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
2022-05-01 09:49:23	ga_ls8c_ard_3-2-1_095080_2022-05-01_final
2022-05-07 09:13:10	ga_ls8c_ard_3-2-1_089082_2022-05-06_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-17 09:47:32	ga_ls8c_ard_3-2-1_095075_2022-05-17_final
2022-05-19 09:36:47	ga_ls8c_ard_3-2-1_093079_2022-05-19_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-05-30 09:19:27	ga_ls8c_ard_3-2-1_090082_2022-05-29_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-08 10:51:53	ga_ls8c_ard_3-2-1_105081_2022-06-08_final
2022-06-11 11:20:50	ga_ls8c_ard_3-2-1_110076_2022-06-11_final
2022-06-19 10:30:40	ga_ls8c_ard_3-2-1_102074_2022-06-19_final
2022-06-22 11:03:59	ga_ls8c_ard_3-2-1_107080_2022-06-22_final
2022-06-23 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-06-23_final
2022-07-02 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-07-02_final
2022-07-08 11:04:24	ga_ls8c_ard_3-2-1_107081_2022-07-08_final
2022-07-10 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-07-10_final
2022-07-10 10:52:02	ga_ls8c_ard_3-2-1_105081_2022-07-10_final
2022-07-18 11:41:30	ga_ls8c_ard_3-2-1_113081_2022-07-18_final
2022-07-21 10:29:10	ga_ls8c_ard_3-2-1_102070_2022-07-21_final
2022-07-22 09:39:09	ga_ls8c_ard_3-2-1_093084_2022-07-22_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-07-24 09:26:01	ga_ls8c_ard_3-2-1_091082_2022-07-23_final
2022-07-25 11:44:59	ga_ls8c_ard_3-2-1_114074_2022-07-25_final
2022-07-26 09:14:28	ga_ls8c_ard_3-2-1_089084_2022-07-25_final
2022-07-27 11:35:26	ga_ls8c_ard_3-2-1_112081_2022-07-27_final
2022-07-28 10:38:13	ga_ls8c_ard_3-2-1_103077_2022-07-28_final
2022-07-29 09:41:01	ga_ls8c_ard_3-2-1_094073_2022-07-29_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-06 10:33:19	ga_ls8c_ard_3-2-1_102080_2022-08-06_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-15 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-08-15_final
2022-08-15 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-08-15_final
2022-08-26 11:47:10	ga_ls8c_ard_3-2-1_114079_2022-08-26_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-08-31 10:24:01	ga_ls8c_ard_3-2-1_101072_2022-08-31_final
2022-09-12 10:52:49	ga_ls8c_ard_3-2-1_105082_2022-09-12_final
2022-09-18 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-09-18_final
2022-09-24 11:15:58	ga_ls8c_ard_3-2-1_109078_2022-09-24_final
2022-09-24 11:17:34	ga_ls8c_ard_3-2-1_109082_2022-09-24_final
2022-09-27 11:47:40	ga_ls8c_ard_3-2-1_114080_2022-09-27_final
2022-09-30 10:35:41	ga_ls8c_ard_3-2-1_103070_2022-09-30_final
2022-10-04 11:52:37	ga_ls8c_ard_3-2-1_115077_2022-10-04_final
2022-10-05 09:19:42	ga_ls8c_ard_3-2-1_090081_2022-10-04_final
2022-10-10 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-10-10_final
2022-10-17 11:19:15	ga_ls8c_ard_3-2-1_110071_2022-10-17_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-28 09:26:18	ga_ls8c_ard_3-2-1_091082_2022-10-27_final
2022-10-28 11:03:36	ga_ls8c_ard_3-2-1_107078_2022-10-28_final
2022-10-28 11:04:00	ga_ls8c_ard_3-2-1_107079_2022-10-28_final
2022-10-29 10:08:46	ga_ls8c_ard_3-2-1_098080_2022-10-29_final
2022-10-29 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-10-29_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-10-31 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-10-31_final
2022-11-02 09:44:04	ga_ls8c_ard_3-2-1_094080_2022-11-02_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-09 09:48:13	ga_ls8c_ard_3-2-1_095075_2022-11-09_final
2022-11-09 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-11-09_final
2022-11-09 11:27:06	ga_ls8c_ard_3-2-1_111075_2022-11-09_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-13 09:24:39	ga_ls8c_ard_3-2-1_091078_2022-11-12_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-11-24 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-11-24_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-04 09:43:59	ga_ls8c_ard_3-2-1_094080_2022-12-04_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-15 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-12-15_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-07 09:35:03	ga_ls8c_ard_3-2-1_092089_2023-01-07_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-16 09:25:34	ga_ls8c_ard_3-2-1_091081_2023-01-15_final
2023-01-22 10:24:37	ga_ls8c_ard_3-2-1_101074_2023-01-22_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-15 11:17:11	ga_ls8c_ard_3-2-1_109082_2023-02-15_final
2023-02-17 11:01:12	ga_ls8c_ard_3-2-1_107073_2023-02-17_final
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_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