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
2021-11-08 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-11-10 09:42:17	ga_ls9c_ard_3-2-1_094084_2021-11-10_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-18 09:39:06	ga_ls9c_ard_3-2-1_093084_2021-12-18_final.stac-item
2021-12-25 09:45:18	ga_ls9c_ard_3-2-1_094084_2021-12-25_final.stac-item
2021-12-30 10:03:50	ga_ls9c_ard_3-2-1_097084_2021-12-30_final.stac-item
2022-01-01 09:51:29	ga_ls9c_ard_3-2-1_095084_2022-01-01_final.stac-item
2022-01-03 09:39:07	ga_ls9c_ard_3-2-1_093084_2022-01-03_final.stac-item
2022-01-24 09:57:39	ga_ls9c_ard_3-2-1_096084_2022-01-24_final.stac-item
2022-02-02 09:51:28	ga_ls9c_ard_3-2-1_095084_2022-02-02_final.stac-item
2022-02-11 09:45:15	ga_ls9c_ard_3-2-1_094084_2022-02-11_final.stac-item
2022-02-18 09:51:22	ga_ls9c_ard_3-2-1_095084_2022-02-18_final.stac-item
2022-02-20 09:38:59	ga_ls9c_ard_3-2-1_093084_2022-02-20_final.stac-item
2022-02-25 09:57:27	ga_ls9c_ard_3-2-1_096084_2022-02-25_final.stac-item
2022-02-27 09:45:04	ga_ls9c_ard_3-2-1_094084_2022-02-27_final.stac-item
2022-03-24 09:38:48	ga_ls9c_ard_3-2-1_093084_2022-03-24_final.stac-item
2022-04-05 10:03:29	ga_ls9c_ard_3-2-1_097084_2022-04-05_final.stac-item
2022-04-09 09:38:44	ga_ls9c_ard_3-2-1_093084_2022-04-09_final.stac-item
2022-04-14 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-04-14_final.stac-item
2022-05-09 09:50:52	ga_ls9c_ard_3-2-1_095084_2022-05-09_final.stac-item
2022-05-27 09:38:20	ga_ls9c_ard_3-2-1_093084_2022-05-27_final.stac-item
2022-06-10 09:50:44	ga_ls9c_ard_3-2-1_095084_2022-06-10_final.stac-item
2022-06-10 11:29:37	ga_ls9c_ard_3-2-1_111084_2022-06-10_final.stac-item
2022-06-12 09:38:24	ga_ls9c_ard_3-2-1_093084_2022-06-12_final.stac-item
2022-06-17 09:57:01	ga_ls9c_ard_3-2-1_096084_2022-06-17_final.stac-item
2022-06-26 09:51:05	ga_ls9c_ard_3-2-1_095084_2022-06-26_final.stac-item
2022-06-28 09:38:43	ga_ls9c_ard_3-2-1_093084_2022-06-28_final.stac-item
2022-07-03 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-07-03_final.stac-item
2022-07-05 09:44:52	ga_ls9c_ard_3-2-1_094084_2022-07-05_final.stac-item
2022-07-10 10:03:23	ga_ls9c_ard_3-2-1_097084_2022-07-10_final.stac-item
2022-07-12 09:51:00	ga_ls9c_ard_3-2-1_095084_2022-07-12_final.stac-item
2022-07-19 09:57:15	ga_ls9c_ard_3-2-1_096084_2022-07-19_final.stac-item
2022-07-21 09:44:55	ga_ls9c_ard_3-2-1_094084_2022-07-21_final.stac-item
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-07-30 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-07-30_final.stac-item
2022-08-06 09:45:08	ga_ls9c_ard_3-2-1_094084_2022-08-06_final.stac-item
2022-08-13 11:30:16	ga_ls9c_ard_3-2-1_111084_2022-08-13_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-08-27 10:03:47	ga_ls9c_ard_3-2-1_097084_2022-08-27_final.stac-item
2022-08-31 09:39:04	ga_ls9c_ard_3-2-1_093084_2022-08-31_final.stac-item
2022-09-05 11:36:29	ga_ls9c_ard_3-2-1_112084_2022-09-05_final.stac-item
2022-09-07 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-09-07_final.stac-item
2022-09-16 09:39:08	ga_ls9c_ard_3-2-1_093084_2022-09-16_final.stac-item
2022-09-21 11:36:35	ga_ls9c_ard_3-2-1_112084_2022-09-21_final.stac-item
2022-09-23 09:45:21	ga_ls9c_ard_3-2-1_094084_2022-09-23_final.stac-item
2022-09-28 10:03:55	ga_ls9c_ard_3-2-1_097084_2022-09-28_final.stac-item
2022-10-02 09:39:11	ga_ls9c_ard_3-2-1_093084_2022-10-02_final.stac-item
2022-10-07 09:57:43	ga_ls9c_ard_3-2-1_096084_2022-10-07_final.stac-item
2022-10-07 11:36:36	ga_ls9c_ard_3-2-1_112084_2022-10-07_final.stac-item
2022-10-09 09:45:23	ga_ls9c_ard_3-2-1_094084_2022-10-09_final.stac-item
2022-10-14 10:03:59	ga_ls9c_ard_3-2-1_097084_2022-10-14_final.stac-item
2022-10-18 09:39:17	ga_ls9c_ard_3-2-1_093084_2022-10-18_final.stac-item
2022-10-23 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-10-23_final.stac-item
2022-10-25 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-10-25_final.stac-item
2022-11-03 09:39:14	ga_ls9c_ard_3-2-1_093084_2022-11-03_final.stac-item
2022-11-08 11:36:42	ga_ls9c_ard_3-2-1_112084_2022-11-08_final.stac-item
2022-11-10 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-11-10_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-17 11:30:33	ga_ls9c_ard_3-2-1_111084_2022-11-17_final.stac-item
2022-11-19 09:39:18	ga_ls9c_ard_3-2-1_093084_2022-11-19_final.stac-item
2022-11-24 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-11-24_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2022-12-03 09:51:36	ga_ls9c_ard_3-2-1_095084_2022-12-03_final.stac-item
2022-12-05 09:39:16	ga_ls9c_ard_3-2-1_093084_2022-12-05_final.stac-item
2022-12-10 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-12-10_final.stac-item
2022-12-10 11:36:42	ga_ls9c_ard_3-2-1_112084_2022-12-10_final.stac-item
2022-12-12 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-12-12_final.stac-item
2022-12-19 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-12-19_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-11 09:57:48	ga_ls9c_ard_3-2-1_096084_2023-01-11_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-18 10:03:53	ga_ls9c_ard_3-2-1_097084_2023-01-18_final.stac-item
2023-01-20 09:51:29	ga_ls9c_ard_3-2-1_095084_2023-01-20_final.stac-item
2023-01-22 09:39:08	ga_ls9c_ard_3-2-1_093084_2023-01-22_final.stac-item
2023-01-27 11:36:40	ga_ls9c_ard_3-2-1_112084_2023-01-27_final.stac-item
2023-02-07 09:39:20	ga_ls9c_ard_3-2-1_093084_2023-02-07_final.stac-item
2023-03-09 09:51:20	ga_ls9c_ard_3-2-1_095084_2023-03-09_final.stac-item
2023-03-18 09:45:09	ga_ls9c_ard_3-2-1_094084_2023-03-18_final.stac-item
2023-03-23 10:03:38	ga_ls9c_ard_3-2-1_097084_2023-03-23_final.stac-item
2023-03-27 09:38:50	ga_ls9c_ard_3-2-1_093084_2023-03-27_final.stac-item
2023-04-01 09:57:20	ga_ls9c_ard_3-2-1_096084_2023-04-01_final.stac-item
2023-04-12 09:38:43	ga_ls9c_ard_3-2-1_093084_2023-04-12_final.stac-item
2023-04-17 09:57:13	ga_ls9c_ard_3-2-1_096084_2023-04-17_final.stac-item
2023-05-05 09:44:39	ga_ls9c_ard_3-2-1_094084_2023-05-05_final.stac-item
2023-05-10 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-05-10_final.stac-item
2023-05-14 09:38:27	ga_ls9c_ard_3-2-1_093084_2023-05-14_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-05-21 09:44:33	ga_ls9c_ard_3-2-1_094084_2023-05-21_final.stac-item
2023-05-28 09:50:40	ga_ls9c_ard_3-2-1_095084_2023-05-28_final.stac-item
2023-06-15 09:38:09	ga_ls9c_ard_3-2-1_093084_2023-06-15_final.stac-item
2023-06-20 11:35:35	ga_ls9c_ard_3-2-1_112084_2023-06-20_final.stac-item
2023-06-22 09:44:20	ga_ls9c_ard_3-2-1_094084_2023-06-22_final.stac-item
2023-06-27 10:02:55	ga_ls9c_ard_3-2-1_097084_2023-06-27_final.stac-item
2023-07-01 09:38:18	ga_ls9c_ard_3-2-1_093084_2023-07-01_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_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