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
2022-01-14 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-01-14_final
2022-09-07 10:33:50	ga_ls8c_ard_3-2-1_102081_2022-09-07_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-16 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-09-16_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-09-22 11:29:32	ga_ls8c_ard_3-2-1_111081_2022-09-22_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-10-03 11:06:34	ga_ls8c_ard_3-2-1_108070_2022-10-03_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-14 10:49:54	ga_ls8c_ard_3-2-1_105075_2022-10-14_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-11-01 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-11-01_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-10 10:33:52	ga_ls8c_ard_3-2-1_102081_2022-11-10_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-18 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-11-18_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-15 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-12-14_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-15 09:26:34	ga_ls8c_ard_3-2-1_091083_2022-12-14_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-09 09:21:29	ga_ls8c_ard_3-2-1_090086_2023-01-08_final
2023-01-17 10:06:49	ga_ls8c_ard_3-2-1_098076_2023-01-17_final
2023-01-17 11:45:42	ga_ls8c_ard_3-2-1_114076_2023-01-17_final
2023-01-26 09:58:44	ga_ls8c_ard_3-2-1_097071_2023-01-26_final
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-26 10:58:26	ga_ls8c_ard_3-2-1_106082_2023-02-26_final
2023-03-05 09:27:42	ga_ls8c_ard_3-2-1_091087_2023-03-04_final
2023-03-05 09:28:30	ga_ls8c_ard_3-2-1_091089_2023-03-04_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_final
2023-03-07 09:16:06	ga_ls8c_ard_3-2-1_089089_2023-03-06_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-11 10:25:51	ga_ls8c_ard_3-2-1_101078_2023-03-11_final
2023-03-19 09:34:45	ga_ls8c_ard_3-2-1_093074_2023-03-19_final
2023-03-26 11:22:08	ga_ls8c_ard_3-2-1_110080_2023-03-26_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-30 10:55:47	ga_ls8c_ard_3-2-1_106076_2023-03-30_final
2023-03-31 09:59:21	ga_ls8c_ard_3-2-1_097074_2023-03-31_final
2023-04-06 09:24:57	ga_ls8c_ard_3-2-1_091081_2023-04-05_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-10 10:34:38	ga_ls8c_ard_3-2-1_103070_2023-04-10_final
2023-04-12 10:27:02	ga_ls8c_ard_3-2-1_101082_2023-04-12_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-28 10:22:35	ga_ls8c_ard_3-2-1_101071_2023-04-28_final
2023-04-29 11:07:02	ga_ls8c_ard_3-2-1_108074_2023-04-29_final
2023-04-30 11:50:41	ga_ls8c_ard_3-2-1_115075_2023-04-30_final
2023-05-01 09:16:58	ga_ls8c_ard_3-2-1_090077_2023-04-30_final
2023-05-01 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-04-30_final
2023-05-02 09:57:02	ga_ls8c_ard_3-2-1_097069_2023-05-02_final
2023-05-11 09:57:29	ga_ls8c_ard_3-2-1_096086_2023-05-11_final
2023-05-20 11:24:10	ga_ls8c_ard_3-2-1_111071_2023-05-20_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-05-25 10:04:15	ga_ls8c_ard_3-2-1_098072_2023-05-25_final
2023-05-26 09:11:01	ga_ls8c_ard_3-2-1_089078_2023-05-25_final
2023-06-01 11:50:31	ga_ls8c_ard_3-2-1_115075_2023-06-01_final
2023-06-02 09:16:48	ga_ls8c_ard_3-2-1_090077_2023-06-01_final
2023-06-11 09:13:08	ga_ls8c_ard_3-2-1_089083_2023-06-10_final
2023-06-11 10:48:50	ga_ls8c_ard_3-2-1_105075_2023-06-11_final
2023-06-12 09:57:13	ga_ls8c_ard_3-2-1_096085_2023-06-12_final
2023-06-14 11:19:45	ga_ls8c_ard_3-2-1_110075_2023-06-14_final
2023-06-15 10:26:56	ga_ls8c_ard_3-2-1_101082_2023-06-15_final
2023-06-16 11:05:25	ga_ls8c_ard_3-2-1_108070_2023-06-16_final
2023-06-16 11:06:36	ga_ls8c_ard_3-2-1_108073_2023-06-16_final
2023-06-17 10:13:47	ga_ls8c_ard_3-2-1_099080_2023-06-17_final
2023-06-21 09:49:52	ga_ls8c_ard_3-2-1_095082_2023-06-21_final
2023-06-23 09:33:07	ga_ls8c_ard_3-2-1_093071_2023-06-23_final
2023-06-23 11:11:12	ga_ls8c_ard_3-2-1_109069_2023-06-23_final
2023-06-24 10:18:23	ga_ls8c_ard_3-2-1_100076_2023-06-24_final
2023-06-25 11:01:40	ga_ls8c_ard_3-2-1_107076_2023-06-25_final
2023-07-12 10:03:51	ga_ls8c_ard_3-2-1_098070_2023-07-12_final
2023-07-18 11:06:51	ga_ls8c_ard_3-2-1_108073_2023-07-18_final
2023-07-18 11:07:15	ga_ls8c_ard_3-2-1_108074_2023-07-18_final
2023-07-29 09:13:08	ga_ls8c_ard_3-2-1_089082_2023-07-28_final
2023-07-30 11:36:05	ga_ls8c_ard_3-2-1_112084_2023-07-30_final
2023-08-01 11:18:57	ga_ls8c_ard_3-2-1_110072_2023-08-01_final
2023-08-01 11:20:33	ga_ls8c_ard_3-2-1_110076_2023-08-01_final
2023-08-21 10:55:34	ga_ls8c_ard_3-2-1_106075_2023-08-21_final
2023-09-04 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-09-04_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_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