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
2021-11-08 11:35:42	ga_ls9c_ard_3-2-1_113074_2021-11-08_final.stac-item
2021-11-13 11:38:10	ga_ls9c_ard_3-2-1_113074_2021-11-13_final.stac-item
2021-11-18 11:40:38	ga_ls9c_ard_3-2-1_113074_2021-11-18_final.stac-item
2021-11-18 11:41:02	ga_ls9c_ard_3-2-1_113075_2021-11-18_final.stac-item
2021-12-07 11:33:27	ga_ls9c_ard_3-2-1_112076_2021-12-07_final.stac-item
2021-12-14 11:38:45	ga_ls9c_ard_3-2-1_113074_2021-12-14_final.stac-item
2021-12-14 11:39:09	ga_ls9c_ard_3-2-1_113075_2021-12-14_final.stac-item
2021-12-23 11:33:45	ga_ls9c_ard_3-2-1_112077_2021-12-23_final.stac-item
2021-12-23 11:34:09	ga_ls9c_ard_3-2-1_112078_2021-12-23_final.stac-item
2021-12-30 11:38:44	ga_ls9c_ard_3-2-1_113074_2021-12-30_final.stac-item
2021-12-30 11:39:08	ga_ls9c_ard_3-2-1_113075_2021-12-30_final.stac-item
2021-12-30 11:39:56	ga_ls9c_ard_3-2-1_113077_2021-12-30_final.stac-item
2022-01-08 11:33:19	ga_ls9c_ard_3-2-1_112076_2022-01-08_final.stac-item
2022-01-08 11:33:43	ga_ls9c_ard_3-2-1_112077_2022-01-08_final.stac-item
2022-01-15 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-01-15_final.stac-item
2022-01-15 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-01-15_final.stac-item
2022-01-15 11:39:53	ga_ls9c_ard_3-2-1_113077_2022-01-15_final.stac-item
2022-01-24 11:33:20	ga_ls9c_ard_3-2-1_112076_2022-01-24_final.stac-item
2022-01-24 11:34:08	ga_ls9c_ard_3-2-1_112078_2022-01-24_final.stac-item
2022-01-31 11:38:43	ga_ls9c_ard_3-2-1_113074_2022-01-31_final.stac-item
2022-01-31 11:39:07	ga_ls9c_ard_3-2-1_113075_2022-01-31_final.stac-item
2022-02-09 11:34:06	ga_ls9c_ard_3-2-1_112078_2022-02-09_final.stac-item
2022-02-16 11:38:38	ga_ls9c_ard_3-2-1_113074_2022-02-16_final.stac-item
2022-02-16 11:39:50	ga_ls9c_ard_3-2-1_113077_2022-02-16_final.stac-item
2022-02-25 11:33:09	ga_ls9c_ard_3-2-1_112076_2022-02-25_final.stac-item
2022-03-04 11:38:28	ga_ls9c_ard_3-2-1_113074_2022-03-04_final.stac-item
2022-03-04 11:39:16	ga_ls9c_ard_3-2-1_113076_2022-03-04_final.stac-item
2022-03-04 11:39:40	ga_ls9c_ard_3-2-1_113077_2022-03-04_final.stac-item
2022-03-20 11:38:26	ga_ls9c_ard_3-2-1_113074_2022-03-20_final.stac-item
2022-03-20 11:38:50	ga_ls9c_ard_3-2-1_113075_2022-03-20_final.stac-item
2022-03-20 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-03-20_final.stac-item
2022-03-20 11:39:38	ga_ls9c_ard_3-2-1_113077_2022-03-20_final.stac-item
2022-03-29 11:33:00	ga_ls9c_ard_3-2-1_112076_2022-03-29_final.stac-item
2022-03-29 11:33:24	ga_ls9c_ard_3-2-1_112077_2022-03-29_final.stac-item
2022-04-05 11:38:47	ga_ls9c_ard_3-2-1_113075_2022-04-05_final.stac-item
2022-04-14 11:32:55	ga_ls9c_ard_3-2-1_112076_2022-04-14_final.stac-item
2022-04-14 11:33:19	ga_ls9c_ard_3-2-1_112077_2022-04-14_final.stac-item
2022-04-30 11:32:48	ga_ls9c_ard_3-2-1_112076_2022-04-30_final.stac-item
2022-04-30 11:33:12	ga_ls9c_ard_3-2-1_112077_2022-04-30_final.stac-item
2022-05-02 11:24:02	ga_ls9c_ard_3-2-1_110085_2022-05-02_final.stac-item
2022-05-07 11:38:08	ga_ls9c_ard_3-2-1_113074_2022-05-07_final.stac-item
2022-05-07 11:38:56	ga_ls9c_ard_3-2-1_113076_2022-05-07_final.stac-item
2022-05-07 11:39:20	ga_ls9c_ard_3-2-1_113077_2022-05-07_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-05-23 11:39:09	ga_ls9c_ard_3-2-1_113077_2022-05-23_final.stac-item
2022-06-01 11:33:23	ga_ls9c_ard_3-2-1_112078_2022-06-01_final.stac-item
2022-06-08 11:38:23	ga_ls9c_ard_3-2-1_113075_2022-06-08_final.stac-item
2022-06-17 11:33:06	ga_ls9c_ard_3-2-1_112077_2022-06-17_final.stac-item
2022-06-24 11:38:19	ga_ls9c_ard_3-2-1_113074_2022-06-24_final.stac-item
2022-06-24 11:39:07	ga_ls9c_ard_3-2-1_113076_2022-06-24_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-10 11:38:17	ga_ls9c_ard_3-2-1_113074_2022-07-10_final.stac-item
2022-07-10 11:39:28	ga_ls9c_ard_3-2-1_113077_2022-07-10_final.stac-item
2022-07-19 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-19_final.stac-item
2022-07-19 11:33:44	ga_ls9c_ard_3-2-1_112078_2022-07-19_final.stac-item
2022-08-27 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-08-27_final.stac-item
2022-08-27 11:39:53	ga_ls9c_ard_3-2-1_113077_2022-08-27_final.stac-item
2022-09-05 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-09-05_final.stac-item
2022-09-12 11:39:06	ga_ls9c_ard_3-2-1_113075_2022-09-12_final.stac-item
2022-09-21 11:33:24	ga_ls9c_ard_3-2-1_112076_2022-09-21_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-09-28 11:38:48	ga_ls9c_ard_3-2-1_113074_2022-09-28_final.stac-item
2022-09-28 11:40:00	ga_ls9c_ard_3-2-1_113077_2022-09-28_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-14 11:39:16	ga_ls9c_ard_3-2-1_113075_2022-10-14_final.stac-item
2022-10-14 11:39:40	ga_ls9c_ard_3-2-1_113076_2022-10-14_final.stac-item
2022-10-23 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-10-23_final.stac-item
2022-10-30 11:39:17	ga_ls9c_ard_3-2-1_113075_2022-10-30_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-08 11:33:54	ga_ls9c_ard_3-2-1_112077_2022-11-08_final.stac-item
2022-11-15 11:39:19	ga_ls9c_ard_3-2-1_113075_2022-11-15_final.stac-item
2022-11-15 11:40:07	ga_ls9c_ard_3-2-1_113077_2022-11-15_final.stac-item
2022-12-01 11:39:15	ga_ls9c_ard_3-2-1_113075_2022-12-01_final.stac-item
2022-12-01 11:40:03	ga_ls9c_ard_3-2-1_113077_2022-12-01_final.stac-item
2022-12-10 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-12-10_final.stac-item
2022-12-10 11:34:19	ga_ls9c_ard_3-2-1_112078_2022-12-10_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-17 11:39:17	ga_ls9c_ard_3-2-1_113075_2022-12-17_final.stac-item
2022-12-17 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-12-17_final.stac-item
2023-01-02 11:39:42	ga_ls9c_ard_3-2-1_113076_2023-01-02_final.stac-item
2023-01-11 11:34:18	ga_ls9c_ard_3-2-1_112078_2023-01-11_final.stac-item
2023-01-18 11:38:47	ga_ls9c_ard_3-2-1_113074_2023-01-18_final.stac-item
2023-01-18 11:39:34	ga_ls9c_ard_3-2-1_113076_2023-01-18_final.stac-item
2023-01-18 11:39:58	ga_ls9c_ard_3-2-1_113077_2023-01-18_final.stac-item
2023-01-27 11:33:52	ga_ls9c_ard_3-2-1_112077_2023-01-27_final.stac-item
2023-02-03 11:39:20	ga_ls9c_ard_3-2-1_113075_2023-02-03_final.stac-item
2023-02-19 11:39:14	ga_ls9c_ard_3-2-1_113075_2023-02-19_final.stac-item
2023-02-19 11:40:02	ga_ls9c_ard_3-2-1_113077_2023-02-19_final.stac-item
2023-03-07 11:39:02	ga_ls9c_ard_3-2-1_113075_2023-03-07_final.stac-item
2023-03-07 11:39:50	ga_ls9c_ard_3-2-1_113077_2023-03-07_final.stac-item
2023-03-16 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-03-16_final.stac-item
2023-03-23 11:38:56	ga_ls9c_ard_3-2-1_113075_2023-03-23_final.stac-item
2023-03-23 11:39:44	ga_ls9c_ard_3-2-1_113077_2023-03-23_final.stac-item
2023-04-01 11:33:25	ga_ls9c_ard_3-2-1_112077_2023-04-01_final.stac-item
2023-04-08 11:39:34	ga_ls9c_ard_3-2-1_113077_2023-04-08_final.stac-item
2023-04-17 11:33:19	ga_ls9c_ard_3-2-1_112077_2023-04-17_final.stac-item
2023-04-17 11:33:43	ga_ls9c_ard_3-2-1_112078_2023-04-17_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-19 11:33:26	ga_ls9c_ard_3-2-1_112078_2023-05-19_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