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
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-02 11:47:00	ga_ls8c_ard_3-2-1_114079_2023-02-02_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-05 09:26:30	ga_ls8c_ard_3-2-1_091084_2023-03-04_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_final
2023-03-22 10:06:00	ga_ls8c_ard_3-2-1_098075_2023-03-22_final
2023-03-23 09:13:57	ga_ls8c_ard_3-2-1_089084_2023-03-22_final
2023-03-24 09:52:49	ga_ls8c_ard_3-2-1_096073_2023-03-24_final
2023-03-26 09:44:03	ga_ls8c_ard_3-2-1_094082_2023-03-26_final
2023-03-27 10:24:30	ga_ls8c_ard_3-2-1_101075_2023-03-27_final
2023-03-28 09:30:28	ga_ls8c_ard_3-2-1_092079_2023-03-28_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-11 09:40:11	ga_ls8c_ard_3-2-1_094073_2023-04-11_final
2023-04-11 09:44:34	ga_ls8c_ard_3-2-1_094084_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-13 09:33:01	ga_ls8c_ard_3-2-1_092086_2023-04-13_final
2023-04-13 11:06:18	ga_ls8c_ard_3-2-1_108072_2023-04-13_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-04-21 10:18:25	ga_ls8c_ard_3-2-1_100076_2023-04-21_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-05-05 10:33:05	ga_ls8c_ard_3-2-1_102082_2023-05-05_final
2023-05-08 09:25:27	ga_ls8c_ard_3-2-1_091083_2023-05-07_final
2023-05-08 10:59:33	ga_ls8c_ard_3-2-1_107071_2023-05-08_final
2023-05-09 10:04:18	ga_ls8c_ard_3-2-1_098072_2023-05-09_final
2023-05-10 09:12:39	ga_ls8c_ard_3-2-1_089082_2023-05-09_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_final
2023-05-17 09:17:33	ga_ls8c_ard_3-2-1_090079_2023-05-16_final
2023-06-07 11:11:07	ga_ls8c_ard_3-2-1_109069_2023-06-07_final
2023-06-07 11:11:55	ga_ls8c_ard_3-2-1_109071_2023-06-07_final
2023-06-11 10:46:26	ga_ls8c_ard_3-2-1_105069_2023-06-11_final
2023-06-15 10:22:09	ga_ls8c_ard_3-2-1_101070_2023-06-15_final
2023-06-18 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-06-17_final
2023-06-18 10:53:27	ga_ls8c_ard_3-2-1_106071_2023-06-18_final
2023-06-27 10:47:21	ga_ls8c_ard_3-2-1_105071_2023-06-27_final
2023-07-05 11:40:30	ga_ls8c_ard_3-2-1_113080_2023-07-05_final
2023-07-09 11:12:37	ga_ls8c_ard_3-2-1_109072_2023-07-09_final
2023-07-10 10:19:47	ga_ls8c_ard_3-2-1_100079_2023-07-10_final
2023-07-11 09:24:10	ga_ls8c_ard_3-2-1_091079_2023-07-10_final
2023-07-21 10:03:15	ga_ls8c_ard_3-2-1_097084_2023-07-21_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-29 10:51:37	ga_ls8c_ard_3-2-1_105081_2023-07-29_final
2023-08-03 09:29:19	ga_ls8c_ard_3-2-1_092076_2023-08-02_final
2023-08-04 10:11:23	ga_ls8c_ard_3-2-1_099073_2023-08-04_final
2023-08-04 10:12:35	ga_ls8c_ard_3-2-1_099076_2023-08-04_final
2023-08-05 09:19:21	ga_ls8c_ard_3-2-1_090082_2023-08-04_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-11 10:17:57	ga_ls8c_ard_3-2-1_100074_2023-08-11_final
2023-08-11 10:21:09	ga_ls8c_ard_3-2-1_100082_2023-08-11_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-21 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-08-21_final
2023-08-22 10:01:32	ga_ls8c_ard_3-2-1_097079_2023-08-22_final
2023-08-25 10:33:39	ga_ls8c_ard_3-2-1_102082_2023-08-25_final
2023-08-28 11:01:22	ga_ls8c_ard_3-2-1_107074_2023-08-28_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-13 09:26:07	ga_ls8c_ard_3-2-1_091083_2023-09-12_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-24 10:44:30	ga_ls8c_ard_3-2-1_104078_2023-09-24_final
2023-09-29 09:27:00	ga_ls8c_ard_3-2-1_091085_2023-09-28_final
2023-09-29 09:28:11	ga_ls8c_ard_3-2-1_091088_2023-09-28_final
2023-10-06 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-10-06_final
2023-10-09 11:41:23	ga_ls8c_ard_3-2-1_113081_2023-10-09_final
2023-10-09 11:41:47	ga_ls8c_ard_3-2-1_113082_2023-10-09_final
2023-10-10 10:40:59	ga_ls8c_ard_3-2-1_104069_2023-10-10_final
2023-10-13 11:15:05	ga_ls8c_ard_3-2-1_109077_2023-10-13_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-16 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-10-16_final
2023-10-22 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-10-22_final
2023-10-25 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-10-25_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-29 09:39:03	ga_ls8c_ard_3-2-1_093084_2023-10-29_final
2023-10-29 09:39:27	ga_ls8c_ard_3-2-1_093085_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-30 10:17:55	ga_ls8c_ard_3-2-1_100073_2023-10-30_final
2023-11-01 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-01_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-03 09:52:48	ga_ls8c_ard_3-2-1_096072_2023-11-03_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-07 11:10:54	ga_ls8c_ard_3-2-1_108082_2023-11-07_final
2023-11-10 09:58:53	ga_ls8c_ard_3-2-1_097072_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-12 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-11-12_final
2023-11-14 09:37:49	ga_ls8c_ard_3-2-1_093081_2023-11-14_final
2023-11-17 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-17_final
2023-11-21 09:45:39	ga_ls8c_ard_3-2-1_094085_2023-11-21_final
2023-11-21 11:18:57	ga_ls8c_ard_3-2-1_110071_2023-11-21_final
2023-11-25 10:58:38	ga_ls8c_ard_3-2-1_106082_2023-11-25_final
2023-11-28 09:47:50	ga_ls8c_ard_3-2-1_095075_2023-11-28_nrt
2023-11-29 10:29:06	ga_ls8c_ard_3-2-1_102070_2023-11-29_nrt
2023-12-03 10:08:18	ga_ls8c_ard_3-2-1_098080_2023-12-03_nrt
2023-12-04 10:47:57	ga_ls8c_ard_3-2-1_105071_2023-12-04_nrt
2023-12-06 10:35:33	ga_ls8c_ard_3-2-1_103071_2023-12-06_nrt

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