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
2021-11-12 10:55:49	ga_ls9c_ard_3-2-1_106068_2021-11-12_final.stac-item
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-15 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-15_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2021-12-29 10:53:05	ga_ls9c_ard_3-2-1_106068_2021-12-29_final.stac-item
2021-12-31 10:43:54	ga_ls9c_ard_3-2-1_104076_2021-12-31_final.stac-item
2021-12-31 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-31_final.stac-item
2022-01-07 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-07_final.stac-item
2022-01-14 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-01-14_final.stac-item
2022-01-16 10:44:40	ga_ls9c_ard_3-2-1_104078_2022-01-16_final.stac-item
2022-02-08 10:50:03	ga_ls9c_ard_3-2-1_105076_2022-02-08_final.stac-item
2022-03-05 10:44:27	ga_ls9c_ard_3-2-1_104078_2022-03-05_final.stac-item
2022-03-12 10:49:50	ga_ls9c_ard_3-2-1_105076_2022-03-12_final.stac-item
2022-03-21 10:44:01	ga_ls9c_ard_3-2-1_104077_2022-03-21_final.stac-item
2022-03-21 10:44:24	ga_ls9c_ard_3-2-1_104078_2022-03-21_final.stac-item
2022-03-28 10:49:45	ga_ls9c_ard_3-2-1_105076_2022-03-28_final.stac-item
2022-04-04 10:53:08	ga_ls9c_ard_3-2-1_106069_2022-04-04_final.stac-item
2022-04-06 10:43:57	ga_ls9c_ard_3-2-1_104077_2022-04-06_final.stac-item
2022-04-06 10:44:21	ga_ls9c_ard_3-2-1_104078_2022-04-06_final.stac-item
2022-04-13 10:49:40	ga_ls9c_ard_3-2-1_105076_2022-04-13_final.stac-item
2022-04-22 10:43:22	ga_ls9c_ard_3-2-1_104076_2022-04-22_final.stac-item
2022-05-06 10:52:29	ga_ls9c_ard_3-2-1_106068_2022-05-06_final.stac-item
2022-05-08 10:44:06	ga_ls9c_ard_3-2-1_104078_2022-05-08_final.stac-item
2022-05-22 10:52:18	ga_ls9c_ard_3-2-1_106068_2022-05-22_final.stac-item
2022-05-24 10:43:32	ga_ls9c_ard_3-2-1_104077_2022-05-24_final.stac-item
2022-05-24 10:43:56	ga_ls9c_ard_3-2-1_104078_2022-05-24_final.stac-item
2022-05-31 10:49:19	ga_ls9c_ard_3-2-1_105076_2022-05-31_final.stac-item
2022-06-07 10:52:20	ga_ls9c_ard_3-2-1_106068_2022-06-07_final.stac-item
2022-06-09 10:43:33	ga_ls9c_ard_3-2-1_104077_2022-06-09_final.stac-item
2022-06-16 10:49:26	ga_ls9c_ard_3-2-1_105076_2022-06-16_final.stac-item
2022-06-23 10:52:37	ga_ls9c_ard_3-2-1_106068_2022-06-23_final.stac-item
2022-06-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2022-06-23_final.stac-item
2022-06-25 10:43:30	ga_ls9c_ard_3-2-1_104076_2022-06-25_final.stac-item
2022-07-02 10:49:40	ga_ls9c_ard_3-2-1_105076_2022-07-02_final.stac-item
2022-07-09 10:52:38	ga_ls9c_ard_3-2-1_106068_2022-07-09_final.stac-item
2022-07-11 10:43:27	ga_ls9c_ard_3-2-1_104076_2022-07-11_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-07-27 10:43:37	ga_ls9c_ard_3-2-1_104076_2022-07-27_final.stac-item
2022-08-03 10:49:53	ga_ls9c_ard_3-2-1_105076_2022-08-03_final.stac-item
2022-08-10 10:52:57	ga_ls9c_ard_3-2-1_106068_2022-08-10_final.stac-item
2022-08-19 10:50:01	ga_ls9c_ard_3-2-1_105076_2022-08-19_final.stac-item
2022-08-26 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-08-26_final.stac-item
2022-08-26 10:53:25	ga_ls9c_ard_3-2-1_106069_2022-08-26_final.stac-item
2022-09-04 10:50:02	ga_ls9c_ard_3-2-1_105076_2022-09-04_final.stac-item
2022-09-20 10:50:08	ga_ls9c_ard_3-2-1_105076_2022-09-20_final.stac-item
2022-09-27 10:53:09	ga_ls9c_ard_3-2-1_106068_2022-09-27_final.stac-item
2022-09-29 10:44:23	ga_ls9c_ard_3-2-1_104077_2022-09-29_final.stac-item
2022-10-06 10:50:09	ga_ls9c_ard_3-2-1_105076_2022-10-06_final.stac-item
2022-10-13 10:53:13	ga_ls9c_ard_3-2-1_106068_2022-10-13_final.stac-item
2022-10-15 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-10-15_final.stac-item
2022-10-22 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-10-22_final.stac-item
2022-10-29 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-10-29_final.stac-item
2022-10-29 10:54:02	ga_ls9c_ard_3-2-1_106070_2022-10-29_final.stac-item
2022-10-31 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-10-31_final.stac-item
2022-11-07 10:50:14	ga_ls9c_ard_3-2-1_105076_2022-11-07_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-11-23 10:50:16	ga_ls9c_ard_3-2-1_105076_2022-11-23_final.stac-item
2022-11-30 10:53:12	ga_ls9c_ard_3-2-1_106068_2022-11-30_final.stac-item
2022-12-02 10:44:25	ga_ls9c_ard_3-2-1_104077_2022-12-02_final.stac-item
2022-12-09 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-12-09_final.stac-item
2022-12-18 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-12-18_final.stac-item
2022-12-25 10:50:12	ga_ls9c_ard_3-2-1_105076_2022-12-25_final.stac-item
2023-01-01 10:53:14	ga_ls9c_ard_3-2-1_106068_2023-01-01_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-10 10:50:14	ga_ls9c_ard_3-2-1_105076_2023-01-10_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-19 10:44:20	ga_ls9c_ard_3-2-1_104077_2023-01-19_final.stac-item
2023-01-26 10:50:11	ga_ls9c_ard_3-2-1_105076_2023-01-26_final.stac-item
2023-02-02 10:53:16	ga_ls9c_ard_3-2-1_106068_2023-02-02_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-02-18 10:53:12	ga_ls9c_ard_3-2-1_106068_2023-02-18_final.stac-item
2023-02-20 10:44:23	ga_ls9c_ard_3-2-1_104077_2023-02-20_final.stac-item
2023-02-27 10:50:04	ga_ls9c_ard_3-2-1_105076_2023-02-27_final.stac-item
2023-03-06 10:52:36	ga_ls9c_ard_3-2-1_106067_2023-03-06_interim.stac-item
2023-03-15 10:49:57	ga_ls9c_ard_3-2-1_105076_2023-03-15_final.stac-item
2023-03-24 10:44:06	ga_ls9c_ard_3-2-1_104077_2023-03-24_final.stac-item
2023-04-09 10:43:56	ga_ls9c_ard_3-2-1_104077_2023-04-09_final.stac-item
2023-04-16 10:49:39	ga_ls9c_ard_3-2-1_105076_2023-04-16_final.stac-item
2023-05-02 10:49:30	ga_ls9c_ard_3-2-1_105076_2023-05-02_final.stac-item
2023-05-18 10:49:23	ga_ls9c_ard_3-2-1_105076_2023-05-18_final.stac-item
2023-06-03 10:49:16	ga_ls9c_ard_3-2-1_105076_2023-06-03_final.stac-item
2023-06-10 10:52:11	ga_ls9c_ard_3-2-1_106068_2023-06-10_final.stac-item
2023-06-19 10:49:08	ga_ls9c_ard_3-2-1_105076_2023-06-19_final.stac-item
2023-07-05 10:49:20	ga_ls9c_ard_3-2-1_105076_2023-07-05_final.stac-item
2023-08-22 10:49:38	ga_ls9c_ard_3-2-1_105076_2023-08-22_final.stac-item
2023-09-07 10:49:49	ga_ls9c_ard_3-2-1_105076_2023-09-07_final.stac-item
2023-09-14 10:53:40	ga_ls9c_ard_3-2-1_106070_2023-09-14_final.stac-item
2023-09-23 10:49:51	ga_ls9c_ard_3-2-1_105076_2023-09-23_final.stac-item
2023-09-30 10:53:37	ga_ls9c_ard_3-2-1_106070_2023-09-30_final.stac-item
2023-10-09 10:49:56	ga_ls9c_ard_3-2-1_105076_2023-10-09_final.stac-item
2023-10-16 10:53:49	ga_ls9c_ard_3-2-1_106070_2023-10-16_final.stac-item
2023-11-01 10:53:44	ga_ls9c_ard_3-2-1_106070_2023-11-01_final.stac-item
2024-02-21 10:53:42	ga_ls9c_ard_3-2-1_106070_2024-02-21_final.stac-item
2024-03-08 10:53:46	ga_ls9c_ard_3-2-1_106070_2024-03-08_final.stac-item
2024-03-24 10:53:18	ga_ls9c_ard_3-2-1_106069_2024-03-24_final.stac-item
2024-04-09 10:53:10	ga_ls9c_ard_3-2-1_106069_2024-04-09_final.stac-item
2024-04-09 10:53:33	ga_ls9c_ard_3-2-1_106070_2024-04-09_final.stac-item
2024-04-25 10:52:49	ga_ls9c_ard_3-2-1_106069_2024-04-25_final.stac-item
2024-05-04 10:49:24	ga_ls9c_ard_3-2-1_105076_2024-05-04_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