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
2021-04-28 08:10:17	ga_ls8c_ard_3-2-1_079080_2021-04-27_final
2022-01-15 09:12:44	ga_ls8c_ard_3-2-1_089080_2022-01-14_final
2022-02-03 11:24:26	ga_ls8c_ard_3-2-1_110085_2022-02-03_final
2022-02-16 09:14:35	ga_ls8c_ard_3-2-1_089085_2022-02-15_final
2022-02-16 10:47:28	ga_ls8c_ard_3-2-1_105070_2022-02-16_final
2022-02-17 11:36:19	ga_ls8c_ard_3-2-1_112084_2022-02-17_final
2022-02-19 09:44:15	ga_ls8c_ard_3-2-1_094082_2022-02-19_final
2022-02-21 11:11:34	ga_ls8c_ard_3-2-1_108084_2022-02-21_final
2022-02-27 10:28:53	ga_ls8c_ard_3-2-1_102070_2022-02-27_final
2022-03-01 10:20:31	ga_ls8c_ard_3-2-1_100080_2022-03-01_final
2022-03-01 11:58:36	ga_ls8c_ard_3-2-1_116078_2022-03-01_final
2022-03-12 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-03-12_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-04 11:44:23	ga_ls8c_ard_3-2-1_114074_2022-04-04_final
2022-04-05 09:13:04	ga_ls8c_ard_3-2-1_089082_2022-04-04_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-08 09:53:15	ga_ls8c_ard_3-2-1_096074_2022-05-08_final
2022-05-15 10:01:05	ga_ls8c_ard_3-2-1_097078_2022-05-15_final
2022-05-16 09:07:28	ga_ls8c_ard_3-2-1_088083_2022-05-15_final
2022-05-24 11:34:36	ga_ls8c_ard_3-2-1_112080_2022-05-24_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-07-01 09:22:32	ga_ls8c_ard_3-2-1_090089_2022-06-30_final
2022-07-08 09:23:31	ga_ls8c_ard_3-2-1_091076_2022-07-07_final
2022-07-09 10:03:59	ga_ls8c_ard_3-2-1_098069_2022-07-09_final
2022-07-22 09:37:33	ga_ls8c_ard_3-2-1_093080_2022-07-22_final
2022-07-24 11:00:30	ga_ls8c_ard_3-2-1_107071_2022-07-24_final
2022-07-27 09:52:09	ga_ls8c_ard_3-2-1_096070_2022-07-27_final
2022-07-27 11:36:38	ga_ls8c_ard_3-2-1_112084_2022-07-27_final
2022-08-04 09:07:11	ga_ls8c_ard_3-2-1_088081_2022-08-03_final
2022-08-05 09:51:15	ga_ls8c_ard_3-2-1_095083_2022-08-05_final
2022-08-09 09:26:58	ga_ls8c_ard_3-2-1_091084_2022-08-08_final
2022-08-09 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-08-09_final
2022-08-09 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-08-09_final
2022-08-14 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-08-14_final
2022-09-13 09:53:36	ga_ls8c_ard_3-2-1_096073_2022-09-13_final
2022-09-24 09:38:17	ga_ls8c_ard_3-2-1_093081_2022-09-24_final
2022-09-26 11:02:49	ga_ls8c_ard_3-2-1_107076_2022-09-26_final
2022-10-03 09:28:29	ga_ls8c_ard_3-2-1_092072_2022-10-02_final
2022-10-10 09:38:11	ga_ls8c_ard_3-2-1_093081_2022-10-10_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-11-07 09:58:36	ga_ls8c_ard_3-2-1_097070_2022-11-07_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-03-12 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-03-11_final
2023-04-04 09:35:46	ga_ls8c_ard_3-2-1_093077_2023-04-04_final
2023-04-06 09:22:58	ga_ls8c_ard_3-2-1_091076_2023-04-05_final
2023-04-12 10:27:26	ga_ls8c_ard_3-2-1_101083_2023-04-12_final
2023-04-13 09:28:37	ga_ls8c_ard_3-2-1_092075_2023-04-12_final
2023-04-13 11:09:06	ga_ls8c_ard_3-2-1_108079_2023-04-13_final
2023-04-16 09:59:06	ga_ls8c_ard_3-2-1_097074_2023-04-16_final
2023-04-20 11:12:50	ga_ls8c_ard_3-2-1_109073_2023-04-20_final
2023-04-26 10:34:34	ga_ls8c_ard_3-2-1_103070_2023-04-26_final
2023-05-25 10:09:26	ga_ls8c_ard_3-2-1_098085_2023-05-25_final
2023-05-26 09:15:25	ga_ls8c_ard_3-2-1_089089_2023-05-25_final
2023-06-01 11:51:19	ga_ls8c_ard_3-2-1_115077_2023-06-01_final
2023-06-02 09:21:36	ga_ls8c_ard_3-2-1_090089_2023-06-01_final
2023-06-10 10:06:22	ga_ls8c_ard_3-2-1_098077_2023-06-10_final
2023-06-11 10:51:14	ga_ls8c_ard_3-2-1_105081_2023-06-11_final
2023-06-14 09:43:40	ga_ls8c_ard_3-2-1_094082_2023-06-14_final
2023-07-04 10:56:49	ga_ls8c_ard_3-2-1_106079_2023-07-04_final
2023-08-13 10:03:14	ga_ls8c_ard_3-2-1_098068_2023-08-13_final
2023-08-13 10:08:25	ga_ls8c_ard_3-2-1_098081_2023-08-13_final
2023-08-16 10:39:46	ga_ls8c_ard_3-2-1_103082_2023-08-16_final
2023-08-19 09:29:25	ga_ls8c_ard_3-2-1_092076_2023-08-18_final
2023-08-30 09:10:07	ga_ls8c_ard_3-2-1_089074_2023-08-29_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_final
2023-09-02 09:44:12	ga_ls8c_ard_3-2-1_094082_2023-09-02_final
2023-09-06 09:20:39	ga_ls8c_ard_3-2-1_090085_2023-09-05_final
2023-09-12 10:22:07	ga_ls8c_ard_3-2-1_100084_2023-09-12_final
2023-10-05 10:25:12	ga_ls8c_ard_3-2-1_101076_2023-10-05_final
2023-10-08 09:22:25	ga_ls8c_ard_3-2-1_090089_2023-10-07_final
2023-10-10 09:06:29	ga_ls8c_ard_3-2-1_088080_2023-10-09_final
2023-10-25 10:01:21	ga_ls8c_ard_3-2-1_097078_2023-10-25_final
2023-10-31 09:25:06	ga_ls8c_ard_3-2-1_091080_2023-10-30_final
2023-11-04 10:34:51	ga_ls8c_ard_3-2-1_103069_2023-11-04_final
2023-11-06 10:25:16	ga_ls8c_ard_3-2-1_101076_2023-11-06_final
2023-11-07 09:33:37	ga_ls8c_ard_3-2-1_092086_2023-11-07_final
2023-11-16 09:23:29	ga_ls8c_ard_3-2-1_091076_2023-11-15_final
2023-11-20 10:36:29	ga_ls8c_ard_3-2-1_103073_2023-11-20_final
2023-11-26 10:02:36	ga_ls8c_ard_3-2-1_097081_2023-11-26_final
2023-12-01 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-12-01_final
2024-01-28 09:22:18	ga_ls8c_ard_3-2-1_090089_2024-01-27_final
2024-02-04 09:22:10	ga_ls8c_ard_3-2-1_091073_2024-02-03_final
2024-02-12 10:12:01	ga_ls8c_ard_3-2-1_099074_2024-02-12_final
2024-02-22 09:14:34	ga_ls8c_ard_3-2-1_089085_2024-02-21_final
2024-03-13 10:23:20	ga_ls8c_ard_3-2-1_101072_2024-03-13_final
2024-03-22 10:17:50	ga_ls8c_ard_3-2-1_100074_2024-03-22_final
2024-04-04 09:46:25	ga_ls8c_ard_3-2-1_095073_2024-04-04_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