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
2022-07-22 11:14:02	ga_ls8c_ard_3-2-1_109074_2022-07-22_final
2022-07-24 09:26:24	ga_ls8c_ard_3-2-1_091083_2022-07-23_final
2022-07-25 10:07:17	ga_ls8c_ard_3-2-1_098077_2022-07-25_final
2022-07-26 09:13:16	ga_ls8c_ard_3-2-1_089081_2022-07-25_final
2022-08-04 10:41:41	ga_ls8c_ard_3-2-1_104070_2022-08-04_final
2022-08-04 10:42:52	ga_ls8c_ard_3-2-1_104073_2022-08-04_final
2022-08-05 09:46:52	ga_ls8c_ard_3-2-1_095072_2022-08-05_final
2022-08-05 11:24:09	ga_ls8c_ard_3-2-1_111068_2022-08-05_final
2022-08-05 11:25:21	ga_ls8c_ard_3-2-1_111071_2022-08-05_final
2022-08-05 11:25:45	ga_ls8c_ard_3-2-1_111072_2022-08-05_final
2022-08-05 11:26:57	ga_ls8c_ard_3-2-1_111075_2022-08-05_final
2022-08-05 11:27:45	ga_ls8c_ard_3-2-1_111077_2022-08-05_final
2022-08-05 11:28:08	ga_ls8c_ard_3-2-1_111078_2022-08-05_final
2022-08-05 11:28:56	ga_ls8c_ard_3-2-1_111080_2022-08-05_final
2022-08-06 10:29:20	ga_ls8c_ard_3-2-1_102070_2022-08-06_final
2022-08-06 10:30:32	ga_ls8c_ard_3-2-1_102073_2022-08-06_final
2022-08-06 10:31:20	ga_ls8c_ard_3-2-1_102075_2022-08-06_final
2022-08-06 10:32:08	ga_ls8c_ard_3-2-1_102077_2022-08-06_final
2022-08-06 10:32:32	ga_ls8c_ard_3-2-1_102078_2022-08-06_final
2022-08-06 10:32:56	ga_ls8c_ard_3-2-1_102079_2022-08-06_final
2022-08-07 09:34:07	ga_ls8c_ard_3-2-1_093071_2022-08-07_final
2022-08-07 09:37:19	ga_ls8c_ard_3-2-1_093079_2022-08-07_final
2022-08-07 09:40:06	ga_ls8c_ard_3-2-1_093086_2022-08-07_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-07 11:14:12	ga_ls8c_ard_3-2-1_109074_2022-08-07_final
2022-08-07 11:15:00	ga_ls8c_ard_3-2-1_109076_2022-08-07_final
2022-08-07 11:15:24	ga_ls8c_ard_3-2-1_109077_2022-08-07_final
2022-08-07 11:15:48	ga_ls8c_ard_3-2-1_109078_2022-08-07_final
2022-08-07 11:16:12	ga_ls8c_ard_3-2-1_109079_2022-08-07_final
2022-08-07 11:17:00	ga_ls8c_ard_3-2-1_109081_2022-08-07_final
2022-08-07 11:17:24	ga_ls8c_ard_3-2-1_109082_2022-08-07_final
2022-08-08 10:20:11	ga_ls8c_ard_3-2-1_100078_2022-08-08_final
2022-08-08 10:21:23	ga_ls8c_ard_3-2-1_100081_2022-08-08_final
2022-08-08 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-08-08_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-09 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-08-08_final
2022-08-09 09:26:10	ga_ls8c_ard_3-2-1_091082_2022-08-08_final
2022-08-09 09:26:58	ga_ls8c_ard_3-2-1_091084_2022-08-08_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-09 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-08-09_final
2022-08-09 11:01:27	ga_ls8c_ard_3-2-1_107073_2022-08-09_final
2022-08-09 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-08-09_final
2022-08-09 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-08-09_final
2022-08-09 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-08-09_final
2022-08-09 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-08-09_final
2022-08-09 11:05:27	ga_ls8c_ard_3-2-1_107083_2022-08-09_final
2022-08-09 11:05:51	ga_ls8c_ard_3-2-1_107084_2022-08-09_final
2022-08-10 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-08-10_final
2022-08-10 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-08-10_final
2022-08-10 10:05:26	ga_ls8c_ard_3-2-1_098072_2022-08-10_final
2022-08-10 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-08-10_final
2022-08-10 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-08-10_final
2022-08-10 10:09:50	ga_ls8c_ard_3-2-1_098083_2022-08-10_final
2022-08-10 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-08-10_final
2022-08-10 11:47:07	ga_ls8c_ard_3-2-1_114079_2022-08-10_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-11 10:47:31	ga_ls8c_ard_3-2-1_105069_2022-08-11_final
2022-08-11 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-08-11_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-11 10:51:54	ga_ls8c_ard_3-2-1_105080_2022-08-11_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-12 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-08-12_final
2022-08-12 09:55:29	ga_ls8c_ard_3-2-1_096078_2022-08-12_final
2022-08-12 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-08-12_final
2022-08-12 09:56:17	ga_ls8c_ard_3-2-1_096080_2022-08-12_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-12 09:57:29	ga_ls8c_ard_3-2-1_096083_2022-08-12_final
2022-08-12 09:57:53	ga_ls8c_ard_3-2-1_096084_2022-08-12_final
2022-08-12 09:58:17	ga_ls8c_ard_3-2-1_096085_2022-08-12_final
2022-08-12 11:33:58	ga_ls8c_ard_3-2-1_112077_2022-08-12_final
2022-08-12 11:34:46	ga_ls8c_ard_3-2-1_112079_2022-08-12_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-14 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-08-14_final
2022-08-14 09:43:08	ga_ls8c_ard_3-2-1_094078_2022-08-14_final
2022-08-14 11:18:26	ga_ls8c_ard_3-2-1_110069_2022-08-14_final
2022-08-15 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-08-15_final
2022-08-15 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-08-15_final
2022-08-15 10:26:48	ga_ls8c_ard_3-2-1_101079_2022-08-15_final
2022-08-15 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-08-15_final
2022-08-16 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-08-15_final
2022-08-16 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-15_final
2022-08-16 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-15_final
2022-08-16 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-08-16_final
2022-08-16 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-08-16_final
2022-08-16 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-08-16_final
2022-08-16 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-08-16_final
2022-08-16 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-08-16_final
2022-08-17 10:14:03	ga_ls8c_ard_3-2-1_099078_2022-08-17_final
2022-08-17 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-08-17_final
2022-08-17 10:16:26	ga_ls8c_ard_3-2-1_099084_2022-08-17_final
2022-08-18 09:18:02	ga_ls8c_ard_3-2-1_090077_2022-08-17_final
2022-08-18 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-08-17_final
2022-08-18 09:19:37	ga_ls8c_ard_3-2-1_090081_2022-08-17_final
2022-08-18 09:22:01	ga_ls8c_ard_3-2-1_090087_2022-08-17_final
2022-08-18 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-08-17_final
2022-08-18 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-08-17_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-19 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-08-19_final
2022-08-19 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-08-19_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