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
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-13 11:06:06	ga_ls8c_ard_3-2-1_108070_2022-06-13_final
2022-06-25 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-06-25_final
2022-06-30 11:52:15	ga_ls8c_ard_3-2-1_115077_2022-06-30_final
2022-06-30 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-06-30_final
2022-07-06 09:35:05	ga_ls8c_ard_3-2-1_093074_2022-07-06_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-07-09 11:46:04	ga_ls8c_ard_3-2-1_114077_2022-07-09_final
2022-07-10 09:13:09	ga_ls8c_ard_3-2-1_089081_2022-07-09_final
2022-07-27 09:52:09	ga_ls8c_ard_3-2-1_096070_2022-07-27_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-08-11 09:13:01	ga_ls8c_ard_3-2-1_089080_2022-08-10_final
2022-08-12 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-08-12_final
2022-08-12 11:31:59	ga_ls8c_ard_3-2-1_112072_2022-08-12_final
2022-08-24 10:20:14	ga_ls8c_ard_3-2-1_100078_2022-08-24_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-08-26 10:08:16	ga_ls8c_ard_3-2-1_098079_2022-08-26_final
2022-08-27 09:12:39	ga_ls8c_ard_3-2-1_089079_2022-08-26_final
2022-09-15 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-09-15_final
2022-09-18 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-09-18_final
2022-09-22 11:24:44	ga_ls8c_ard_3-2-1_111069_2022-09-22_final
2022-09-27 10:04:00	ga_ls8c_ard_3-2-1_098068_2022-09-27_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-06 09:58:34	ga_ls8c_ard_3-2-1_097070_2022-10-06_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-16 10:36:46	ga_ls8c_ard_3-2-1_103073_2022-10-16_final
2022-10-20 11:52:11	ga_ls8c_ard_3-2-1_115076_2022-10-20_final
2022-10-29 10:05:11	ga_ls8c_ard_3-2-1_098071_2022-10-29_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-11 09:39:26	ga_ls8c_ard_3-2-1_093084_2022-11-11_final
2022-11-11 11:12:44	ga_ls8c_ard_3-2-1_109070_2022-11-11_final
2022-11-21 10:10:04	ga_ls8c_ard_3-2-1_099068_2022-11-21_final
2022-11-21 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-11-21_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-24 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-11-23_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-11-29 09:27:02	ga_ls8c_ard_3-2-1_091084_2022-11-28_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-02 09:52:45	ga_ls8c_ard_3-2-1_096071_2022-12-02_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-24 10:53:10	ga_ls8c_ard_3-2-1_106068_2022-12-24_final
2022-12-27 09:48:00	ga_ls8c_ard_3-2-1_095075_2022-12-27_final
2022-12-31 09:28:29	ga_ls8c_ard_3-2-1_091088_2022-12-30_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-11 10:42:48	ga_ls8c_ard_3-2-1_104073_2023-01-11_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-18 09:11:59	ga_ls8c_ard_3-2-1_089078_2023-01-17_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-21 09:40:33	ga_ls8c_ard_3-2-1_094072_2023-01-21_final
2023-01-24 10:09:29	ga_ls8c_ard_3-2-1_099067_2023-01-24_final
2023-01-30 09:34:49	ga_ls8c_ard_3-2-1_093073_2023-01-30_final
2023-01-31 11:58:34	ga_ls8c_ard_3-2-1_116077_2023-01-31_final
2023-02-02 10:07:43	ga_ls8c_ard_3-2-1_098078_2023-02-02_final
2023-02-03 09:10:54	ga_ls8c_ard_3-2-1_089075_2023-02-02_final
2023-02-03 09:13:42	ga_ls8c_ard_3-2-1_089082_2023-02-02_final
2023-02-03 10:47:47	ga_ls8c_ard_3-2-1_105070_2023-02-03_final
2023-02-06 09:41:47	ga_ls8c_ard_3-2-1_094075_2023-02-06_final
2023-02-13 11:25:11	ga_ls8c_ard_3-2-1_111071_2023-02-13_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-24 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-02-24_final
2023-02-25 11:51:15	ga_ls8c_ard_3-2-1_115075_2023-02-25_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-16 09:06:17	ga_ls8c_ard_3-2-1_088080_2023-03-15_final
2023-03-20 11:58:29	ga_ls8c_ard_3-2-1_116078_2023-03-20_final
2023-03-21 11:04:02	ga_ls8c_ard_3-2-1_107081_2023-03-21_final
2023-03-23 09:13:09	ga_ls8c_ard_3-2-1_089082_2023-03-22_final
2023-04-07 11:46:41	ga_ls8c_ard_3-2-1_114080_2023-04-07_final
2023-04-14 11:50:46	ga_ls8c_ard_3-2-1_115075_2023-04-14_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-04-18 11:23:37	ga_ls8c_ard_3-2-1_111069_2023-04-18_final
2023-04-29 09:32:33	ga_ls8c_ard_3-2-1_092085_2023-04-29_final
2023-05-02 09:56:38	ga_ls8c_ard_3-2-1_097068_2023-05-02_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-02 09:19:36	ga_ls8c_ard_3-2-1_090084_2023-06-01_final
2023-06-07 09:34:14	ga_ls8c_ard_3-2-1_093074_2023-06-07_final
2023-06-09 09:22:17	ga_ls8c_ard_3-2-1_091075_2023-06-08_final
2023-06-11 09:12:21	ga_ls8c_ard_3-2-1_089081_2023-06-10_final
2023-06-17 10:09:00	ga_ls8c_ard_3-2-1_099068_2023-06-17_final
2023-06-17 11:51:52	ga_ls8c_ard_3-2-1_115078_2023-06-17_final
2023-06-17 11:52:16	ga_ls8c_ard_3-2-1_115079_2023-06-17_final
2023-07-09 11:11:49	ga_ls8c_ard_3-2-1_109070_2023-07-09_final
2023-07-23 11:29:25	ga_ls8c_ard_3-2-1_111083_2023-07-23_final
2023-07-25 09:34:36	ga_ls8c_ard_3-2-1_093074_2023-07-25_final
2023-07-26 10:18:41	ga_ls8c_ard_3-2-1_100076_2023-07-26_final
2023-07-29 09:13:08	ga_ls8c_ard_3-2-1_089082_2023-07-28_final
2023-08-07 09:06:36	ga_ls8c_ard_3-2-1_088081_2023-08-06_final
2023-08-12 09:24:45	ga_ls8c_ard_3-2-1_091080_2023-08-11_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_final
2023-08-15 11:31:23	ga_ls8c_ard_3-2-1_112072_2023-08-15_final
2023-08-20 10:13:05	ga_ls8c_ard_3-2-1_099077_2023-08-20_final
2023-09-05 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-09-05_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