2023-05-02 09:09:49	ga_ls9c_ard_3-2-1_089074_2023-05-01_final.stac-item
2023-05-07 11:07:12	ga_ls9c_ard_3-2-1_108074_2023-05-07_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-16 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-05-16_final.stac-item
2023-05-18 09:09:42	ga_ls9c_ard_3-2-1_089074_2023-05-17_final.stac-item
2023-06-01 11:00:50	ga_ls9c_ard_3-2-1_107074_2023-06-01_final.stac-item
2023-06-03 09:09:35	ga_ls9c_ard_3-2-1_089074_2023-06-02_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-08 11:06:58	ga_ls9c_ard_3-2-1_108074_2023-06-08_final.stac-item
2023-06-19 09:09:27	ga_ls9c_ard_3-2-1_089074_2023-06-18_final.stac-item
2023-06-24 11:06:52	ga_ls9c_ard_3-2-1_108074_2023-06-24_final.stac-item
2023-07-03 11:00:52	ga_ls9c_ard_3-2-1_107074_2023-07-03_final.stac-item
2023-09-21 11:01:26	ga_ls9c_ard_3-2-1_107074_2023-09-21_final.stac-item
2023-09-28 11:07:32	ga_ls9c_ard_3-2-1_108074_2023-09-28_final.stac-item
2024-04-23 11:07:12	ga_ls9c_ard_3-2-1_108074_2024-04-23_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