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
2021-11-05 09:39:48	ga_ls9c_ard_3-2-1_093084_2021-11-05_final.stac-item
2021-11-20 09:44:49	ga_ls9c_ard_3-2-1_094078_2021-11-20_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2022-01-01 09:49:05	ga_ls9c_ard_3-2-1_095078_2022-01-01_final.stac-item
2022-01-12 09:35:17	ga_ls9c_ard_3-2-1_092090_2022-01-12_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_final.stac-item
2022-03-29 09:54:07	ga_ls9c_ard_3-2-1_096076_2022-03-29_final.stac-item
2022-03-29 11:33:00	ga_ls9c_ard_3-2-1_112076_2022-03-29_final.stac-item
2022-03-31 09:42:34	ga_ls9c_ard_3-2-1_094078_2022-03-31_final.stac-item
2022-04-07 09:48:19	ga_ls9c_ard_3-2-1_095077_2022-04-07_final.stac-item
2022-04-07 09:48:43	ga_ls9c_ard_3-2-1_095078_2022-04-07_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
2022-04-16 09:42:27	ga_ls9c_ard_3-2-1_094078_2022-04-16_final.stac-item
2022-04-23 09:48:33	ga_ls9c_ard_3-2-1_095078_2022-04-23_final.stac-item
2022-04-23 11:27:26	ga_ls9c_ard_3-2-1_111078_2022-04-23_final.stac-item
2022-04-23 11:27:50	ga_ls9c_ard_3-2-1_111079_2022-04-23_final.stac-item
2022-04-30 11:33:12	ga_ls9c_ard_3-2-1_112077_2022-04-30_final.stac-item
2022-05-09 11:27:45	ga_ls9c_ard_3-2-1_111079_2022-05-09_final.stac-item
2022-05-20 11:08:15	ga_ls9c_ard_3-2-1_108077_2022-05-20_final.stac-item
2022-06-01 11:33:47	ga_ls9c_ard_3-2-1_112079_2022-06-01_final.stac-item
2022-06-03 11:21:26	ga_ls9c_ard_3-2-1_110079_2022-06-03_final.stac-item
2022-06-05 11:08:17	ga_ls9c_ard_3-2-1_108077_2022-06-05_final.stac-item
2022-06-26 11:27:34	ga_ls9c_ard_3-2-1_111078_2022-06-26_final.stac-item
2022-06-28 11:15:36	ga_ls9c_ard_3-2-1_109079_2022-06-28_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-07 11:08:35	ga_ls9c_ard_3-2-1_108077_2022-07-07_final.stac-item
2022-07-12 11:27:54	ga_ls9c_ard_3-2-1_111079_2022-07-12_final.stac-item
2022-07-14 11:15:07	ga_ls9c_ard_3-2-1_109078_2022-07-14_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 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-19_final.stac-item
2022-08-04 11:33:10	ga_ls9c_ard_3-2-1_112076_2022-08-04_final.stac-item
2022-08-06 09:41:32	ga_ls9c_ard_3-2-1_094075_2022-08-06_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-13 11:28:16	ga_ls9c_ard_3-2-1_111079_2022-08-13_final.stac-item
2022-08-20 11:33:17	ga_ls9c_ard_3-2-1_112076_2022-08-20_final.stac-item
2022-08-20 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-08-20_final.stac-item
2022-08-20 11:34:05	ga_ls9c_ard_3-2-1_112078_2022-08-20_final.stac-item
2022-08-22 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-08-22_final.stac-item
2022-08-22 11:22:08	ga_ls9c_ard_3-2-1_110079_2022-08-22_final.stac-item
2022-08-29 11:27:55	ga_ls9c_ard_3-2-1_111078_2022-08-29_final.stac-item
2022-08-29 11:28:19	ga_ls9c_ard_3-2-1_111079_2022-08-29_final.stac-item
2022-09-02 09:24:19	ga_ls9c_ard_3-2-1_091078_2022-09-01_final.stac-item
2022-09-21 11:33:48	ga_ls9c_ard_3-2-1_112077_2022-09-21_final.stac-item
2022-10-03 11:58:32	ga_ls9c_ard_3-2-1_116077_2022-10-03_final.stac-item
2022-10-31 10:46:03	ga_ls9c_ard_3-2-1_104081_2022-10-31_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-12-30 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-30_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-15 10:50:45	ga_ls9c_ard_3-2-1_105078_2023-03-15_final.stac-item
2023-03-23 11:39:44	ga_ls9c_ard_3-2-1_113077_2023-03-23_final.stac-item
2023-03-25 09:48:27	ga_ls9c_ard_3-2-1_095077_2023-03-25_final.stac-item
2023-04-03 09:42:34	ga_ls9c_ard_3-2-1_094078_2023-04-03_final.stac-item
2023-04-10 11:27:59	ga_ls9c_ard_3-2-1_111079_2023-04-10_final.stac-item
2023-04-17 11:33:43	ga_ls9c_ard_3-2-1_112078_2023-04-17_final.stac-item
2023-04-19 09:42:28	ga_ls9c_ard_3-2-1_094078_2023-04-19_final.stac-item
2023-04-26 11:27:53	ga_ls9c_ard_3-2-1_111079_2023-04-26_final.stac-item
2023-05-03 09:53:51	ga_ls9c_ard_3-2-1_096076_2023-05-03_final.stac-item
2023-05-03 11:33:08	ga_ls9c_ard_3-2-1_112077_2023-05-03_final.stac-item
2023-05-05 09:42:16	ga_ls9c_ard_3-2-1_094078_2023-05-05_final.stac-item
2023-05-12 11:27:43	ga_ls9c_ard_3-2-1_111079_2023-05-12_final.stac-item
2023-05-19 11:33:02	ga_ls9c_ard_3-2-1_112077_2023-05-19_final.stac-item
2023-05-21 11:21:26	ga_ls9c_ard_3-2-1_110079_2023-05-21_final.stac-item
2023-06-04 11:32:55	ga_ls9c_ard_3-2-1_112077_2023-06-04_final.stac-item
2023-06-04 11:33:19	ga_ls9c_ard_3-2-1_112078_2023-06-04_final.stac-item
2023-06-08 11:08:10	ga_ls9c_ard_3-2-1_108077_2023-06-08_final.stac-item
2023-06-13 11:27:02	ga_ls9c_ard_3-2-1_111078_2023-06-13_final.stac-item
2023-06-13 11:27:26	ga_ls9c_ard_3-2-1_111079_2023-06-13_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-06-24 11:08:04	ga_ls9c_ard_3-2-1_108077_2023-06-24_final.stac-item
2023-07-06 09:53:43	ga_ls9c_ard_3-2-1_096076_2023-07-06_final.stac-item
2023-07-08 11:21:04	ga_ls9c_ard_3-2-1_110078_2023-07-08_final.stac-item
2023-07-17 11:15:20	ga_ls9c_ard_3-2-1_109079_2023-07-17_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-07-22 11:33:27	ga_ls9c_ard_3-2-1_112078_2023-07-22_final.stac-item
2023-07-24 11:21:05	ga_ls9c_ard_3-2-1_110078_2023-07-24_final.stac-item
2023-08-07 09:54:44	ga_ls9c_ard_3-2-1_096078_2023-08-07_final.stac-item
2023-08-11 11:08:31	ga_ls9c_ard_3-2-1_108077_2023-08-11_final.stac-item
2023-08-18 11:15:29	ga_ls9c_ard_3-2-1_109079_2023-08-18_final.stac-item
2023-08-22 09:15:33	ga_ls9c_ard_3-2-1_089088_2023-08-21_final.stac-item
2023-08-23 09:54:02	ga_ls9c_ard_3-2-1_096076_2023-08-23_final.stac-item
2023-08-23 11:32:55	ga_ls9c_ard_3-2-1_112076_2023-08-23_final.stac-item
2023-08-23 11:33:43	ga_ls9c_ard_3-2-1_112078_2023-08-23_final.stac-item
2023-08-25 11:21:23	ga_ls9c_ard_3-2-1_110078_2023-08-25_final.stac-item
2023-09-01 11:28:02	ga_ls9c_ard_3-2-1_111079_2023-09-01_final.stac-item
2023-09-17 09:48:29	ga_ls9c_ard_3-2-1_095077_2023-09-17_final.stac-item
2023-10-10 09:54:20	ga_ls9c_ard_3-2-1_096076_2023-10-10_final.stac-item
2023-10-10 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-10-10_final.stac-item
2023-10-12 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-12_final.stac-item
2023-10-26 09:54:24	ga_ls9c_ard_3-2-1_096076_2023-10-26_final.stac-item
2023-10-28 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-28_final.stac-item
2023-12-01 11:09:27	ga_ls9c_ard_3-2-1_108078_2023-12-01_final.stac-item
2023-12-06 09:49:02	ga_ls9c_ard_3-2-1_095078_2023-12-06_final.stac-item
2024-01-06 10:45:50	ga_ls9c_ard_3-2-1_104081_2024-01-06_final.stac-item
2024-01-18 11:09:25	ga_ls9c_ard_3-2-1_108078_2024-01-18_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