Search ga_ls8c_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
2022-02-02 10:35:35	ga_ls8c_ard_3-2-1_103071_2022-02-02_final
2022-02-02 10:36:47	ga_ls8c_ard_3-2-1_103074_2022-02-02_final
2022-02-02 10:37:11	ga_ls8c_ard_3-2-1_103075_2022-02-02_final
2022-02-02 10:37:59	ga_ls8c_ard_3-2-1_103077_2022-02-02_final
2022-02-02 10:39:34	ga_ls8c_ard_3-2-1_103081_2022-02-02_final
2022-02-03 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-02-03_final
2022-02-03 09:41:33	ga_ls8c_ard_3-2-1_094075_2022-02-03_final
2022-02-03 09:42:45	ga_ls8c_ard_3-2-1_094078_2022-02-03_final
2022-02-03 09:43:09	ga_ls8c_ard_3-2-1_094079_2022-02-03_final
2022-02-03 09:44:21	ga_ls8c_ard_3-2-1_094082_2022-02-03_final
2022-02-03 09:44:45	ga_ls8c_ard_3-2-1_094083_2022-02-03_final
2022-02-03 09:45:09	ga_ls8c_ard_3-2-1_094084_2022-02-03_final
2022-02-03 09:45:33	ga_ls8c_ard_3-2-1_094085_2022-02-03_final
2022-02-03 09:45:57	ga_ls8c_ard_3-2-1_094086_2022-02-03_final
2022-02-03 11:18:51	ga_ls8c_ard_3-2-1_110071_2022-02-03_final
2022-02-03 11:19:15	ga_ls8c_ard_3-2-1_110072_2022-02-03_final
2022-02-03 11:19:38	ga_ls8c_ard_3-2-1_110073_2022-02-03_final
2022-02-03 11:22:02	ga_ls8c_ard_3-2-1_110079_2022-02-03_final
2022-02-03 11:22:26	ga_ls8c_ard_3-2-1_110080_2022-02-03_final
2022-02-03 11:22:50	ga_ls8c_ard_3-2-1_110081_2022-02-03_final
2022-02-03 11:23:14	ga_ls8c_ard_3-2-1_110082_2022-02-03_final
2022-02-03 11:24:02	ga_ls8c_ard_3-2-1_110084_2022-02-03_final
2022-02-04 10:24:25	ga_ls8c_ard_3-2-1_101074_2022-02-04_final
2022-02-04 10:25:37	ga_ls8c_ard_3-2-1_101077_2022-02-04_final
2022-02-04 10:28:00	ga_ls8c_ard_3-2-1_101083_2022-02-04_final
2022-02-05 09:27:36	ga_ls8c_ard_3-2-1_092071_2022-02-04_final
2022-02-05 09:29:35	ga_ls8c_ard_3-2-1_092076_2022-02-04_final
2022-02-05 09:30:23	ga_ls8c_ard_3-2-1_092078_2022-02-05_final
2022-02-05 09:30:47	ga_ls8c_ard_3-2-1_092079_2022-02-05_final
2022-02-05 09:31:35	ga_ls8c_ard_3-2-1_092081_2022-02-05_final
2022-02-05 09:31:59	ga_ls8c_ard_3-2-1_092082_2022-02-05_final
2022-02-05 09:32:23	ga_ls8c_ard_3-2-1_092083_2022-02-05_final
2022-02-05 09:32:47	ga_ls8c_ard_3-2-1_092084_2022-02-05_final
2022-02-05 09:33:11	ga_ls8c_ard_3-2-1_092085_2022-02-05_final
2022-02-05 09:33:35	ga_ls8c_ard_3-2-1_092086_2022-02-05_final
2022-02-05 09:33:59	ga_ls8c_ard_3-2-1_092087_2022-02-05_final
2022-02-05 09:34:23	ga_ls8c_ard_3-2-1_092088_2022-02-05_final
2022-02-05 09:34:47	ga_ls8c_ard_3-2-1_092089_2022-02-05_final
2022-02-05 11:06:29	ga_ls8c_ard_3-2-1_108071_2022-02-05_final
2022-02-05 11:08:28	ga_ls8c_ard_3-2-1_108076_2022-02-05_final
2022-02-05 11:08:52	ga_ls8c_ard_3-2-1_108077_2022-02-05_final
2022-02-05 11:09:16	ga_ls8c_ard_3-2-1_108078_2022-02-05_final
2022-02-05 11:09:40	ga_ls8c_ard_3-2-1_108079_2022-02-05_final
2022-02-05 11:10:04	ga_ls8c_ard_3-2-1_108080_2022-02-05_final
2022-02-05 11:10:28	ga_ls8c_ard_3-2-1_108081_2022-02-05_final
2022-02-05 11:10:52	ga_ls8c_ard_3-2-1_108082_2022-02-05_final
2022-02-05 11:11:16	ga_ls8c_ard_3-2-1_108083_2022-02-05_final
2022-02-06 10:10:03	ga_ls8c_ard_3-2-1_099069_2022-02-06_final
2022-02-06 10:10:27	ga_ls8c_ard_3-2-1_099070_2022-02-06_final
2022-02-06 10:10:51	ga_ls8c_ard_3-2-1_099071_2022-02-06_final
2022-02-06 10:12:03	ga_ls8c_ard_3-2-1_099074_2022-02-06_final
2022-02-06 10:13:39	ga_ls8c_ard_3-2-1_099078_2022-02-06_final
2022-02-06 10:14:03	ga_ls8c_ard_3-2-1_099079_2022-02-06_final
2022-02-06 10:14:27	ga_ls8c_ard_3-2-1_099080_2022-02-06_final
2022-02-06 10:14:51	ga_ls8c_ard_3-2-1_099081_2022-02-06_final
2022-02-06 10:15:14	ga_ls8c_ard_3-2-1_099082_2022-02-06_final
2022-02-06 10:15:38	ga_ls8c_ard_3-2-1_099083_2022-02-06_final
2022-02-06 10:16:02	ga_ls8c_ard_3-2-1_099084_2022-02-06_final
2022-02-06 10:16:26	ga_ls8c_ard_3-2-1_099085_2022-02-06_final
2022-02-06 11:51:44	ga_ls8c_ard_3-2-1_115076_2022-02-06_final
2022-02-06 11:52:08	ga_ls8c_ard_3-2-1_115077_2022-02-06_final
2022-02-06 11:52:32	ga_ls8c_ard_3-2-1_115078_2022-02-06_final
2022-02-06 11:52:56	ga_ls8c_ard_3-2-1_115079_2022-02-06_final
2022-02-07 09:16:25	ga_ls8c_ard_3-2-1_090074_2022-02-06_final
2022-02-07 09:18:01	ga_ls8c_ard_3-2-1_090078_2022-02-06_final
2022-02-07 09:18:25	ga_ls8c_ard_3-2-1_090079_2022-02-06_final
2022-02-07 09:18:49	ga_ls8c_ard_3-2-1_090080_2022-02-06_final
2022-02-07 09:19:13	ga_ls8c_ard_3-2-1_090081_2022-02-06_final
2022-02-07 09:19:37	ga_ls8c_ard_3-2-1_090082_2022-02-06_final
2022-02-07 09:20:25	ga_ls8c_ard_3-2-1_090084_2022-02-06_final
2022-02-07 09:20:49	ga_ls8c_ard_3-2-1_090085_2022-02-06_final
2022-02-07 09:21:13	ga_ls8c_ard_3-2-1_090086_2022-02-06_final
2022-02-07 09:21:37	ga_ls8c_ard_3-2-1_090087_2022-02-06_final
2022-02-07 09:22:01	ga_ls8c_ard_3-2-1_090088_2022-02-06_final
2022-02-07 10:54:07	ga_ls8c_ard_3-2-1_106071_2022-02-07_final
2022-02-07 10:54:54	ga_ls8c_ard_3-2-1_106073_2022-02-07_final
2022-02-07 10:55:18	ga_ls8c_ard_3-2-1_106074_2022-02-07_final
2022-02-07 10:55:42	ga_ls8c_ard_3-2-1_106075_2022-02-07_final
2022-02-07 10:56:06	ga_ls8c_ard_3-2-1_106076_2022-02-07_final
2022-02-07 10:57:42	ga_ls8c_ard_3-2-1_106080_2022-02-07_final
2022-02-07 10:58:06	ga_ls8c_ard_3-2-1_106081_2022-02-07_final
2022-02-07 10:58:30	ga_ls8c_ard_3-2-1_106082_2022-02-07_final
2022-02-07 10:58:54	ga_ls8c_ard_3-2-1_106083_2022-02-07_final
2022-02-08 09:57:41	ga_ls8c_ard_3-2-1_097069_2022-02-08_final
2022-02-08 09:58:29	ga_ls8c_ard_3-2-1_097071_2022-02-08_final
2022-02-08 09:58:53	ga_ls8c_ard_3-2-1_097072_2022-02-08_final
2022-02-08 10:00:53	ga_ls8c_ard_3-2-1_097077_2022-02-08_final
2022-02-08 10:01:17	ga_ls8c_ard_3-2-1_097078_2022-02-08_final
2022-02-08 10:01:41	ga_ls8c_ard_3-2-1_097079_2022-02-08_final
2022-02-08 10:02:04	ga_ls8c_ard_3-2-1_097080_2022-02-08_final
2022-02-08 10:02:28	ga_ls8c_ard_3-2-1_097081_2022-02-08_final
2022-02-08 10:02:52	ga_ls8c_ard_3-2-1_097082_2022-02-08_final
2022-02-08 10:03:16	ga_ls8c_ard_3-2-1_097083_2022-02-08_final
2022-02-08 10:03:40	ga_ls8c_ard_3-2-1_097084_2022-02-08_final
2022-02-08 11:37:46	ga_ls8c_ard_3-2-1_113072_2022-02-08_final
2022-02-08 11:38:58	ga_ls8c_ard_3-2-1_113075_2022-02-08_final
2022-02-08 11:39:22	ga_ls8c_ard_3-2-1_113076_2022-02-08_final
2022-02-08 11:39:46	ga_ls8c_ard_3-2-1_113077_2022-02-08_final
2022-02-08 11:40:10	ga_ls8c_ard_3-2-1_113078_2022-02-08_final
2022-02-08 11:40:34	ga_ls8c_ard_3-2-1_113079_2022-02-08_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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