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
2021-11-03 09:56:09	ga_ls9c_ard_3-2-1_096078_2021-11-03_final.stac-item
2021-11-04 10:36:07	ga_ls9c_ard_3-2-1_103078_2021-11-04_final.stac-item
2021-11-07 09:18:40	ga_ls9c_ard_3-2-1_090078_2021-11-06_final.stac-item
2021-11-08 09:58:38	ga_ls9c_ard_3-2-1_097078_2021-11-08_final.stac-item
2021-11-09 10:38:35	ga_ls9c_ard_3-2-1_103078_2021-11-09_final.stac-item
2021-11-12 09:21:08	ga_ls9c_ard_3-2-1_091078_2021-11-11_final.stac-item
2021-11-13 10:01:06	ga_ls9c_ard_3-2-1_097078_2021-11-13_final.stac-item
2021-11-14 10:41:03	ga_ls9c_ard_3-2-1_103078_2021-11-14_final.stac-item
2021-11-18 11:42:13	ga_ls9c_ard_3-2-1_113078_2021-11-18_final.stac-item
2021-11-20 11:23:28	ga_ls9c_ard_3-2-1_110078_2021-11-20_final.stac-item
2021-11-22 11:04:43	ga_ls9c_ard_3-2-1_107078_2021-11-22_final.stac-item
2021-11-25 09:47:16	ga_ls9c_ard_3-2-1_095078_2021-11-25_final.stac-item
2021-12-09 09:42:59	ga_ls9c_ard_3-2-1_094078_2021-12-09_final.stac-item
2022-01-14 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-01-13_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-06-01 09:54:30	ga_ls9c_ard_3-2-1_096078_2022-06-01_final.stac-item
2022-06-02 10:37:46	ga_ls9c_ard_3-2-1_103078_2022-06-02_final.stac-item
2022-06-03 09:42:09	ga_ls9c_ard_3-2-1_094078_2022-06-03_final.stac-item
2022-06-07 09:17:26	ga_ls9c_ard_3-2-1_090078_2022-06-06_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-11 10:31:37	ga_ls9c_ard_3-2-1_102078_2022-06-11_final.stac-item
2022-06-16 09:11:21	ga_ls9c_ard_3-2-1_089078_2022-06-15_final.stac-item
2022-06-17 09:54:37	ga_ls9c_ard_3-2-1_096078_2022-06-17_final.stac-item
2022-06-19 09:42:19	ga_ls9c_ard_3-2-1_094078_2022-06-19_final.stac-item
2022-06-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2022-06-22_final.stac-item
2022-07-02 09:11:35	ga_ls9c_ard_3-2-1_089078_2022-07-01_final.stac-item
2022-07-04 10:38:06	ga_ls9c_ard_3-2-1_103078_2022-07-04_final.stac-item
2022-07-05 09:42:29	ga_ls9c_ard_3-2-1_094078_2022-07-05_final.stac-item
2022-07-09 09:17:44	ga_ls9c_ard_3-2-1_090078_2022-07-08_final.stac-item
2022-07-10 10:00:59	ga_ls9c_ard_3-2-1_097078_2022-07-10_final.stac-item
2022-07-12 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-13 10:31:52	ga_ls9c_ard_3-2-1_102078_2022-07-13_final.stac-item
2022-07-25 09:17:52	ga_ls9c_ard_3-2-1_090078_2022-07-24_final.stac-item
2022-07-26 10:01:09	ga_ls9c_ard_3-2-1_097078_2022-07-26_final.stac-item
2022-07-28 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-07-28_final.stac-item
2022-08-04 09:55:05	ga_ls9c_ard_3-2-1_096078_2022-08-04_final.stac-item
2022-08-11 10:01:19	ga_ls9c_ard_3-2-1_097078_2022-08-11_final.stac-item
2022-08-14 10:32:15	ga_ls9c_ard_3-2-1_102078_2022-08-14_final.stac-item
2022-08-19 09:11:56	ga_ls9c_ard_3-2-1_089078_2022-08-18_final.stac-item
2022-08-20 09:55:12	ga_ls9c_ard_3-2-1_096078_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 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-08-22_final.stac-item
2022-08-26 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-08-25_final.stac-item
2022-08-27 11:40:17	ga_ls9c_ard_3-2-1_113078_2022-08-27_final.stac-item
2022-09-02 11:03:12	ga_ls9c_ard_3-2-1_107078_2022-09-02_final.stac-item
2022-09-11 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-09-10_final.stac-item
2022-09-20 09:12:03	ga_ls9c_ard_3-2-1_089078_2022-09-19_final.stac-item
2022-09-21 09:55:19	ga_ls9c_ard_3-2-1_096078_2022-09-21_final.stac-item
2022-09-27 09:18:15	ga_ls9c_ard_3-2-1_090078_2022-09-26_final.stac-item
2022-10-01 10:32:25	ga_ls9c_ard_3-2-1_102078_2022-10-01_final.stac-item
2022-10-06 09:12:04	ga_ls9c_ard_3-2-1_089078_2022-10-05_final.stac-item
2022-10-07 09:55:19	ga_ls9c_ard_3-2-1_096078_2022-10-07_final.stac-item
2022-10-08 10:38:36	ga_ls9c_ard_3-2-1_103078_2022-10-08_final.stac-item
2022-10-13 09:18:19	ga_ls9c_ard_3-2-1_090078_2022-10-12_final.stac-item
2022-10-14 10:01:35	ga_ls9c_ard_3-2-1_097078_2022-10-14_final.stac-item
2022-10-17 10:32:30	ga_ls9c_ard_3-2-1_102078_2022-10-17_final.stac-item
2022-10-22 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-10-21_final.stac-item
2022-10-29 09:18:20	ga_ls9c_ard_3-2-1_090078_2022-10-28_final.stac-item
2022-11-02 10:32:28	ga_ls9c_ard_3-2-1_102078_2022-11-02_final.stac-item
2022-11-09 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-11-09_final.stac-item
2022-11-14 09:18:22	ga_ls9c_ard_3-2-1_090078_2022-11-13_final.stac-item
2022-11-23 09:12:11	ga_ls9c_ard_3-2-1_089078_2022-11-22_final.stac-item
2022-12-04 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-04_final.stac-item
2022-12-19 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-12-19_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2023-01-11 09:55:24	ga_ls9c_ard_3-2-1_096078_2023-01-11_final.stac-item
2023-06-19 09:11:02	ga_ls9c_ard_3-2-1_089078_2023-06-18_final.stac-item
2023-06-20 09:54:18	ga_ls9c_ard_3-2-1_096078_2023-06-20_final.stac-item
2023-06-27 10:00:31	ga_ls9c_ard_3-2-1_097078_2023-06-27_final.stac-item
2023-06-29 09:48:13	ga_ls9c_ard_3-2-1_095078_2023-06-29_final.stac-item
2023-06-30 10:31:30	ga_ls9c_ard_3-2-1_102078_2023-06-30_final.stac-item
2023-07-06 09:54:31	ga_ls9c_ard_3-2-1_096078_2023-07-06_final.stac-item
2023-07-07 10:37:47	ga_ls9c_ard_3-2-1_103078_2023-07-07_final.stac-item
2023-07-13 11:39:38	ga_ls9c_ard_3-2-1_113078_2023-07-13_final.stac-item
2023-07-15 11:27:17	ga_ls9c_ard_3-2-1_111078_2023-07-15_final.stac-item
2023-07-19 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-07-19_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 11:33:37	ga_ls9c_ard_3-2-1_112078_2023-08-07_final.stac-item
2023-08-11 11:08:55	ga_ls9c_ard_3-2-1_108078_2023-08-11_final.stac-item
2023-08-16 11:27:27	ga_ls9c_ard_3-2-1_111078_2023-08-16_final.stac-item
2023-08-18 11:15:05	ga_ls9c_ard_3-2-1_109078_2023-08-18_final.stac-item
2023-08-20 11:02:46	ga_ls9c_ard_3-2-1_107078_2023-08-20_final.stac-item
2023-08-23 11:33:43	ga_ls9c_ard_3-2-1_112078_2023-08-23_final.stac-item
2023-09-01 11:27:38	ga_ls9c_ard_3-2-1_111078_2023-09-01_final.stac-item
2023-09-07 09:11:44	ga_ls9c_ard_3-2-1_089078_2023-09-06_final.stac-item
2023-09-07 10:50:37	ga_ls9c_ard_3-2-1_105078_2023-09-07_final.stac-item
2023-09-19 11:15:24	ga_ls9c_ard_3-2-1_109078_2023-09-19_final.stac-item
2023-10-07 11:03:05	ga_ls9c_ard_3-2-1_107078_2023-10-07_final.stac-item
2023-10-14 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-10-14_final.stac-item
2023-10-17 11:40:17	ga_ls9c_ard_3-2-1_113078_2023-10-17_final.stac-item
2023-10-30 11:09:19	ga_ls9c_ard_3-2-1_108078_2023-10-30_final.stac-item
2023-11-02 11:40:10	ga_ls9c_ard_3-2-1_113078_2023-11-02_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-12-28 10:50:56	ga_ls9c_ard_3-2-1_105078_2023-12-28_final.stac-item
2024-01-04 10:57:02	ga_ls9c_ard_3-2-1_106078_2024-01-04_final.stac-item
2024-01-11 11:03:14	ga_ls9c_ard_3-2-1_107078_2024-01-11_final.stac-item
2024-01-16 11:21:47	ga_ls9c_ard_3-2-1_110078_2024-01-16_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years