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
2021-11-10 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-12-11 11:09:05	ga_ls9c_ard_3-2-1_108077_2021-12-11_final.stac-item
2021-12-25 09:42:30	ga_ls9c_ard_3-2-1_094077_2021-12-25_final.stac-item
2021-12-25 11:20:36	ga_ls9c_ard_3-2-1_110075_2021-12-25_final.stac-item
2021-12-27 11:09:02	ga_ls9c_ard_3-2-1_108077_2021-12-27_final.stac-item
2022-01-30 09:18:58	ga_ls9c_ard_3-2-1_090080_2022-01-29_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-10 10:35:17	ga_ls9c_ard_3-2-1_103070_2022-02-10_final.stac-item
2022-02-18 09:48:58	ga_ls9c_ard_3-2-1_095078_2022-02-18_final.stac-item
2022-02-24 10:50:18	ga_ls9c_ard_3-2-1_105077_2022-02-24_final.stac-item
2022-03-03 09:19:31	ga_ls9c_ard_3-2-1_090082_2022-03-02_final.stac-item
2022-03-22 09:48:47	ga_ls9c_ard_3-2-1_095078_2022-03-22_final.stac-item
2022-04-23 09:48:33	ga_ls9c_ard_3-2-1_095078_2022-04-23_final.stac-item
2022-04-27 11:02:19	ga_ls9c_ard_3-2-1_107077_2022-04-27_final.stac-item
2022-06-03 11:19:50	ga_ls9c_ard_3-2-1_110075_2022-06-03_final.stac-item
2022-06-12 11:14:30	ga_ls9c_ard_3-2-1_109077_2022-06-12_final.stac-item
2022-06-17 09:54:37	ga_ls9c_ard_3-2-1_096078_2022-06-17_final.stac-item
2022-06-21 11:08:30	ga_ls9c_ard_3-2-1_108077_2022-06-21_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-07-07 11:08:35	ga_ls9c_ard_3-2-1_108077_2022-07-07_final.stac-item
2022-07-17 10:03:11	ga_ls9c_ard_3-2-1_098068_2022-07-17_final.stac-item
2022-07-21 11:19:49	ga_ls9c_ard_3-2-1_110074_2022-07-21_final.stac-item
2022-07-28 11:28:06	ga_ls9c_ard_3-2-1_111079_2022-07-28_final.stac-item
2022-08-06 11:20:02	ga_ls9c_ard_3-2-1_110074_2022-08-06_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-22 11:20:56	ga_ls9c_ard_3-2-1_110076_2022-08-22_final.stac-item
2022-09-17 10:22:24	ga_ls9c_ard_3-2-1_100084_2022-09-17_final.stac-item
2022-09-23 11:21:03	ga_ls9c_ard_3-2-1_110076_2022-09-23_final.stac-item
2022-10-18 11:15:22	ga_ls9c_ard_3-2-1_109077_2022-10-18_final.stac-item
2022-10-23 11:35:31	ga_ls9c_ard_3-2-1_112081_2022-10-23_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-27 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-10-27_final.stac-item
2022-11-01 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-11-01_final.stac-item
2022-11-08 09:55:25	ga_ls9c_ard_3-2-1_096078_2022-11-08_final.stac-item
2022-11-08 09:55:49	ga_ls9c_ard_3-2-1_096079_2022-11-08_final.stac-item
2022-11-08 11:34:42	ga_ls9c_ard_3-2-1_112079_2022-11-08_final.stac-item
2022-11-12 11:09:12	ga_ls9c_ard_3-2-1_108077_2022-11-12_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-17 11:28:33	ga_ls9c_ard_3-2-1_111079_2022-11-17_final.stac-item
2022-11-26 09:46:15	ga_ls9c_ard_3-2-1_094086_2022-11-26_final.stac-item
2022-11-28 09:30:17	ga_ls9c_ard_3-2-1_092077_2022-11-28_final.stac-item
2022-11-29 10:14:44	ga_ls9c_ard_3-2-1_099080_2022-11-29_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-06 10:20:32	ga_ls9c_ard_3-2-1_100079_2022-12-06_final.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-14 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-14_final.stac-item
2022-12-21 11:15:20	ga_ls9c_ard_3-2-1_109077_2022-12-21_final.stac-item
2022-12-25 10:52:12	ga_ls9c_ard_3-2-1_105081_2022-12-25_final.stac-item
2022-12-27 10:37:28	ga_ls9c_ard_3-2-1_103075_2022-12-27_final.stac-item
2022-12-30 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-30_final.stac-item
2023-01-07 10:20:33	ga_ls9c_ard_3-2-1_100079_2023-01-07_final.stac-item
2023-01-11 09:55:24	ga_ls9c_ard_3-2-1_096078_2023-01-11_final.stac-item
2023-01-19 10:45:56	ga_ls9c_ard_3-2-1_104081_2023-01-19_final.stac-item
2023-01-23 10:20:26	ga_ls9c_ard_3-2-1_100079_2023-01-23_final.stac-item
2023-02-04 10:46:31	ga_ls9c_ard_3-2-1_104082_2023-02-04_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-07 11:15:26	ga_ls9c_ard_3-2-1_109077_2023-02-07_final.stac-item
2023-02-27 10:50:28	ga_ls9c_ard_3-2-1_105077_2023-02-27_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-16 09:55:08	ga_ls9c_ard_3-2-1_096078_2023-03-16_final.stac-item
2023-03-25 09:48:51	ga_ls9c_ard_3-2-1_095078_2023-03-25_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-03-27 11:13:44	ga_ls9c_ard_3-2-1_109074_2023-03-27_final.stac-item
2023-03-27 11:14:32	ga_ls9c_ard_3-2-1_109076_2023-03-27_final.stac-item
2023-04-05 11:08:42	ga_ls9c_ard_3-2-1_108077_2023-04-05_final.stac-item
2023-04-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2023-04-23_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_2023-04-28_final.stac-item
2023-05-05 11:21:33	ga_ls9c_ard_3-2-1_110079_2023-05-05_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-05-19 11:31:50	ga_ls9c_ard_3-2-1_112074_2023-05-19_final.stac-item
2023-05-30 11:15:36	ga_ls9c_ard_3-2-1_109080_2023-05-30_final.stac-item
2023-06-18 10:09:03	ga_ls9c_ard_3-2-1_098084_2023-06-18_final.stac-item
2023-06-24 11:07:40	ga_ls9c_ard_3-2-1_108076_2023-06-24_final.stac-item
2023-06-24 11:08:04	ga_ls9c_ard_3-2-1_108077_2023-06-24_final.stac-item
2023-07-01 11:14:47	ga_ls9c_ard_3-2-1_109078_2023-07-01_final.stac-item
2023-07-15 11:26:05	ga_ls9c_ard_3-2-1_111075_2023-07-15_final.stac-item
2023-07-17 09:36:27	ga_ls9c_ard_3-2-1_093079_2023-07-17_final.stac-item
2023-07-26 11:08:20	ga_ls9c_ard_3-2-1_108077_2023-07-26_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-07-29 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-07-29_final.stac-item
2023-07-31 09:48:29	ga_ls9c_ard_3-2-1_095078_2023-07-31_final.stac-item
2023-07-31 11:27:46	ga_ls9c_ard_3-2-1_111079_2023-07-31_final.stac-item
2023-08-09 11:21:16	ga_ls9c_ard_3-2-1_110078_2023-08-09_final.stac-item
2023-08-11 11:08:07	ga_ls9c_ard_3-2-1_108076_2023-08-11_final.stac-item
2023-08-12 11:50:35	ga_ls9c_ard_3-2-1_115074_2023-08-12_final.stac-item
2023-10-14 11:08:58	ga_ls9c_ard_3-2-1_108077_2023-10-14_final.stac-item
2023-10-21 11:15:10	ga_ls9c_ard_3-2-1_109077_2023-10-21_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-03 10:45:44	ga_ls9c_ard_3-2-1_104081_2023-11-03_final.stac-item
2023-11-15 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-11-15_final.stac-item
2023-11-15 11:08:55	ga_ls9c_ard_3-2-1_108077_2023-11-15_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_2023-11-15_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-27 11:32:35	ga_ls9c_ard_3-2-1_112074_2023-11-27_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