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
2023-02-04 11:36:14	ga_ls8c_ard_3-2-1_112083_2023-02-04_final
2023-03-12 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-03-12_final
2023-03-13 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-03-13_final
2023-03-16 10:45:58	ga_ls8c_ard_3-2-1_104082_2023-03-16_final
2023-03-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2023-03-17_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-04-04 11:15:50	ga_ls8c_ard_3-2-1_109080_2023-04-04_final
2023-04-05 10:18:36	ga_ls8c_ard_3-2-1_100076_2023-04-05_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-04-11 09:40:35	ga_ls8c_ard_3-2-1_094074_2023-04-11_final
2023-04-13 09:32:13	ga_ls8c_ard_3-2-1_092084_2023-04-13_final
2023-04-16 10:01:06	ga_ls8c_ard_3-2-1_097079_2023-04-16_final
2023-04-24 09:13:14	ga_ls8c_ard_3-2-1_089083_2023-04-23_final
2023-04-24 10:46:32	ga_ls8c_ard_3-2-1_105069_2023-04-24_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-05-02 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-05-02_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-02 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-05-02_final
2023-05-11 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-11_final
2023-05-15 09:29:56	ga_ls8c_ard_3-2-1_092079_2023-05-14_final
2023-05-18 09:57:13	ga_ls8c_ard_3-2-1_097070_2023-05-18_final
2023-05-18 10:03:12	ga_ls8c_ard_3-2-1_097085_2023-05-18_final
2023-05-20 09:50:52	ga_ls8c_ard_3-2-1_095085_2023-05-20_final
2023-05-25 10:03:51	ga_ls8c_ard_3-2-1_098071_2023-05-25_final
2023-05-30 10:23:36	ga_ls8c_ard_3-2-1_101074_2023-05-30_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-04 10:45:21	ga_ls8c_ard_3-2-1_104082_2023-06-04_final
2023-06-05 09:50:33	ga_ls8c_ard_3-2-1_095084_2023-06-05_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-10 10:03:58	ga_ls8c_ard_3-2-1_098071_2023-06-10_final
2023-06-11 09:10:45	ga_ls8c_ard_3-2-1_089077_2023-06-10_final
2023-06-12 09:57:13	ga_ls8c_ard_3-2-1_096085_2023-06-12_final
2023-06-13 10:38:53	ga_ls8c_ard_3-2-1_103081_2023-06-13_final
2023-06-14 09:40:28	ga_ls8c_ard_3-2-1_094074_2023-06-14_final
2023-06-14 11:18:10	ga_ls8c_ard_3-2-1_110071_2023-06-14_final
2023-06-18 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-06-18_final
2023-06-19 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-06-19_final
2023-06-21 09:49:52	ga_ls8c_ard_3-2-1_095082_2023-06-21_final
2023-06-26 10:08:04	ga_ls8c_ard_3-2-1_098081_2023-06-26_final
2023-06-26 11:46:33	ga_ls8c_ard_3-2-1_114080_2023-06-26_final
2023-07-02 09:31:04	ga_ls8c_ard_3-2-1_092081_2023-07-02_final
2023-07-02 11:06:22	ga_ls8c_ard_3-2-1_108072_2023-07-02_final
2023-07-02 11:11:09	ga_ls8c_ard_3-2-1_108084_2023-07-02_final
2023-07-04 10:53:14	ga_ls8c_ard_3-2-1_106070_2023-07-04_final
2023-07-05 09:58:01	ga_ls8c_ard_3-2-1_097071_2023-07-05_final
2023-07-05 11:41:17	ga_ls8c_ard_3-2-1_113082_2023-07-05_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-20 10:57:16	ga_ls8c_ard_3-2-1_106080_2023-07-20_final
2023-07-23 09:51:20	ga_ls8c_ard_3-2-1_095085_2023-07-23_final
2023-07-24 10:33:00	ga_ls8c_ard_3-2-1_102081_2023-07-24_final
2023-07-28 11:44:26	ga_ls8c_ard_3-2-1_114074_2023-07-28_final
2023-07-29 09:14:43	ga_ls8c_ard_3-2-1_089086_2023-07-28_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-05 10:53:03	ga_ls8c_ard_3-2-1_106069_2023-08-05_final
2023-08-12 09:26:44	ga_ls8c_ard_3-2-1_091085_2023-08-11_final
2023-08-12 11:00:02	ga_ls8c_ard_3-2-1_107071_2023-08-12_final
2023-08-15 11:35:46	ga_ls8c_ard_3-2-1_112083_2023-08-15_final
2023-08-17 09:45:45	ga_ls8c_ard_3-2-1_094086_2023-08-17_final
2023-08-17 11:18:39	ga_ls8c_ard_3-2-1_110071_2023-08-17_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-15 09:11:22	ga_ls8c_ard_3-2-1_089077_2023-09-14_final
2023-09-15 09:13:22	ga_ls8c_ard_3-2-1_089082_2023-09-14_final
2023-09-15 09:16:34	ga_ls8c_ard_3-2-1_089090_2023-09-14_final
2023-09-15 10:46:40	ga_ls8c_ard_3-2-1_105068_2023-09-15_final
2023-09-16 09:57:26	ga_ls8c_ard_3-2-1_096084_2023-09-16_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-09-21 10:15:11	ga_ls8c_ard_3-2-1_099082_2023-09-21_final
2023-09-22 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-09-21_final
2023-09-27 11:14:38	ga_ls8c_ard_3-2-1_109076_2023-09-27_final
2023-10-04 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-10-04_final
2023-10-07 10:10:51	ga_ls8c_ard_3-2-1_099071_2023-10-07_final
2023-10-07 11:51:20	ga_ls8c_ard_3-2-1_115075_2023-10-07_final
2023-10-08 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-10-08_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-15 11:02:20	ga_ls8c_ard_3-2-1_107076_2023-10-15_final
2023-10-21 10:27:37	ga_ls8c_ard_3-2-1_101082_2023-10-21_final
2023-10-22 09:29:13	ga_ls8c_ard_3-2-1_092075_2023-10-21_final
2023-10-22 11:07:18	ga_ls8c_ard_3-2-1_108073_2023-10-22_final
2023-10-23 10:09:42	ga_ls8c_ard_3-2-1_099068_2023-10-23_final
2023-10-23 11:52:59	ga_ls8c_ard_3-2-1_115079_2023-10-23_final
2023-10-24 09:20:52	ga_ls8c_ard_3-2-1_090085_2023-10-23_final
2023-10-24 10:54:58	ga_ls8c_ard_3-2-1_106073_2023-10-24_final
2023-10-27 09:47:01	ga_ls8c_ard_3-2-1_095073_2023-10-27_final
2023-10-29 09:38:39	ga_ls8c_ard_3-2-1_093083_2023-10-29_final
2023-10-29 09:40:15	ga_ls8c_ard_3-2-1_093087_2023-10-29_final
2023-10-31 11:00:47	ga_ls8c_ard_3-2-1_107072_2023-10-31_final
2023-11-01 10:05:10	ga_ls8c_ard_3-2-1_098072_2023-11-01_final
2023-11-09 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-11-09_final
2023-11-10 10:03:40	ga_ls8c_ard_3-2-1_097084_2023-11-10_final
2023-11-15 10:22:17	ga_ls8c_ard_3-2-1_100084_2023-11-15_final
2023-11-16 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-11-15_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_final
2023-11-18 10:46:26	ga_ls8c_ard_3-2-1_105067_2023-11-18_final
2023-11-19 09:53:37	ga_ls8c_ard_3-2-1_096074_2023-11-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years