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
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-16 11:33:36	ga_ls8c_ard_3-2-1_112076_2022-11-16_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-24 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-11-24_final
2022-11-25 09:49:21	ga_ls8c_ard_3-2-1_095078_2022-11-25_final
2022-11-25 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-11-25_final
2022-11-27 09:35:24	ga_ls8c_ard_3-2-1_093074_2022-11-27_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-04 11:19:16	ga_ls8c_ard_3-2-1_110071_2022-12-04_final
2022-12-06 09:28:49	ga_ls8c_ard_3-2-1_092073_2022-12-05_final
2022-12-06 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-12-06_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-09 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-12-09_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-10 10:40:58	ga_ls8c_ard_3-2-1_104068_2022-12-10_final
2022-12-11 09:49:19	ga_ls8c_ard_3-2-1_095078_2022-12-11_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_2022-12-14_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 10:04:13	ga_ls8c_ard_3-2-1_098069_2022-12-16_final
2022-12-18 09:54:38	ga_ls8c_ard_3-2-1_096076_2022-12-18_final
2022-12-18 11:34:42	ga_ls8c_ard_3-2-1_112079_2022-12-18_final
2022-12-18 11:35:06	ga_ls8c_ard_3-2-1_112080_2022-12-18_final
2022-12-19 10:37:04	ga_ls8c_ard_3-2-1_103074_2022-12-19_final
2022-12-19 10:37:28	ga_ls8c_ard_3-2-1_103075_2022-12-19_final
2022-12-20 09:43:02	ga_ls8c_ard_3-2-1_094078_2022-12-20_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-21 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-12-21_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-25 11:41:14	ga_ls8c_ard_3-2-1_113080_2022-12-25_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2022-12-29 11:13:44	ga_ls8c_ard_3-2-1_109073_2022-12-29_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-07 11:09:09	ga_ls8c_ard_3-2-1_108077_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-14 09:37:34	ga_ls8c_ard_3-2-1_093080_2023-01-14_final
2023-01-14 11:12:52	ga_ls8c_ard_3-2-1_109071_2023-01-14_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-14 11:16:03	ga_ls8c_ard_3-2-1_109079_2023-01-14_final
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-20 10:37:21	ga_ls8c_ard_3-2-1_103075_2023-01-20_final
2023-01-22 10:26:37	ga_ls8c_ard_3-2-1_101079_2023-01-22_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-24 10:12:41	ga_ls8c_ard_3-2-1_099075_2023-01-24_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-01-25 10:57:32	ga_ls8c_ard_3-2-1_106079_2023-01-25_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-30 09:37:13	ga_ls8c_ard_3-2-1_093079_2023-01-30_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-01-30 11:17:18	ga_ls8c_ard_3-2-1_109082_2023-01-30_final
2023-02-05 10:40:13	ga_ls8c_ard_3-2-1_103082_2023-02-05_final
2023-02-06 09:44:59	ga_ls8c_ard_3-2-1_094083_2023-02-06_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-07 10:25:27	ga_ls8c_ard_3-2-1_101076_2023-02-07_final
2023-02-07 10:26:38	ga_ls8c_ard_3-2-1_101079_2023-02-07_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-09 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-02-09_final
2023-02-10 10:55:07	ga_ls8c_ard_3-2-1_106073_2023-02-10_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-20 09:55:09	ga_ls8c_ard_3-2-1_096078_2023-02-20_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-22 11:18:26	ga_ls8c_ard_3-2-1_110070_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-27 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-02-27_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-05 10:59:48	ga_ls8c_ard_3-2-1_107070_2023-03-05_final
2023-03-08 09:55:45	ga_ls8c_ard_3-2-1_096080_2023-03-08_final
2023-03-10 11:21:53	ga_ls8c_ard_3-2-1_110079_2023-03-10_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years