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
2021-12-13 10:04:54	ga_ls8c_ard_3-2-1_098071_2021-12-13_final
2022-01-06 10:53:50	ga_ls8c_ard_3-2-1_106070_2022-01-06_final
2022-01-07 11:37:53	ga_ls8c_ard_3-2-1_113072_2022-01-07_final
2022-01-16 11:36:04	ga_ls8c_ard_3-2-1_112083_2022-01-16_final
2022-01-20 09:28:51	ga_ls8c_ard_3-2-1_092074_2022-01-19_final
2022-01-23 09:58:32	ga_ls8c_ard_3-2-1_097071_2022-01-23_final
2022-02-10 09:52:06	ga_ls8c_ard_3-2-1_095086_2022-02-10_final
2022-02-10 11:25:24	ga_ls8c_ard_3-2-1_111072_2022-02-10_final
2022-02-10 11:25:48	ga_ls8c_ard_3-2-1_111073_2022-02-10_final
2022-02-16 10:52:40	ga_ls8c_ard_3-2-1_105083_2022-02-16_final
2022-03-04 09:16:07	ga_ls8c_ard_3-2-1_089089_2022-03-03_final
2022-03-09 11:05:56	ga_ls8c_ard_3-2-1_108070_2022-03-09_final
2022-03-20 09:14:47	ga_ls8c_ard_3-2-1_089086_2022-03-19_final
2022-03-26 11:52:12	ga_ls8c_ard_3-2-1_115078_2022-03-26_final
2022-04-18 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-04-18_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-05 11:03:36	ga_ls8c_ard_3-2-1_107080_2022-05-05_final
2022-05-06 10:03:36	ga_ls8c_ard_3-2-1_098069_2022-05-06_final
2022-05-19 09:34:47	ga_ls8c_ard_3-2-1_093074_2022-05-19_final
2022-05-21 09:28:49	ga_ls8c_ard_3-2-1_091090_2022-05-20_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-29 10:15:51	ga_ls8c_ard_3-2-1_099084_2022-05-29_final
2022-06-09 11:32:22	ga_ls8c_ard_3-2-1_112074_2022-06-09_final
2022-06-11 11:23:14	ga_ls8c_ard_3-2-1_110082_2022-06-11_final
2022-06-19 10:28:16	ga_ls8c_ard_3-2-1_102068_2022-06-19_final
2022-06-22 09:23:06	ga_ls8c_ard_3-2-1_091075_2022-06-21_final
2022-06-27 09:46:03	ga_ls8c_ard_3-2-1_094086_2022-06-27_final
2022-07-02 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-07-02_final
2022-07-06 11:17:10	ga_ls8c_ard_3-2-1_109082_2022-07-06_final
2022-07-09 10:03:35	ga_ls8c_ard_3-2-1_098068_2022-07-09_final
2022-07-29 11:20:18	ga_ls8c_ard_3-2-1_110074_2022-07-29_final
2022-08-02 09:17:08	ga_ls8c_ard_3-2-1_090075_2022-08-01_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-08-26 11:47:57	ga_ls8c_ard_3-2-1_114081_2022-08-26_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-10-15 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-10-15_final
2022-10-20 10:11:18	ga_ls8c_ard_3-2-1_099071_2022-10-20_final
2022-10-26 09:35:04	ga_ls8c_ard_3-2-1_093073_2022-10-26_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-11 11:17:31	ga_ls8c_ard_3-2-1_109082_2022-11-11_final
2022-11-25 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-11-25_final
2022-12-01 10:49:58	ga_ls8c_ard_3-2-1_105075_2022-12-01_final
2022-12-05 10:24:03	ga_ls8c_ard_3-2-1_101072_2022-12-05_final
2022-12-08 09:17:39	ga_ls8c_ard_3-2-1_090076_2022-12-07_final
2022-12-11 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-12-11_final
2022-12-23 11:52:47	ga_ls8c_ard_3-2-1_115078_2022-12-23_final
2022-12-26 09:06:44	ga_ls8c_ard_3-2-1_088080_2022-12-25_final
2022-12-31 09:22:54	ga_ls8c_ard_3-2-1_091074_2022-12-30_final
2023-01-02 09:11:44	ga_ls8c_ard_3-2-1_089077_2023-01-01_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-01-13 10:28:25	ga_ls8c_ard_3-2-1_102068_2023-01-13_final
2023-01-24 10:09:29	ga_ls8c_ard_3-2-1_099067_2023-01-24_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-02-01 09:22:04	ga_ls8c_ard_3-2-1_091072_2023-01-31_final
2023-02-25 11:52:27	ga_ls8c_ard_3-2-1_115078_2023-02-25_final
2023-03-14 09:16:40	ga_ls8c_ard_3-2-1_090075_2023-03-13_final
2023-04-27 09:45:43	ga_ls8c_ard_3-2-1_094087_2023-04-27_final
2023-05-24 09:20:59	ga_ls8c_ard_3-2-1_091072_2023-05-23_final
2023-06-02 09:16:00	ga_ls8c_ard_3-2-1_090075_2023-06-01_final
2023-06-03 11:36:58	ga_ls8c_ard_3-2-1_113072_2023-06-03_final
2023-06-07 09:39:25	ga_ls8c_ard_3-2-1_093087_2023-06-07_final
2023-06-09 09:27:53	ga_ls8c_ard_3-2-1_091089_2023-06-08_final
2023-06-16 09:34:07	ga_ls8c_ard_3-2-1_092089_2023-06-16_final
2023-06-16 11:07:24	ga_ls8c_ard_3-2-1_108075_2023-06-16_final
2023-07-25 09:33:25	ga_ls8c_ard_3-2-1_093071_2023-07-25_final
2023-07-28 10:09:08	ga_ls8c_ard_3-2-1_098083_2023-07-28_final
2023-08-04 10:14:58	ga_ls8c_ard_3-2-1_099082_2023-08-04_final
2023-08-06 09:57:02	ga_ls8c_ard_3-2-1_097068_2023-08-06_final
2023-08-11 10:17:09	ga_ls8c_ard_3-2-1_100072_2023-08-11_final
2023-08-24 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-08-24_final
2023-08-28 09:28:04	ga_ls8c_ard_3-2-1_091088_2023-08-27_final
2023-09-22 09:17:34	ga_ls8c_ard_3-2-1_090077_2023-09-21_final
2023-09-22 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-09-22_final
2023-09-30 10:03:04	ga_ls8c_ard_3-2-1_098067_2023-09-30_final
2023-10-02 11:31:36	ga_ls8c_ard_3-2-1_112072_2023-10-02_final
2023-10-03 10:35:58	ga_ls8c_ard_3-2-1_103072_2023-10-03_final
2023-10-07 10:14:03	ga_ls8c_ard_3-2-1_099079_2023-10-07_final
2023-10-08 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-10-08_final
2023-10-16 10:09:30	ga_ls8c_ard_3-2-1_098083_2023-10-16_final
2023-10-25 09:57:46	ga_ls8c_ard_3-2-1_097069_2023-10-25_final
2023-11-05 11:20:30	ga_ls8c_ard_3-2-1_110075_2023-11-05_final
2023-11-08 11:52:33	ga_ls8c_ard_3-2-1_115078_2023-11-08_final
2023-11-16 09:21:53	ga_ls8c_ard_3-2-1_091072_2023-11-15_final
2023-11-26 09:57:49	ga_ls8c_ard_3-2-1_097069_2023-11-26_final
2023-11-26 11:37:54	ga_ls8c_ard_3-2-1_113072_2023-11-26_final
2023-11-28 11:24:19	ga_ls8c_ard_3-2-1_111069_2023-11-28_final
2023-12-05 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-12-05_final
2023-12-12 09:58:07	ga_ls8c_ard_3-2-1_097070_2023-12-12_final
2023-12-15 10:28:15	ga_ls8c_ard_3-2-1_102068_2023-12-15_final
2024-01-05 09:16:10	ga_ls8c_ard_3-2-1_089089_2024-01-04_final
2024-01-22 11:32:20	ga_ls8c_ard_3-2-1_112074_2024-01-22_final
2024-01-26 11:05:57	ga_ls8c_ard_3-2-1_108070_2024-01-26_final
2024-02-21 10:07:48	ga_ls8c_ard_3-2-1_098079_2024-02-21_final
2024-03-01 11:38:25	ga_ls8c_ard_3-2-1_113074_2024-03-01_final
2024-03-06 10:17:59	ga_ls8c_ard_3-2-1_100074_2024-03-06_final
2024-03-16 09:16:31	ga_ls8c_ard_3-2-1_090075_2024-03-15_final
2024-03-30 09:28:16	ga_ls8c_ard_3-2-1_092074_2024-03-29_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