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

74 results

Time (local)	Label
2023-03-05 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-03-05_final.stac-item
2023-03-05 10:13:20	ga_ls9c_ard_3-2-1_099077_2023-03-05_final.stac-item
2023-03-05 10:14:32	ga_ls9c_ard_3-2-1_099080_2023-03-05_final.stac-item
2023-03-05 10:15:20	ga_ls9c_ard_3-2-1_099082_2023-03-05_final.stac-item
2023-03-05 10:15:44	ga_ls9c_ard_3-2-1_099083_2023-03-05_final.stac-item
2023-03-05 11:52:37	ga_ls9c_ard_3-2-1_115078_2023-03-05_final.stac-item
2023-03-05 11:53:01	ga_ls9c_ard_3-2-1_115079_2023-03-05_final.stac-item
2023-03-06 09:17:18	ga_ls9c_ard_3-2-1_090076_2023-03-05_final.stac-item
2023-03-06 09:18:30	ga_ls9c_ard_3-2-1_090079_2023-03-05_final.stac-item
2023-03-06 09:19:18	ga_ls9c_ard_3-2-1_090081_2023-03-05_final.stac-item
2023-03-06 09:19:42	ga_ls9c_ard_3-2-1_090082_2023-03-05_final.stac-item
2023-03-06 09:20:06	ga_ls9c_ard_3-2-1_090083_2023-03-05_final.stac-item
2023-03-06 09:20:30	ga_ls9c_ard_3-2-1_090084_2023-03-05_final.stac-item
2023-03-06 09:21:18	ga_ls9c_ard_3-2-1_090086_2023-03-05_final.stac-item
2023-03-06 09:21:42	ga_ls9c_ard_3-2-1_090087_2023-03-05_final.stac-item
2023-03-06 09:22:06	ga_ls9c_ard_3-2-1_090088_2023-03-05_final.stac-item
2023-03-06 09:22:54	ga_ls9c_ard_3-2-1_090090_2023-03-05_final.stac-item
2023-03-06 10:53:48	ga_ls9c_ard_3-2-1_106070_2023-03-06_final.stac-item
2023-03-06 10:54:12	ga_ls9c_ard_3-2-1_106071_2023-03-06_final.stac-item
2023-03-06 10:54:59	ga_ls9c_ard_3-2-1_106073_2023-03-06_final.stac-item
2023-03-06 10:55:23	ga_ls9c_ard_3-2-1_106074_2023-03-06_final.stac-item
2023-03-06 10:57:47	ga_ls9c_ard_3-2-1_106080_2023-03-06_final.stac-item
2023-03-06 10:58:11	ga_ls9c_ard_3-2-1_106081_2023-03-06_final.stac-item
2023-03-07 09:57:45	ga_ls9c_ard_3-2-1_097069_2023-03-07_final.stac-item
2023-03-07 09:58:33	ga_ls9c_ard_3-2-1_097071_2023-03-07_final.stac-item
2023-03-07 10:00:33	ga_ls9c_ard_3-2-1_097076_2023-03-07_final.stac-item
2023-03-07 10:01:21	ga_ls9c_ard_3-2-1_097078_2023-03-07_final.stac-item
2023-03-07 10:02:33	ga_ls9c_ard_3-2-1_097081_2023-03-07_final.stac-item
2023-03-07 10:02:56	ga_ls9c_ard_3-2-1_097082_2023-03-07_final.stac-item
2023-03-07 10:03:20	ga_ls9c_ard_3-2-1_097083_2023-03-07_final.stac-item
2023-03-07 10:03:44	ga_ls9c_ard_3-2-1_097084_2023-03-07_final.stac-item
2023-03-07 11:37:50	ga_ls9c_ard_3-2-1_113072_2023-03-07_final.stac-item
2023-03-07 11:38:14	ga_ls9c_ard_3-2-1_113073_2023-03-07_final.stac-item
2023-03-07 11:38:38	ga_ls9c_ard_3-2-1_113074_2023-03-07_final.stac-item
2023-03-07 11:39:02	ga_ls9c_ard_3-2-1_113075_2023-03-07_final.stac-item
2023-03-07 11:39:26	ga_ls9c_ard_3-2-1_113076_2023-03-07_final.stac-item
2023-03-07 11:41:26	ga_ls9c_ard_3-2-1_113081_2023-03-07_final.stac-item
2023-03-08 09:06:30	ga_ls9c_ard_3-2-1_088080_2023-03-07_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-03-08 10:41:48	ga_ls9c_ard_3-2-1_104071_2023-03-08_final.stac-item
2023-03-08 10:42:11	ga_ls9c_ard_3-2-1_104072_2023-03-08_final.stac-item
2023-03-08 10:42:35	ga_ls9c_ard_3-2-1_104073_2023-03-08_final.stac-item
2023-03-08 10:44:11	ga_ls9c_ard_3-2-1_104077_2023-03-08_final.stac-item
2023-03-08 10:46:11	ga_ls9c_ard_3-2-1_104082_2023-03-08_final.stac-item
2023-03-09 09:48:08	ga_ls9c_ard_3-2-1_095076_2023-03-09_final.stac-item
2023-03-09 09:48:56	ga_ls9c_ard_3-2-1_095078_2023-03-09_final.stac-item
2023-03-09 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-03-09_final.stac-item
2023-03-09 09:49:44	ga_ls9c_ard_3-2-1_095080_2023-03-09_final.stac-item
2023-03-09 09:50:08	ga_ls9c_ard_3-2-1_095081_2023-03-09_final.stac-item
2023-03-09 09:51:20	ga_ls9c_ard_3-2-1_095084_2023-03-09_final.stac-item
2023-03-09 09:52:08	ga_ls9c_ard_3-2-1_095086_2023-03-09_final.stac-item
2023-03-09 09:52:32	ga_ls9c_ard_3-2-1_095087_2023-03-09_final.stac-item
2023-03-09 11:24:14	ga_ls9c_ard_3-2-1_111069_2023-03-09_final.stac-item
2023-03-09 11:24:38	ga_ls9c_ard_3-2-1_111070_2023-03-09_final.stac-item
2023-03-09 11:26:37	ga_ls9c_ard_3-2-1_111075_2023-03-09_final.stac-item
2023-03-09 11:27:49	ga_ls9c_ard_3-2-1_111078_2023-03-09_final.stac-item
2023-03-09 11:29:01	ga_ls9c_ard_3-2-1_111081_2023-03-09_final.stac-item
2023-03-10 10:28:36	ga_ls9c_ard_3-2-1_102069_2023-03-10_final.stac-item
2023-03-10 10:30:36	ga_ls9c_ard_3-2-1_102074_2023-03-10_final.stac-item
2023-03-10 10:33:23	ga_ls9c_ard_3-2-1_102081_2023-03-10_final.stac-item
2023-03-11 09:34:59	ga_ls9c_ard_3-2-1_093074_2023-03-11_final.stac-item
2023-03-11 09:36:34	ga_ls9c_ard_3-2-1_093078_2023-03-11_final.stac-item
2023-03-11 09:36:58	ga_ls9c_ard_3-2-1_093079_2023-03-11_final.stac-item
2023-03-11 09:37:46	ga_ls9c_ard_3-2-1_093081_2023-03-11_final.stac-item
2023-03-11 09:39:22	ga_ls9c_ard_3-2-1_093085_2023-03-11_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-03-11 09:40:10	ga_ls9c_ard_3-2-1_093087_2023-03-11_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-11 11:12:40	ga_ls9c_ard_3-2-1_109071_2023-03-11_final.stac-item
2023-03-11 11:13:52	ga_ls9c_ard_3-2-1_109074_2023-03-11_final.stac-item
2023-03-11 11:14:16	ga_ls9c_ard_3-2-1_109075_2023-03-11_final.stac-item
2023-03-11 11:15:51	ga_ls9c_ard_3-2-1_109079_2023-03-11_final.stac-item
2023-03-11 11:17:03	ga_ls9c_ard_3-2-1_109082_2023-03-11_final.stac-item
2023-03-11 11:17:27	ga_ls9c_ard_3-2-1_109083_2023-03-11_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