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
2021-11-09 10:37:00	ga_ls9c_ard_3-2-1_103074_2021-11-09_final.stac-item
2021-11-10 11:16:34	ga_ls9c_ard_3-2-1_110073_2021-11-10_final.stac-item
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-12-05 10:05:45	ga_ls9c_ard_3-2-1_098073_2021-12-05_final.stac-item
2021-12-10 10:24:14	ga_ls9c_ard_3-2-1_101073_2021-12-10_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-19 10:17:59	ga_ls9c_ard_3-2-1_100073_2021-12-19_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-18 10:30:19	ga_ls9c_ard_3-2-1_102073_2022-01-18_final.stac-item
2022-01-30 10:55:04	ga_ls9c_ard_3-2-1_106073_2022-01-30_final.stac-item
2022-02-03 10:30:20	ga_ls9c_ard_3-2-1_102073_2022-02-03_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-15 10:54:59	ga_ls9c_ard_3-2-1_106073_2022-02-15_final.stac-item
2022-02-18 11:25:51	ga_ls9c_ard_3-2-1_111073_2022-02-18_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-04-07 11:25:37	ga_ls9c_ard_3-2-1_111073_2022-04-07_final.stac-item
2022-04-10 10:17:36	ga_ls9c_ard_3-2-1_100073_2022-04-10_final.stac-item
2022-04-23 11:25:26	ga_ls9c_ard_3-2-1_111073_2022-04-23_final.stac-item
2022-04-28 10:05:06	ga_ls9c_ard_3-2-1_098073_2022-04-28_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-10 10:29:43	ga_ls9c_ard_3-2-1_102073_2022-05-10_final.stac-item
2022-05-22 10:54:18	ga_ls9c_ard_3-2-1_106073_2022-05-22_final.stac-item
2022-05-25 11:25:12	ga_ls9c_ard_3-2-1_111073_2022-05-25_final.stac-item
2022-05-26 10:29:34	ga_ls9c_ard_3-2-1_102073_2022-05-26_final.stac-item
2022-06-15 10:04:58	ga_ls9c_ard_3-2-1_098073_2022-06-15_final.stac-item
2022-06-27 10:29:57	ga_ls9c_ard_3-2-1_102073_2022-06-27_final.stac-item
2022-06-29 10:17:35	ga_ls9c_ard_3-2-1_100073_2022-06-29_final.stac-item
2022-08-02 10:05:25	ga_ls9c_ard_3-2-1_098073_2022-08-02_final.stac-item
2022-08-10 10:54:57	ga_ls9c_ard_3-2-1_106073_2022-08-10_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-18 10:05:33	ga_ls9c_ard_3-2-1_098073_2022-08-18_final.stac-item
2022-08-23 10:24:07	ga_ls9c_ard_3-2-1_101073_2022-08-23_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-09-01 10:17:56	ga_ls9c_ard_3-2-1_100073_2022-09-01_final.stac-item
2022-09-03 10:05:35	ga_ls9c_ard_3-2-1_098073_2022-09-03_final.stac-item
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-17 10:18:01	ga_ls9c_ard_3-2-1_100073_2022-09-17_final.stac-item
2022-09-24 10:24:14	ga_ls9c_ard_3-2-1_101073_2022-09-24_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-01 10:30:25	ga_ls9c_ard_3-2-1_102073_2022-10-01_final.stac-item
2022-10-05 10:05:42	ga_ls9c_ard_3-2-1_098073_2022-10-05_final.stac-item
2022-10-10 10:24:16	ga_ls9c_ard_3-2-1_101073_2022-10-10_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-21 10:05:48	ga_ls9c_ard_3-2-1_098073_2022-10-21_final.stac-item
2022-10-26 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-10-26_final.stac-item
2022-11-02 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-11-02_final.stac-item
2022-11-17 11:26:10	ga_ls9c_ard_3-2-1_111073_2022-11-17_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-27 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-11-27_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-08 10:05:47	ga_ls9c_ard_3-2-1_098073_2022-12-08_final.stac-item
2022-12-16 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-12-16_final.stac-item
2022-12-24 10:05:44	ga_ls9c_ard_3-2-1_098073_2022-12-24_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-02-10 10:05:51	ga_ls9c_ard_3-2-1_098073_2023-02-10_final.stac-item
2023-02-26 10:05:37	ga_ls9c_ard_3-2-1_098073_2023-02-26_final.stac-item
2023-03-06 10:54:59	ga_ls9c_ard_3-2-1_106073_2023-03-06_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-14 10:05:30	ga_ls9c_ard_3-2-1_098073_2023-03-14_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-03-30 10:05:17	ga_ls9c_ard_3-2-1_098073_2023-03-30_final.stac-item
2023-04-10 11:25:36	ga_ls9c_ard_3-2-1_111073_2023-04-10_final.stac-item
2023-04-12 11:13:13	ga_ls9c_ard_3-2-1_109073_2023-04-12_final.stac-item
2023-04-15 10:05:11	ga_ls9c_ard_3-2-1_098073_2023-04-15_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-05-01 10:05:04	ga_ls9c_ard_3-2-1_098073_2023-05-01_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-17 10:04:56	ga_ls9c_ard_3-2-1_098073_2023-05-17_final.stac-item
2023-05-25 10:54:15	ga_ls9c_ard_3-2-1_106073_2023-05-25_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-06-02 10:04:49	ga_ls9c_ard_3-2-1_098073_2023-06-02_final.stac-item
2023-06-13 11:25:02	ga_ls9c_ard_3-2-1_111073_2023-06-13_final.stac-item
2023-06-18 10:04:40	ga_ls9c_ard_3-2-1_098073_2023-06-18_final.stac-item
2023-06-26 10:54:07	ga_ls9c_ard_3-2-1_106073_2023-06-26_final.stac-item
2023-07-01 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-07-01_final.stac-item
2023-07-04 10:04:51	ga_ls9c_ard_3-2-1_098073_2023-07-04_final.stac-item
2023-07-20 10:04:57	ga_ls9c_ard_3-2-1_098073_2023-07-20_final.stac-item
2023-08-05 10:05:05	ga_ls9c_ard_3-2-1_098073_2023-08-05_final.stac-item
2023-08-21 10:05:10	ga_ls9c_ard_3-2-1_098073_2023-08-21_final.stac-item
2023-09-06 10:05:20	ga_ls9c_ard_3-2-1_098073_2023-09-06_final.stac-item
2023-09-22 10:05:24	ga_ls9c_ard_3-2-1_098073_2023-09-22_final.stac-item
2023-10-08 10:05:28	ga_ls9c_ard_3-2-1_098073_2023-10-08_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-11-09 10:05:31	ga_ls9c_ard_3-2-1_098073_2023-11-09_final.stac-item
2023-11-25 10:05:39	ga_ls9c_ard_3-2-1_098073_2023-11-25_final.stac-item
2023-12-11 10:05:36	ga_ls9c_ard_3-2-1_098073_2023-12-11_final.stac-item
2023-12-27 10:05:41	ga_ls9c_ard_3-2-1_098073_2023-12-27_final.stac-item
2024-01-12 10:05:37	ga_ls9c_ard_3-2-1_098073_2024-01-12_final.stac-item
2024-01-28 10:05:36	ga_ls9c_ard_3-2-1_098073_2024-01-28_final.stac-item
2024-02-13 10:05:37	ga_ls9c_ard_3-2-1_098073_2024-02-13_final.stac-item
2024-02-29 10:05:29	ga_ls9c_ard_3-2-1_098073_2024-02-29_final.stac-item
2024-03-16 10:05:30	ga_ls9c_ard_3-2-1_098073_2024-03-16_final.stac-item
2024-04-01 10:05:21	ga_ls9c_ard_3-2-1_098073_2024-04-01_final.stac-item
2024-04-17 10:05:12	ga_ls9c_ard_3-2-1_098073_2024-04-17_final.stac-item
2024-05-03 10:04:56	ga_ls9c_ard_3-2-1_098073_2024-05-03_final.stac-item
2024-05-19 10:04:49	ga_ls9c_ard_3-2-1_098073_2024-05-19_nrt.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