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
2021-11-18 11:44:13	ga_ls9c_ard_3-2-1_113083_2021-11-18_final.stac-item
2021-12-14 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-14_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2021-12-30 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-30_final.stac-item
2022-01-06 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-01-06_final.stac-item
2022-01-13 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-01-13_final.stac-item
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-01-13 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-01-13_final.stac-item
2022-01-22 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-01-22_final.stac-item
2022-01-29 11:51:29	ga_ls9c_ard_3-2-1_115075_2022-01-29_final.stac-item
2022-01-29 11:52:17	ga_ls9c_ard_3-2-1_115077_2022-01-29_final.stac-item
2022-01-31 11:42:19	ga_ls9c_ard_3-2-1_113083_2022-01-31_final.stac-item
2022-02-07 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-02-07_final.stac-item
2022-02-14 11:51:25	ga_ls9c_ard_3-2-1_115075_2022-02-14_final.stac-item
2022-02-14 11:51:49	ga_ls9c_ard_3-2-1_115076_2022-02-14_final.stac-item
2022-02-16 11:42:14	ga_ls9c_ard_3-2-1_113083_2022-02-16_final.stac-item
2022-03-02 11:51:13	ga_ls9c_ard_3-2-1_115075_2022-03-02_final.stac-item
2022-03-02 11:52:01	ga_ls9c_ard_3-2-1_115077_2022-03-02_final.stac-item
2022-03-11 11:47:03	ga_ls9c_ard_3-2-1_114080_2022-03-11_final.stac-item
2022-03-27 11:46:58	ga_ls9c_ard_3-2-1_114080_2022-03-27_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-03 11:53:09	ga_ls9c_ard_3-2-1_115080_2022-04-03_final.stac-item
2022-04-05 11:41:58	ga_ls9c_ard_3-2-1_113083_2022-04-05_final.stac-item
2022-04-19 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-04-19 11:51:48	ga_ls9c_ard_3-2-1_115077_2022-04-19_final.stac-item
2022-04-19 11:52:59	ga_ls9c_ard_3-2-1_115080_2022-04-19_final.stac-item
2022-05-05 11:50:55	ga_ls9c_ard_3-2-1_115075_2022-05-05_final.stac-item
2022-05-05 11:51:43	ga_ls9c_ard_3-2-1_115077_2022-05-05_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-07 11:41:44	ga_ls9c_ard_3-2-1_113083_2022-05-07_final.stac-item
2022-05-14 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-05-14_final.stac-item
2022-05-21 11:51:07	ga_ls9c_ard_3-2-1_115076_2022-05-21_final.stac-item
2022-05-23 11:41:33	ga_ls9c_ard_3-2-1_113083_2022-05-23_final.stac-item
2022-06-08 11:41:34	ga_ls9c_ard_3-2-1_113083_2022-06-08_final.stac-item
2022-06-15 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-06-15_final.stac-item
2022-06-24 11:41:54	ga_ls9c_ard_3-2-1_113083_2022-06-24_final.stac-item
2022-07-10 11:41:52	ga_ls9c_ard_3-2-1_113083_2022-07-10_final.stac-item
2022-07-24 11:51:34	ga_ls9c_ard_3-2-1_115076_2022-07-24_final.stac-item
2022-07-26 11:42:01	ga_ls9c_ard_3-2-1_113083_2022-07-26_final.stac-item
2022-08-09 11:51:45	ga_ls9c_ard_3-2-1_115076_2022-08-09_final.stac-item
2022-08-11 11:42:12	ga_ls9c_ard_3-2-1_113083_2022-08-11_final.stac-item
2022-08-27 11:42:16	ga_ls9c_ard_3-2-1_113083_2022-08-27_final.stac-item
2022-09-10 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-09-10_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-10-05 11:47:22	ga_ls9c_ard_3-2-1_114080_2022-10-05_final.stac-item
2022-10-12 11:52:01	ga_ls9c_ard_3-2-1_115076_2022-10-12_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-10-28 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-10-28_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-15 11:42:31	ga_ls9c_ard_3-2-1_113083_2022-11-15_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-11-29 11:52:26	ga_ls9c_ard_3-2-1_115077_2022-11-29_final.stac-item
2022-12-08 11:47:28	ga_ls9c_ard_3-2-1_114080_2022-12-08_final.stac-item
2022-12-15 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-12-15_final.stac-item
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-15 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-12-15_final.stac-item
2022-12-17 11:42:29	ga_ls9c_ard_3-2-1_113083_2022-12-17_final.stac-item
2022-12-24 11:47:25	ga_ls9c_ard_3-2-1_114080_2022-12-24_final.stac-item
2022-12-31 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-31_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-16 11:51:58	ga_ls9c_ard_3-2-1_115076_2023-01-16_final.stac-item
2023-01-16 11:53:34	ga_ls9c_ard_3-2-1_115080_2023-01-16_final.stac-item
2023-01-25 11:47:24	ga_ls9c_ard_3-2-1_114080_2023-01-25_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-19 11:42:25	ga_ls9c_ard_3-2-1_113083_2023-02-19_final.stac-item
2023-03-05 11:52:13	ga_ls9c_ard_3-2-1_115077_2023-03-05_final.stac-item
2023-03-05 11:53:25	ga_ls9c_ard_3-2-1_115080_2023-03-05_final.stac-item
2023-03-07 11:42:13	ga_ls9c_ard_3-2-1_113083_2023-03-07_final.stac-item
2023-03-12 11:57:32	ga_ls9c_ard_3-2-1_116075_2023-03-12_final.stac-item
2023-03-21 11:51:19	ga_ls9c_ard_3-2-1_115075_2023-03-21_final.stac-item
2023-03-21 11:52:07	ga_ls9c_ard_3-2-1_115077_2023-03-21_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-03-23 11:42:08	ga_ls9c_ard_3-2-1_113083_2023-03-23_final.stac-item
2023-04-06 11:51:57	ga_ls9c_ard_3-2-1_115077_2023-04-06_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-06-11 11:41:25	ga_ls9c_ard_3-2-1_113083_2023-06-11_final.stac-item
2023-06-27 11:41:24	ga_ls9c_ard_3-2-1_113083_2023-06-27_final.stac-item
2023-07-13 11:41:38	ga_ls9c_ard_3-2-1_113083_2023-07-13_final.stac-item
2023-07-27 11:50:49	ga_ls9c_ard_3-2-1_115075_2023-07-27_final.stac-item
2023-07-29 11:41:41	ga_ls9c_ard_3-2-1_113083_2023-07-29_final.stac-item
2023-08-12 11:52:35	ga_ls9c_ard_3-2-1_115079_2023-08-12_final.stac-item
2023-08-14 11:41:49	ga_ls9c_ard_3-2-1_113083_2023-08-14_final.stac-item
2023-08-19 11:57:10	ga_ls9c_ard_3-2-1_116075_2023-08-19_final.stac-item
2023-08-30 11:41:58	ga_ls9c_ard_3-2-1_113083_2023-08-30_final.stac-item
2023-09-15 11:42:07	ga_ls9c_ard_3-2-1_113083_2023-09-15_final.stac-item
2023-10-01 11:42:05	ga_ls9c_ard_3-2-1_113083_2023-10-01_final.stac-item
2023-10-17 11:42:17	ga_ls9c_ard_3-2-1_113083_2023-10-17_final.stac-item
2023-11-07 11:57:33	ga_ls9c_ard_3-2-1_116075_2023-11-07_final.stac-item
2023-11-18 11:42:15	ga_ls9c_ard_3-2-1_113083_2023-11-18_final.stac-item
2023-12-04 11:42:19	ga_ls9c_ard_3-2-1_113083_2023-12-04_final.stac-item
2023-12-20 11:42:23	ga_ls9c_ard_3-2-1_113083_2023-12-20_final.stac-item
2024-01-05 11:42:16	ga_ls9c_ard_3-2-1_113083_2024-01-05_final.stac-item
2024-01-21 11:42:17	ga_ls9c_ard_3-2-1_113083_2024-01-21_final.stac-item
2024-02-06 11:42:21	ga_ls9c_ard_3-2-1_113083_2024-02-06_final.stac-item
2024-02-20 11:51:21	ga_ls9c_ard_3-2-1_115075_2024-02-20_final.stac-item
2024-03-09 11:42:13	ga_ls9c_ard_3-2-1_113083_2024-03-09_final.stac-item
2024-03-25 11:42:08	ga_ls9c_ard_3-2-1_113083_2024-03-25_final.stac-item
2024-04-10 11:42:00	ga_ls9c_ard_3-2-1_113083_2024-04-10_final.stac-item
2024-04-24 11:50:49	ga_ls9c_ard_3-2-1_115075_2024-04-24_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