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
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-19 10:45:07	ga_ls9c_ard_3-2-1_104082_2021-11-19_final.stac-item
2021-12-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2021-12-08_final.stac-item
2021-12-13 10:55:06	ga_ls9c_ard_3-2-1_106073_2021-12-13_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2021-12-31 10:45:54	ga_ls9c_ard_3-2-1_104081_2021-12-31_final.stac-item
2022-01-07 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-07_final.stac-item
2022-01-09 10:40:05	ga_ls9c_ard_3-2-1_103082_2022-01-09_final.stac-item
2022-01-16 10:46:15	ga_ls9c_ard_3-2-1_104082_2022-01-16_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-01-23 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-23_final.stac-item
2022-02-08 10:48:51	ga_ls9c_ard_3-2-1_105073_2022-02-08_final.stac-item
2022-02-08 10:50:27	ga_ls9c_ard_3-2-1_105077_2022-02-08_final.stac-item
2022-02-08 10:51:15	ga_ls9c_ard_3-2-1_105079_2022-02-08_final.stac-item
2022-02-10 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-02-10_final.stac-item
2022-02-15 10:54:59	ga_ls9c_ard_3-2-1_106073_2022-02-15_final.stac-item
2022-02-17 10:46:12	ga_ls9c_ard_3-2-1_104082_2022-02-17_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-02-24 10:51:06	ga_ls9c_ard_3-2-1_105079_2022-02-24_final.stac-item
2022-03-05 10:46:02	ga_ls9c_ard_3-2-1_104082_2022-03-05_final.stac-item
2022-03-12 10:50:14	ga_ls9c_ard_3-2-1_105077_2022-03-12_final.stac-item
2022-03-21 10:46:00	ga_ls9c_ard_3-2-1_104082_2022-03-21_final.stac-item
2022-04-06 10:45:57	ga_ls9c_ard_3-2-1_104082_2022-04-06_final.stac-item
2022-04-22 10:45:46	ga_ls9c_ard_3-2-1_104082_2022-04-22_final.stac-item
2022-04-29 10:49:33	ga_ls9c_ard_3-2-1_105076_2022-04-29_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-15 10:49:24	ga_ls9c_ard_3-2-1_105076_2022-05-15_final.stac-item
2022-05-15 10:49:48	ga_ls9c_ard_3-2-1_105077_2022-05-15_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-24 10:45:31	ga_ls9c_ard_3-2-1_104082_2022-05-24_final.stac-item
2022-05-31 10:50:31	ga_ls9c_ard_3-2-1_105079_2022-05-31_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-09 10:45:09	ga_ls9c_ard_3-2-1_104081_2022-06-09_final.stac-item
2022-06-16 10:48:14	ga_ls9c_ard_3-2-1_105073_2022-06-16_final.stac-item
2022-06-16 10:49:50	ga_ls9c_ard_3-2-1_105077_2022-06-16_final.stac-item
2022-07-02 10:50:52	ga_ls9c_ard_3-2-1_105079_2022-07-02_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final.stac-item
2022-08-19 10:48:49	ga_ls9c_ard_3-2-1_105073_2022-08-19_final.stac-item
2022-08-19 10:50:25	ga_ls9c_ard_3-2-1_105077_2022-08-19_final.stac-item
2022-08-28 10:46:15	ga_ls9c_ard_3-2-1_104082_2022-08-28_final.stac-item
2022-09-04 10:48:50	ga_ls9c_ard_3-2-1_105073_2022-09-04_final.stac-item
2022-09-11 10:55:02	ga_ls9c_ard_3-2-1_106073_2022-09-11_final.stac-item
2022-09-13 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-09-13_final.stac-item
2022-09-20 10:48:56	ga_ls9c_ard_3-2-1_105073_2022-09-20_final.stac-item
2022-10-06 10:50:33	ga_ls9c_ard_3-2-1_105077_2022-10-06_final.stac-item
2022-10-15 10:46:03	ga_ls9c_ard_3-2-1_104081_2022-10-15_final.stac-item
2022-10-15 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-15_final.stac-item
2022-11-09 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-09_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-23 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-11-23_final.stac-item
2022-11-23 10:50:40	ga_ls9c_ard_3-2-1_105077_2022-11-23_final.stac-item
2022-12-02 10:46:01	ga_ls9c_ard_3-2-1_104081_2022-12-02_final.stac-item
2022-12-09 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-12-09_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-18 10:46:03	ga_ls9c_ard_3-2-1_104081_2022-12-18_final.stac-item
2023-01-03 10:46:04	ga_ls9c_ard_3-2-1_104081_2023-01-03_final.stac-item
2023-01-10 10:50:38	ga_ls9c_ard_3-2-1_105077_2023-01-10_final.stac-item
2023-01-12 10:40:15	ga_ls9c_ard_3-2-1_103082_2023-01-12_final.stac-item
2023-01-19 10:46:20	ga_ls9c_ard_3-2-1_104082_2023-01-19_final.stac-item
2023-01-26 10:50:35	ga_ls9c_ard_3-2-1_105077_2023-01-26_final.stac-item
2023-01-28 10:40:15	ga_ls9c_ard_3-2-1_103082_2023-01-28_final.stac-item
2023-02-04 10:46:07	ga_ls9c_ard_3-2-1_104081_2023-02-04_final.stac-item
2023-02-11 10:50:42	ga_ls9c_ard_3-2-1_105077_2023-02-11_final.stac-item
2023-02-20 10:45:59	ga_ls9c_ard_3-2-1_104081_2023-02-20_final.stac-item
2023-03-01 10:40:06	ga_ls9c_ard_3-2-1_103082_2023-03-01_final.stac-item
2023-03-06 10:54:59	ga_ls9c_ard_3-2-1_106073_2023-03-06_final.stac-item
2023-03-08 10:46:11	ga_ls9c_ard_3-2-1_104082_2023-03-08_final.stac-item
2023-03-15 10:50:21	ga_ls9c_ard_3-2-1_105077_2023-03-15_final.stac-item
2023-03-24 10:45:41	ga_ls9c_ard_3-2-1_104081_2023-03-24_final.stac-item
2023-03-24 10:46:05	ga_ls9c_ard_3-2-1_104082_2023-03-24_final.stac-item
2023-04-02 10:39:48	ga_ls9c_ard_3-2-1_103082_2023-04-02_final.stac-item
2023-04-09 10:45:56	ga_ls9c_ard_3-2-1_104082_2023-04-09_final.stac-item
2023-04-16 10:50:03	ga_ls9c_ard_3-2-1_105077_2023-04-16_final.stac-item
2023-04-18 10:39:41	ga_ls9c_ard_3-2-1_103082_2023-04-18_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-11 10:45:40	ga_ls9c_ard_3-2-1_104082_2023-05-11_final.stac-item
2023-05-27 10:45:29	ga_ls9c_ard_3-2-1_104082_2023-05-27_final.stac-item
2023-06-05 10:39:17	ga_ls9c_ard_3-2-1_103082_2023-06-05_final.stac-item
2023-06-12 10:44:59	ga_ls9c_ard_3-2-1_104081_2023-06-12_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-28 10:45:00	ga_ls9c_ard_3-2-1_104081_2023-06-28_final.stac-item
2023-06-28 10:45:24	ga_ls9c_ard_3-2-1_104082_2023-06-28_final.stac-item
2023-07-12 10:54:22	ga_ls9c_ard_3-2-1_106073_2023-07-12_final.stac-item
2023-07-30 10:45:41	ga_ls9c_ard_3-2-1_104082_2023-07-30_final.stac-item
2023-08-13 10:54:33	ga_ls9c_ard_3-2-1_106073_2023-08-13_final.stac-item
2023-08-15 10:45:47	ga_ls9c_ard_3-2-1_104082_2023-08-15_final.stac-item
2023-08-31 10:45:57	ga_ls9c_ard_3-2-1_104082_2023-08-31_final.stac-item
2023-09-14 10:54:52	ga_ls9c_ard_3-2-1_106073_2023-09-14_final.stac-item
2023-09-16 10:45:42	ga_ls9c_ard_3-2-1_104081_2023-09-16_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-03 10:46:08	ga_ls9c_ard_3-2-1_104082_2023-11-03_final.stac-item
2023-12-03 10:55:04	ga_ls9c_ard_3-2-1_106073_2023-12-03_final.stac-item
2024-01-04 10:55:02	ga_ls9c_ard_3-2-1_106073_2024-01-04_final.stac-item
2024-02-05 10:55:06	ga_ls9c_ard_3-2-1_106073_2024-02-05_final.stac-item
2024-02-21 10:54:54	ga_ls9c_ard_3-2-1_106073_2024-02-21_final.stac-item
2024-02-23 10:46:05	ga_ls9c_ard_3-2-1_104082_2024-02-23_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years