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
2021-10-31 10:24:19	ga_ls8c_ard_3-2-0_101073_2021-10-31_final
2021-11-02 11:51:14	ga_ls8c_ard_3-2-0_115074_2021-11-02_final
2021-11-03 10:56:48	ga_ls8c_ard_3-2-0_106077_2021-11-03_final
2021-11-09 10:20:53	ga_ls8c_ard_3-2-0_100080_2021-11-09_final
2021-11-12 09:12:53	ga_ls8c_ard_3-2-0_089080_2021-11-11_final
2021-11-13 11:35:25	ga_ls8c_ard_3-2-0_112081_2021-11-13_final
2021-11-15 09:46:34	ga_ls8c_ard_3-2-0_094087_2021-11-15_final
2021-11-26 11:03:43	ga_ls8c_ard_3-2-0_107079_2021-11-26_final
2021-11-28 10:48:34	ga_ls8c_ard_3-2-0_105072_2021-11-28_final
2021-11-30 10:39:24	ga_ls8c_ard_3-2-0_103080_2021-11-30_final
2021-12-02 10:26:38	ga_ls8c_ard_3-2-0_101079_2021-12-02_final
2021-12-03 11:10:18	ga_ls8c_ard_3-2-0_108080_2021-12-03_final
2021-12-04 10:12:41	ga_ls8c_ard_3-2-0_099075_2021-12-04_final
2021-12-05 09:19:03	ga_ls8c_ard_3-2-0_090080_2021-12-04_final
2021-12-11 10:18:51	ga_ls8c_ard_3-2-1_100075_2021-12-11_final
2021-12-13 10:06:53	ga_ls8c_ard_3-2-1_098076_2021-12-13_final
2021-12-16 10:36:35	ga_ls8c_ard_3-2-1_103073_2021-12-16_final
2021-12-17 11:23:26	ga_ls8c_ard_3-2-1_110082_2021-12-17_final
2021-12-20 10:11:51	ga_ls8c_ard_3-2-1_099073_2021-12-20_final
2021-12-21 10:58:18	ga_ls8c_ard_3-2-1_106081_2021-12-21_final
2021-12-24 09:50:18	ga_ls8c_ard_3-2-1_095081_2021-12-24_final
2021-12-24 11:29:35	ga_ls8c_ard_3-2-1_111082_2021-12-24_final
2021-12-26 09:36:19	ga_ls8c_ard_3-2-1_093077_2021-12-26_final
2021-12-28 09:28:44	ga_ls8c_ard_3-2-1_091089_2021-12-27_final
2021-12-28 11:03:38	ga_ls8c_ard_3-2-1_107079_2021-12-28_final
2021-12-29 11:46:53	ga_ls8c_ard_3-2-1_114079_2021-12-29_final
2021-12-30 10:50:51	ga_ls8c_ard_3-2-1_105078_2021-12-30_final
2022-01-02 09:44:28	ga_ls8c_ard_3-2-1_094082_2022-01-02_final
2022-01-02 11:22:33	ga_ls8c_ard_3-2-1_110080_2022-01-02_final
2022-01-10 10:32:18	ga_ls8c_ard_3-2-1_102078_2022-01-10_final
2022-01-11 09:37:52	ga_ls8c_ard_3-2-1_093081_2022-01-11_final
2022-01-11 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-01-11_final
2022-01-12 11:58:01	ga_ls8c_ard_3-2-1_116076_2022-01-12_final
2022-01-18 11:22:54	ga_ls8c_ard_3-2-1_110081_2022-01-18_final
2022-01-22 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-01-22_final
2022-01-25 11:29:26	ga_ls8c_ard_3-2-1_111082_2022-01-25_final
2022-02-01 09:54:43	ga_ls8c_ard_3-2-1_096077_2022-02-01_final
2022-02-02 10:37:11	ga_ls8c_ard_3-2-1_103075_2022-02-02_final
2022-02-02 10:39:58	ga_ls8c_ard_3-2-1_103082_2022-02-02_final
2022-02-03 09:43:33	ga_ls8c_ard_3-2-1_094080_2022-02-03_final
2022-02-04 10:24:49	ga_ls8c_ard_3-2-1_101075_2022-02-04_final
2022-02-04 10:25:13	ga_ls8c_ard_3-2-1_101076_2022-02-04_final
2022-02-06 10:12:51	ga_ls8c_ard_3-2-1_099076_2022-02-06_final
2022-02-06 10:14:51	ga_ls8c_ard_3-2-1_099081_2022-02-06_final
2022-02-08 10:03:16	ga_ls8c_ard_3-2-1_097083_2022-02-08_final
2022-02-09 10:41:44	ga_ls8c_ard_3-2-1_104071_2022-02-09_final
2022-02-10 09:50:06	ga_ls8c_ard_3-2-1_095081_2022-02-10_final
2022-02-13 10:18:35	ga_ls8c_ard_3-2-1_100075_2022-02-13_final
2022-02-14 09:25:45	ga_ls8c_ard_3-2-1_091082_2022-02-13_final
2022-02-15 10:06:13	ga_ls8c_ard_3-2-1_098075_2022-02-15_final
2022-02-15 10:09:24	ga_ls8c_ard_3-2-1_098083_2022-02-15_final
2022-02-16 09:12:35	ga_ls8c_ard_3-2-1_089080_2022-02-15_final
2022-02-17 11:35:07	ga_ls8c_ard_3-2-1_112081_2022-02-17_final
2022-02-19 11:22:44	ga_ls8c_ard_3-2-1_110081_2022-02-19_final
2022-02-27 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-02-27_final
2022-02-27 10:31:41	ga_ls8c_ard_3-2-1_102077_2022-02-27_final
2022-02-28 09:38:51	ga_ls8c_ard_3-2-1_093084_2022-02-28_final
2022-03-09 09:30:38	ga_ls8c_ard_3-2-1_092079_2022-03-09_final
2022-03-10 10:15:29	ga_ls8c_ard_3-2-1_099083_2022-03-10_final
2022-03-15 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-03-15_final
2022-03-25 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-03-25_final
2022-03-27 10:56:57	ga_ls8c_ard_3-2-1_106079_2022-03-27_final
2022-03-30 11:26:37	ga_ls8c_ard_3-2-1_111076_2022-03-30_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-04 11:45:34	ga_ls8c_ard_3-2-1_114077_2022-04-04_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-12 09:17:43	ga_ls8c_ard_3-2-1_090078_2022-04-11_final
2022-04-12 09:18:07	ga_ls8c_ard_3-2-1_090079_2022-04-11_final
2022-04-14 10:42:40	ga_ls8c_ard_3-2-1_104074_2022-04-14_final
2022-04-15 09:47:02	ga_ls8c_ard_3-2-1_095074_2022-04-15_final
2022-04-19 09:24:18	ga_ls8c_ard_3-2-1_091079_2022-04-18_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-25 10:23:16	ga_ls8c_ard_3-2-1_101072_2022-04-25_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-05-01 09:46:59	ga_ls8c_ard_3-2-1_095074_2022-05-01_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-07 10:51:39	ga_ls8c_ard_3-2-1_105081_2022-05-07_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-05-14 10:54:18	ga_ls8c_ard_3-2-1_106072_2022-05-14_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-22 10:06:29	ga_ls8c_ard_3-2-1_098076_2022-05-22_final
2022-05-22 11:46:10	ga_ls8c_ard_3-2-1_114078_2022-05-22_final
2022-05-24 09:52:55	ga_ls8c_ard_3-2-1_096073_2022-05-24_final
2022-05-24 09:53:19	ga_ls8c_ard_3-2-1_096074_2022-05-24_final
2022-05-27 10:24:36	ga_ls8c_ard_3-2-1_101075_2022-05-27_final
2022-05-30 09:21:03	ga_ls8c_ard_3-2-1_090086_2022-05-29_final
2022-06-04 09:35:17	ga_ls8c_ard_3-2-1_093075_2022-06-04_final
2022-06-05 10:17:45	ga_ls8c_ard_3-2-1_100073_2022-06-05_final
2022-06-06 11:03:25	ga_ls8c_ard_3-2-1_107079_2022-06-06_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-09 09:52:17	ga_ls8c_ard_3-2-1_096071_2022-06-09_final
2022-06-09 11:35:10	ga_ls8c_ard_3-2-1_112081_2022-06-09_final
2022-06-10 10:37:33	ga_ls8c_ard_3-2-1_103076_2022-06-10_final
2022-06-10 10:37:57	ga_ls8c_ard_3-2-1_103077_2022-06-10_final
2022-06-11 11:21:14	ga_ls8c_ard_3-2-1_110077_2022-06-11_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-19 10:29:28	ga_ls8c_ard_3-2-1_102071_2022-06-19_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