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 10:58:37	ga_ls9c_ard_3-2-1_106075_2021-11-12_final.stac-item
2021-12-08 10:37:25	ga_ls9c_ard_3-2-1_103075_2021-12-08_final.stac-item
2021-12-11 11:08:17	ga_ls9c_ard_3-2-1_108075_2021-12-11_final.stac-item
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2021-12-17 10:31:08	ga_ls9c_ard_3-2-1_102075_2021-12-17_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2021-12-31 10:43:30	ga_ls9c_ard_3-2-1_104075_2021-12-31_final.stac-item
2022-01-13 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-01-13_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-23 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-23_final.stac-item
2022-03-19 10:55:11	ga_ls9c_ard_3-2-1_106074_2022-03-19_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-04 10:55:07	ga_ls9c_ard_3-2-1_106074_2022-04-04_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-05-31 09:10:03	ga_ls9c_ard_3-2-1_089075_2022-05-30_final.stac-item
2022-06-05 11:07:29	ga_ls9c_ard_3-2-1_108075_2022-06-05_final.stac-item
2022-06-06 11:50:44	ga_ls9c_ard_3-2-1_115075_2022-06-06_final.stac-item
2022-06-07 10:54:43	ga_ls9c_ard_3-2-1_106074_2022-06-07_final.stac-item
2022-06-15 10:05:46	ga_ls9c_ard_3-2-1_098075_2022-06-15_final.stac-item
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-06-20 10:24:25	ga_ls9c_ard_3-2-1_101075_2022-06-20_final.stac-item
2022-06-22 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-06-22_final.stac-item
2022-07-02 09:10:23	ga_ls9c_ard_3-2-1_089075_2022-07-01_final.stac-item
2022-07-08 11:51:03	ga_ls9c_ard_3-2-1_115075_2022-07-08_final.stac-item
2022-07-10 09:59:47	ga_ls9c_ard_3-2-1_097075_2022-07-10_final.stac-item
2022-07-23 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-07-23_final.stac-item
2022-07-24 11:51:10	ga_ls9c_ard_3-2-1_115075_2022-07-24_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-09 11:51:21	ga_ls9c_ard_3-2-1_115075_2022-08-09_final.stac-item
2022-08-10 10:55:21	ga_ls9c_ard_3-2-1_106074_2022-08-10_final.stac-item
2022-08-14 10:31:03	ga_ls9c_ard_3-2-1_102075_2022-08-14_final.stac-item
2022-08-18 10:06:21	ga_ls9c_ard_3-2-1_098075_2022-08-18_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-08-25 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-08-25_final.stac-item
2022-08-28 10:43:27	ga_ls9c_ard_3-2-1_104075_2022-08-28_final.stac-item
2022-09-12 10:00:13	ga_ls9c_ard_3-2-1_097075_2022-09-12_final.stac-item
2022-09-28 10:00:19	ga_ls9c_ard_3-2-1_097075_2022-09-28_final.stac-item
2022-10-06 10:49:21	ga_ls9c_ard_3-2-1_105074_2022-10-06_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-13 09:17:07	ga_ls9c_ard_3-2-1_090075_2022-10-12_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-10-22 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-10-22_final.stac-item
2022-10-28 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-10-28_final.stac-item
2022-10-29 09:17:08	ga_ls9c_ard_3-2-1_090075_2022-10-28_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-10-31 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-10-31_final.stac-item
2022-11-07 10:49:26	ga_ls9c_ard_3-2-1_105074_2022-11-07_final.stac-item
2022-11-12 11:08:25	ga_ls9c_ard_3-2-1_108075_2022-11-12_final.stac-item
2022-11-16 10:43:42	ga_ls9c_ard_3-2-1_104075_2022-11-16_final.stac-item
2022-11-21 11:02:14	ga_ls9c_ard_3-2-1_107075_2022-11-21_final.stac-item
2022-11-30 09:17:07	ga_ls9c_ard_3-2-1_090075_2022-11-29_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-01 10:00:22	ga_ls9c_ard_3-2-1_097075_2022-12-01_final.stac-item
2022-12-02 10:43:38	ga_ls9c_ard_3-2-1_104075_2022-12-02_final.stac-item
2022-12-15 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-15_final.stac-item
2022-12-16 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-15_final.stac-item
2022-12-25 10:49:24	ga_ls9c_ard_3-2-1_105074_2022-12-25_final.stac-item
2023-01-26 10:49:23	ga_ls9c_ard_3-2-1_105074_2023-01-26_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-11 10:49:30	ga_ls9c_ard_3-2-1_105074_2023-02-11_final.stac-item
2023-02-18 10:55:35	ga_ls9c_ard_3-2-1_106074_2023-02-18_final.stac-item
2023-03-15 10:49:09	ga_ls9c_ard_3-2-1_105074_2023-03-15_final.stac-item
2023-03-22 10:55:17	ga_ls9c_ard_3-2-1_106074_2023-03-22_final.stac-item
2023-04-16 10:48:51	ga_ls9c_ard_3-2-1_105074_2023-04-16_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-10 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-05-10_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-16 11:56:42	ga_ls9c_ard_3-2-1_116075_2023-06-16_final.stac-item
2023-06-18 10:05:28	ga_ls9c_ard_3-2-1_098075_2023-06-18_final.stac-item
2023-06-24 11:07:16	ga_ls9c_ard_3-2-1_108075_2023-06-24_final.stac-item
2023-06-25 11:50:31	ga_ls9c_ard_3-2-1_115075_2023-06-25_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-06-27 09:59:19	ga_ls9c_ard_3-2-1_097075_2023-06-27_final.stac-item
2023-07-02 11:56:52	ga_ls9c_ard_3-2-1_116075_2023-07-02_final.stac-item
2023-07-04 10:05:39	ga_ls9c_ard_3-2-1_098075_2023-07-04_final.stac-item
2023-07-05 09:10:03	ga_ls9c_ard_3-2-1_089075_2023-07-04_final.stac-item
2023-07-11 11:50:47	ga_ls9c_ard_3-2-1_115075_2023-07-11_final.stac-item
2023-07-12 09:16:17	ga_ls9c_ard_3-2-1_090075_2023-07-11_final.stac-item
2023-07-18 11:57:00	ga_ls9c_ard_3-2-1_116075_2023-07-18_final.stac-item
2023-07-21 09:10:07	ga_ls9c_ard_3-2-1_089075_2023-07-20_final.stac-item
2023-08-03 11:57:07	ga_ls9c_ard_3-2-1_116075_2023-08-03_final.stac-item
2023-08-06 09:10:16	ga_ls9c_ard_3-2-1_089075_2023-08-05_final.stac-item
2023-08-12 11:50:59	ga_ls9c_ard_3-2-1_115075_2023-08-12_final.stac-item
2023-08-28 11:51:07	ga_ls9c_ard_3-2-1_115075_2023-08-28_final.stac-item
2023-09-04 11:57:21	ga_ls9c_ard_3-2-1_116075_2023-09-04_final.stac-item
2023-09-07 09:10:32	ga_ls9c_ard_3-2-1_089075_2023-09-06_final.stac-item
2023-09-20 11:57:28	ga_ls9c_ard_3-2-1_116075_2023-09-20_final.stac-item
2023-09-28 11:07:56	ga_ls9c_ard_3-2-1_108075_2023-09-28_final.stac-item
2023-10-14 11:08:10	ga_ls9c_ard_3-2-1_108075_2023-10-14_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-10-25 09:10:45	ga_ls9c_ard_3-2-1_089075_2023-10-24_final.stac-item
2023-11-15 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-11-15_final.stac-item
2023-11-23 11:57:40	ga_ls9c_ard_3-2-1_116075_2023-11-23_final.stac-item
2023-12-02 11:51:30	ga_ls9c_ard_3-2-1_115075_2023-12-02_final.stac-item
2023-12-09 11:57:37	ga_ls9c_ard_3-2-1_116075_2023-12-09_final.stac-item
2023-12-25 11:57:44	ga_ls9c_ard_3-2-1_116075_2023-12-25_final.stac-item
2024-01-10 11:57:39	ga_ls9c_ard_3-2-1_116075_2024-01-10_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