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
2022-01-01 10:34:54	ga_ls8c_ard_3-2-1_103069_2022-01-01_final
2022-01-02 11:24:09	ga_ls8c_ard_3-2-1_110084_2022-01-02_final
2022-01-03 10:23:44	ga_ls8c_ard_3-2-1_101072_2022-01-03_final
2022-01-03 10:24:32	ga_ls8c_ard_3-2-1_101074_2022-01-03_final
2022-01-03 10:25:20	ga_ls8c_ard_3-2-1_101076_2022-01-03_final
2022-01-03 10:27:43	ga_ls8c_ard_3-2-1_101082_2022-01-03_final
2022-01-04 09:27:43	ga_ls8c_ard_3-2-1_092071_2022-01-03_final
2022-01-04 09:29:18	ga_ls8c_ard_3-2-1_092075_2022-01-03_final
2022-01-04 11:10:59	ga_ls8c_ard_3-2-1_108082_2022-01-04_final
2022-01-05 10:14:58	ga_ls8c_ard_3-2-1_099081_2022-01-05_final
2022-01-05 10:16:09	ga_ls8c_ard_3-2-1_099084_2022-01-05_final
2022-01-05 11:51:03	ga_ls8c_ard_3-2-1_115074_2022-01-05_final
2022-01-06 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-01-05_final
2022-01-06 09:21:20	ga_ls8c_ard_3-2-1_090086_2022-01-05_final
2022-01-06 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-01-06_final
2022-01-06 10:58:13	ga_ls8c_ard_3-2-1_106081_2022-01-06_final
2022-01-07 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-01-07_final
2022-01-07 09:58:36	ga_ls8c_ard_3-2-1_097071_2022-01-07_final
2022-01-07 09:59:24	ga_ls8c_ard_3-2-1_097073_2022-01-07_final
2022-01-07 10:00:36	ga_ls8c_ard_3-2-1_097076_2022-01-07_final
2022-01-07 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-01-07_final
2022-01-07 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-01-07_final
2022-01-07 11:38:41	ga_ls8c_ard_3-2-1_113074_2022-01-07_final
2022-01-07 11:40:41	ga_ls8c_ard_3-2-1_113079_2022-01-07_final
2022-01-07 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-01-07_final
2022-01-08 10:40:40	ga_ls8c_ard_3-2-1_104068_2022-01-08_final
2022-01-08 10:43:52	ga_ls8c_ard_3-2-1_104076_2022-01-08_final
2022-01-08 10:44:16	ga_ls8c_ard_3-2-1_104077_2022-01-08_final
2022-01-08 10:44:40	ga_ls8c_ard_3-2-1_104078_2022-01-08_final
2022-01-08 10:45:04	ga_ls8c_ard_3-2-1_104079_2022-01-08_final
2022-01-08 10:45:27	ga_ls8c_ard_3-2-1_104080_2022-01-08_final
2022-01-08 10:45:51	ga_ls8c_ard_3-2-1_104081_2022-01-08_final
2022-01-08 10:46:15	ga_ls8c_ard_3-2-1_104082_2022-01-08_final
2022-01-09 09:46:15	ga_ls8c_ard_3-2-1_095071_2022-01-09_final
2022-01-09 09:46:39	ga_ls8c_ard_3-2-1_095072_2022-01-09_final
2022-01-09 09:47:50	ga_ls8c_ard_3-2-1_095075_2022-01-09_final
2022-01-09 09:48:14	ga_ls8c_ard_3-2-1_095076_2022-01-09_final
2022-01-09 09:48:38	ga_ls8c_ard_3-2-1_095077_2022-01-09_final
2022-01-09 09:49:02	ga_ls8c_ard_3-2-1_095078_2022-01-09_final
2022-01-09 09:51:50	ga_ls8c_ard_3-2-1_095085_2022-01-09_final
2022-01-09 11:23:56	ga_ls8c_ard_3-2-1_111068_2022-01-09_final
2022-01-09 11:24:20	ga_ls8c_ard_3-2-1_111069_2022-01-09_final
2022-01-09 11:24:44	ga_ls8c_ard_3-2-1_111070_2022-01-09_final
2022-01-09 11:25:08	ga_ls8c_ard_3-2-1_111071_2022-01-09_final
2022-01-09 11:25:32	ga_ls8c_ard_3-2-1_111072_2022-01-09_final
2022-01-09 11:25:56	ga_ls8c_ard_3-2-1_111073_2022-01-09_final
2022-01-09 11:26:43	ga_ls8c_ard_3-2-1_111075_2022-01-09_final
2022-01-09 11:27:07	ga_ls8c_ard_3-2-1_111076_2022-01-09_final
2022-01-09 11:27:31	ga_ls8c_ard_3-2-1_111077_2022-01-09_final
2022-01-09 11:27:55	ga_ls8c_ard_3-2-1_111078_2022-01-09_final
2022-01-09 11:28:19	ga_ls8c_ard_3-2-1_111079_2022-01-09_final
2022-01-09 11:28:43	ga_ls8c_ard_3-2-1_111080_2022-01-09_final
2022-01-09 11:29:07	ga_ls8c_ard_3-2-1_111081_2022-01-09_final
2022-01-09 11:29:31	ga_ls8c_ard_3-2-1_111082_2022-01-09_final
2022-01-09 11:29:55	ga_ls8c_ard_3-2-1_111083_2022-01-09_final
2022-01-09 11:30:19	ga_ls8c_ard_3-2-1_111084_2022-01-09_final
2022-01-10 10:29:54	ga_ls8c_ard_3-2-1_102072_2022-01-10_final
2022-01-10 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-01-10_final
2022-01-10 10:30:42	ga_ls8c_ard_3-2-1_102074_2022-01-10_final
2022-01-10 10:31:06	ga_ls8c_ard_3-2-1_102075_2022-01-10_final
2022-01-10 10:31:30	ga_ls8c_ard_3-2-1_102076_2022-01-10_final
2022-01-10 10:31:54	ga_ls8c_ard_3-2-1_102077_2022-01-10_final
2022-01-10 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-01-10_final
2022-01-10 10:33:30	ga_ls8c_ard_3-2-1_102081_2022-01-10_final
2022-01-10 10:33:54	ga_ls8c_ard_3-2-1_102082_2022-01-10_final
2022-01-11 09:33:53	ga_ls8c_ard_3-2-1_093071_2022-01-11_final
2022-01-11 09:34:41	ga_ls8c_ard_3-2-1_093073_2022-01-11_final
2022-01-11 09:35:05	ga_ls8c_ard_3-2-1_093074_2022-01-11_final
2022-01-11 09:36:16	ga_ls8c_ard_3-2-1_093077_2022-01-11_final
2022-01-11 09:37:52	ga_ls8c_ard_3-2-1_093081_2022-01-11_final
2022-01-11 09:38:40	ga_ls8c_ard_3-2-1_093083_2022-01-11_final
2022-01-11 09:39:04	ga_ls8c_ard_3-2-1_093084_2022-01-11_final
2022-01-11 09:39:28	ga_ls8c_ard_3-2-1_093085_2022-01-11_final
2022-01-11 09:39:52	ga_ls8c_ard_3-2-1_093086_2022-01-11_final
2022-01-11 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-01-11_final
2022-01-11 09:40:40	ga_ls8c_ard_3-2-1_093088_2022-01-11_final
2022-01-11 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-01-11_final
2022-01-11 11:13:10	ga_ls8c_ard_3-2-1_109072_2022-01-11_final
2022-01-11 11:13:34	ga_ls8c_ard_3-2-1_109073_2022-01-11_final
2022-01-11 11:13:58	ga_ls8c_ard_3-2-1_109074_2022-01-11_final
2022-01-12 10:17:32	ga_ls8c_ard_3-2-1_100072_2022-01-12_final
2022-01-12 10:17:56	ga_ls8c_ard_3-2-1_100073_2022-01-12_final
2022-01-12 10:18:20	ga_ls8c_ard_3-2-1_100074_2022-01-12_final
2022-01-12 10:18:44	ga_ls8c_ard_3-2-1_100075_2022-01-12_final
2022-01-12 10:19:08	ga_ls8c_ard_3-2-1_100076_2022-01-12_final
2022-01-12 10:19:56	ga_ls8c_ard_3-2-1_100078_2022-01-12_final
2022-01-12 10:20:20	ga_ls8c_ard_3-2-1_100079_2022-01-12_final
2022-01-12 10:20:44	ga_ls8c_ard_3-2-1_100080_2022-01-12_final
2022-01-12 11:58:01	ga_ls8c_ard_3-2-1_116076_2022-01-12_final
2022-01-12 11:58:25	ga_ls8c_ard_3-2-1_116077_2022-01-12_final
2022-01-12 11:58:49	ga_ls8c_ard_3-2-1_116078_2022-01-12_final
2022-01-13 09:21:55	ga_ls8c_ard_3-2-1_091072_2022-01-12_final
2022-01-13 09:22:19	ga_ls8c_ard_3-2-1_091073_2022-01-12_final
2022-01-13 09:22:43	ga_ls8c_ard_3-2-1_091074_2022-01-12_final
2022-01-13 09:26:18	ga_ls8c_ard_3-2-1_091083_2022-01-12_final
2022-01-13 09:27:06	ga_ls8c_ard_3-2-1_091085_2022-01-12_final
2022-01-13 09:27:30	ga_ls8c_ard_3-2-1_091086_2022-01-12_final
2022-01-13 09:27:54	ga_ls8c_ard_3-2-1_091087_2022-01-12_final
2022-01-13 09:28:18	ga_ls8c_ard_3-2-1_091088_2022-01-12_final
2022-01-13 09:28:42	ga_ls8c_ard_3-2-1_091089_2022-01-12_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