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
2020-03-27 08:42:10	ga_ls8c_ard_3-2-1_084082_2020-03-26_final
2021-12-19 09:29:23	ga_ls8c_ard_3-2-1_092075_2021-12-18_final
2022-01-02 11:23:21	ga_ls8c_ard_3-2-1_110082_2022-01-02_final
2022-02-08 11:42:09	ga_ls8c_ard_3-2-1_113083_2022-02-08_final
2022-02-10 09:46:55	ga_ls8c_ard_3-2-1_095073_2022-02-10_final
2022-02-16 10:47:05	ga_ls8c_ard_3-2-1_105069_2022-02-16_final
2022-02-20 10:23:07	ga_ls8c_ard_3-2-1_101071_2022-02-20_final
2022-02-22 10:13:33	ga_ls8c_ard_3-2-1_099078_2022-02-22_final
2022-02-25 10:45:15	ga_ls8c_ard_3-2-1_104080_2022-02-25_final
2022-02-26 09:52:01	ga_ls8c_ard_3-2-1_095086_2022-02-26_final
2022-03-01 11:58:12	ga_ls8c_ard_3-2-1_116077_2022-03-01_final
2022-03-10 11:52:47	ga_ls8c_ard_3-2-1_115079_2022-03-10_final
2022-03-20 10:46:29	ga_ls8c_ard_3-2-1_105068_2022-03-20_final
2022-04-02 10:19:50	ga_ls8c_ard_3-2-1_100079_2022-04-02_final
2022-04-16 10:33:06	ga_ls8c_ard_3-2-1_102081_2022-04-16_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-20 10:09:57	ga_ls8c_ard_3-2-1_098085_2022-04-20_final
2022-05-03 11:13:56	ga_ls8c_ard_3-2-1_109075_2022-05-03_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-06-07 10:03:26	ga_ls8c_ard_3-2-1_098068_2022-06-07_final
2022-06-12 10:22:50	ga_ls8c_ard_3-2-1_101070_2022-06-12_final
2022-06-13 11:09:41	ga_ls8c_ard_3-2-1_108079_2022-06-13_final
2022-06-17 10:45:24	ga_ls8c_ard_3-2-1_104080_2022-06-17_final
2022-06-20 11:14:20	ga_ls8c_ard_3-2-1_109075_2022-06-20_final
2022-07-04 09:52:38	ga_ls8c_ard_3-2-1_095087_2022-07-04_final
2022-07-24 12:37:48	ga_ls8c_ard_3-2-1_123067_2022-07-24_final
2022-07-25 10:10:29	ga_ls8c_ard_3-2-1_098085_2022-07-25_final
2022-08-01 10:11:09	ga_ls8c_ard_3-2-1_099071_2022-08-01_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-05 09:52:27	ga_ls8c_ard_3-2-1_095086_2022-08-05_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-18 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-08-17_final
2022-08-23 09:34:35	ga_ls8c_ard_3-2-1_093072_2022-08-23_final
2022-08-23 09:39:22	ga_ls8c_ard_3-2-1_093084_2022-08-23_final
2022-08-29 10:34:47	ga_ls8c_ard_3-2-1_103068_2022-08-29_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-06 11:25:51	ga_ls8c_ard_3-2-1_111072_2022-09-06_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-10-04 10:11:20	ga_ls8c_ard_3-2-1_099071_2022-10-04_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-10 11:17:28	ga_ls8c_ard_3-2-1_109082_2022-10-10_final
2022-10-12 11:00:17	ga_ls8c_ard_3-2-1_107070_2022-10-12_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-10-30 10:52:50	ga_ls8c_ard_3-2-1_105082_2022-10-30_final
2022-11-11 11:14:43	ga_ls8c_ard_3-2-1_109075_2022-11-11_final
2022-11-20 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-11-20_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-29 11:05:07	ga_ls8c_ard_3-2-1_107082_2022-11-29_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-05 11:19:07	ga_ls8c_ard_3-2-1_110071_2023-01-05_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-14 11:17:39	ga_ls8c_ard_3-2-1_109083_2023-01-14_final
2023-01-16 11:04:51	ga_ls8c_ard_3-2-1_107082_2023-01-16_final
2023-01-19 11:31:46	ga_ls8c_ard_3-2-1_112072_2023-01-19_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_2023-03-16_final
2023-03-17 11:24:50	ga_ls8c_ard_3-2-1_111071_2023-03-17_final
2023-03-26 11:20:32	ga_ls8c_ard_3-2-1_110076_2023-03-26_final
2023-03-26 11:20:56	ga_ls8c_ard_3-2-1_110077_2023-03-26_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-24 09:15:37	ga_ls8c_ard_3-2-1_089089_2023-04-23_final
2023-04-29 11:07:02	ga_ls8c_ard_3-2-1_108074_2023-04-29_final
2023-05-05 10:30:17	ga_ls8c_ard_3-2-1_102075_2023-05-05_final
2023-05-06 11:13:56	ga_ls8c_ard_3-2-1_109076_2023-05-06_final
2023-05-08 11:01:08	ga_ls8c_ard_3-2-1_107075_2023-05-08_final
2023-05-13 09:43:30	ga_ls8c_ard_3-2-1_094082_2023-05-13_final
2023-05-29 09:43:32	ga_ls8c_ard_3-2-1_094082_2023-05-29_final
2023-06-04 10:44:34	ga_ls8c_ard_3-2-1_104080_2023-06-04_final
2023-06-26 10:06:28	ga_ls8c_ard_3-2-1_098077_2023-06-26_final
2023-07-03 10:15:57	ga_ls8c_ard_3-2-1_099085_2023-07-03_final
2023-07-10 08:42:06	ga_ls8c_ard_3-2-1_084082_2023-07-09_final
2023-07-15 10:39:32	ga_ls8c_ard_3-2-1_103082_2023-07-15_final
2023-07-22 10:44:56	ga_ls8c_ard_3-2-1_104080_2023-07-22_final
2023-07-23 09:50:56	ga_ls8c_ard_3-2-1_095084_2023-07-23_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-08-11 11:57:38	ga_ls8c_ard_3-2-1_116076_2023-08-11_final
2023-08-17 11:19:51	ga_ls8c_ard_3-2-1_110074_2023-08-17_final
2023-08-17 11:20:15	ga_ls8c_ard_3-2-1_110075_2023-08-17_final
2023-08-24 09:51:59	ga_ls8c_ard_3-2-1_095086_2023-08-24_final
2023-10-07 10:10:27	ga_ls8c_ard_3-2-1_099070_2023-10-07_final
2023-11-16 09:23:53	ga_ls8c_ard_3-2-1_091077_2023-11-15_final
2023-11-16 11:00:22	ga_ls8c_ard_3-2-1_107071_2023-11-16_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-25 10:58:38	ga_ls8c_ard_3-2-1_106082_2023-11-25_final
2023-12-02 11:04:44	ga_ls8c_ard_3-2-1_107082_2023-12-02_final
2023-12-21 11:32:29	ga_ls8c_ard_3-2-1_112074_2023-12-21_final
2024-01-02 11:57:30	ga_ls8c_ard_3-2-1_116075_2024-01-02_final
2024-01-09 10:24:23	ga_ls8c_ard_3-2-1_101074_2024-01-09_final
2024-01-27 11:52:24	ga_ls8c_ard_3-2-1_115078_2024-01-27_final
2024-02-12 10:16:24	ga_ls8c_ard_3-2-1_099085_2024-02-12_final
2024-02-27 11:10:45	ga_ls8c_ard_3-2-1_108082_2024-02-27_final
2024-03-02 10:45:10	ga_ls8c_ard_3-2-1_104080_2024-03-02_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