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
2022-01-20 09:32:03	ga_ls8c_ard_3-2-1_092082_2022-01-20_final
2022-01-20 09:32:27	ga_ls8c_ard_3-2-1_092083_2022-01-20_final
2022-01-20 09:32:51	ga_ls8c_ard_3-2-1_092084_2022-01-20_final
2022-01-20 11:09:20	ga_ls8c_ard_3-2-1_108078_2022-01-20_final
2022-01-20 11:11:44	ga_ls8c_ard_3-2-1_108084_2022-01-20_final
2022-01-21 10:09:43	ga_ls8c_ard_3-2-1_099068_2022-01-21_final
2022-01-21 10:11:43	ga_ls8c_ard_3-2-1_099073_2022-01-21_final
2022-01-21 10:12:07	ga_ls8c_ard_3-2-1_099074_2022-01-21_final
2022-01-21 10:12:55	ga_ls8c_ard_3-2-1_099076_2022-01-21_final
2022-01-21 11:51:48	ga_ls8c_ard_3-2-1_115076_2022-01-21_final
2022-01-21 11:52:12	ga_ls8c_ard_3-2-1_115077_2022-01-21_final
2022-01-22 09:17:41	ga_ls8c_ard_3-2-1_090077_2022-01-21_final
2022-01-22 09:18:05	ga_ls8c_ard_3-2-1_090078_2022-01-21_final
2022-01-22 09:18:29	ga_ls8c_ard_3-2-1_090079_2022-01-21_final
2022-01-22 10:55:46	ga_ls8c_ard_3-2-1_106075_2022-01-22_final
2022-01-22 10:56:10	ga_ls8c_ard_3-2-1_106076_2022-01-22_final
2022-01-22 10:56:34	ga_ls8c_ard_3-2-1_106077_2022-01-22_final
2022-01-22 10:56:58	ga_ls8c_ard_3-2-1_106078_2022-01-22_final
2022-01-22 10:57:22	ga_ls8c_ard_3-2-1_106079_2022-01-22_final
2022-01-22 10:57:46	ga_ls8c_ard_3-2-1_106080_2022-01-22_final
2022-01-22 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-01-22_final
2022-01-22 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-01-22_final
2022-01-23 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-01-23_final
2022-01-23 09:57:44	ga_ls8c_ard_3-2-1_097069_2022-01-23_final
2022-01-23 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-01-23_final
2022-01-23 11:40:37	ga_ls8c_ard_3-2-1_113079_2022-01-23_final
2022-01-23 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-01-23_final
2022-01-23 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-01-23_final
2022-01-24 09:06:30	ga_ls8c_ard_3-2-1_088080_2022-01-23_final
2022-01-24 10:40:36	ga_ls8c_ard_3-2-1_104068_2022-01-24_final
2022-01-24 10:41:00	ga_ls8c_ard_3-2-1_104069_2022-01-24_final
2022-01-24 10:45:23	ga_ls8c_ard_3-2-1_104080_2022-01-24_final
2022-01-25 09:49:21	ga_ls8c_ard_3-2-1_095079_2022-01-25_final
2022-01-25 09:50:33	ga_ls8c_ard_3-2-1_095082_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-01-25 09:52:09	ga_ls8c_ard_3-2-1_095086_2022-01-25_final
2022-01-25 09:52:33	ga_ls8c_ard_3-2-1_095087_2022-01-25_final
2022-01-25 11:24:15	ga_ls8c_ard_3-2-1_111069_2022-01-25_final
2022-01-25 11:24:39	ga_ls8c_ard_3-2-1_111070_2022-01-25_final
2022-01-25 11:25:51	ga_ls8c_ard_3-2-1_111073_2022-01-25_final
2022-01-25 11:26:15	ga_ls8c_ard_3-2-1_111074_2022-01-25_final
2022-01-26 10:29:01	ga_ls8c_ard_3-2-1_102070_2022-01-26_final
2022-01-26 10:30:37	ga_ls8c_ard_3-2-1_102074_2022-01-26_final
2022-01-26 10:31:01	ga_ls8c_ard_3-2-1_102075_2022-01-26_final
2022-01-26 10:31:25	ga_ls8c_ard_3-2-1_102076_2022-01-26_final
2022-01-26 10:33:00	ga_ls8c_ard_3-2-1_102080_2022-01-26_final
2022-01-26 10:33:48	ga_ls8c_ard_3-2-1_102082_2022-01-26_final
2022-01-27 09:34:35	ga_ls8c_ard_3-2-1_093073_2022-01-27_final
2022-01-27 09:36:11	ga_ls8c_ard_3-2-1_093077_2022-01-27_final
2022-01-27 09:37:23	ga_ls8c_ard_3-2-1_093080_2022-01-27_final
2022-01-27 09:37:47	ga_ls8c_ard_3-2-1_093081_2022-01-27_final
2022-01-27 09:38:10	ga_ls8c_ard_3-2-1_093082_2022-01-27_final
2022-01-27 09:38:34	ga_ls8c_ard_3-2-1_093083_2022-01-27_final
2022-01-27 09:39:22	ga_ls8c_ard_3-2-1_093085_2022-01-27_final
2022-01-27 11:12:16	ga_ls8c_ard_3-2-1_109070_2022-01-27_final
2022-01-27 11:12:40	ga_ls8c_ard_3-2-1_109071_2022-01-27_final
2022-01-27 11:13:28	ga_ls8c_ard_3-2-1_109073_2022-01-27_final
2022-01-27 11:13:52	ga_ls8c_ard_3-2-1_109074_2022-01-27_final
2022-01-27 11:14:16	ga_ls8c_ard_3-2-1_109075_2022-01-27_final
2022-01-28 10:18:38	ga_ls8c_ard_3-2-1_100075_2022-01-28_final
2022-01-28 10:19:26	ga_ls8c_ard_3-2-1_100077_2022-01-28_final
2022-01-28 10:19:50	ga_ls8c_ard_3-2-1_100078_2022-01-28_final
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-01-28 11:58:19	ga_ls8c_ard_3-2-1_116077_2022-01-28_final
2022-01-28 11:58:43	ga_ls8c_ard_3-2-1_116078_2022-01-28_final
2022-01-29 09:22:37	ga_ls8c_ard_3-2-1_091074_2022-01-28_final
2022-01-29 09:23:01	ga_ls8c_ard_3-2-1_091075_2022-01-28_final
2022-01-29 09:23:49	ga_ls8c_ard_3-2-1_091077_2022-01-28_final
2022-01-29 09:24:13	ga_ls8c_ard_3-2-1_091078_2022-01-28_final
2022-01-29 09:25:01	ga_ls8c_ard_3-2-1_091080_2022-01-28_final
2022-01-29 11:03:54	ga_ls8c_ard_3-2-1_107080_2022-01-29_final
2022-01-29 11:04:18	ga_ls8c_ard_3-2-1_107081_2022-01-29_final
2022-01-29 11:04:42	ga_ls8c_ard_3-2-1_107082_2022-01-29_final
2022-01-29 11:05:06	ga_ls8c_ard_3-2-1_107083_2022-01-29_final
2022-01-30 10:03:29	ga_ls8c_ard_3-2-1_098068_2022-01-30_final
2022-01-30 10:03:53	ga_ls8c_ard_3-2-1_098069_2022-01-30_final
2022-01-30 10:05:05	ga_ls8c_ard_3-2-1_098072_2022-01-30_final
2022-01-30 10:05:29	ga_ls8c_ard_3-2-1_098073_2022-01-30_final
2022-01-30 10:05:53	ga_ls8c_ard_3-2-1_098074_2022-01-30_final
2022-01-30 11:45:34	ga_ls8c_ard_3-2-1_114076_2022-01-30_final
2022-01-30 11:45:58	ga_ls8c_ard_3-2-1_114077_2022-01-30_final
2022-01-30 11:46:22	ga_ls8c_ard_3-2-1_114078_2022-01-30_final
2022-01-30 11:46:46	ga_ls8c_ard_3-2-1_114079_2022-01-30_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_final
2022-01-30 11:47:33	ga_ls8c_ard_3-2-1_114081_2022-01-30_final
2022-01-31 09:10:39	ga_ls8c_ard_3-2-1_089075_2022-01-30_final
2022-01-31 09:11:27	ga_ls8c_ard_3-2-1_089077_2022-01-30_final
2022-01-31 10:47:09	ga_ls8c_ard_3-2-1_105069_2022-01-31_final
2022-01-31 10:47:57	ga_ls8c_ard_3-2-1_105071_2022-01-31_final
2022-01-31 10:48:21	ga_ls8c_ard_3-2-1_105072_2022-01-31_final
2022-01-31 10:48:45	ga_ls8c_ard_3-2-1_105073_2022-01-31_final
2022-01-31 10:49:08	ga_ls8c_ard_3-2-1_105074_2022-01-31_final
2022-02-01 09:51:55	ga_ls8c_ard_3-2-1_096070_2022-02-01_final
2022-02-01 09:52:19	ga_ls8c_ard_3-2-1_096071_2022-02-01_final
2022-02-01 09:52:43	ga_ls8c_ard_3-2-1_096072_2022-02-01_final
2022-02-01 09:55:55	ga_ls8c_ard_3-2-1_096080_2022-02-01_final
2022-02-01 09:56:43	ga_ls8c_ard_3-2-1_096082_2022-02-01_final
2022-02-01 11:31:36	ga_ls8c_ard_3-2-1_112072_2022-02-01_final
2022-02-01 11:33:36	ga_ls8c_ard_3-2-1_112077_2022-02-01_final
2022-02-01 11:34:00	ga_ls8c_ard_3-2-1_112078_2022-02-01_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