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
2022-04-27 11:50:34	ga_ls8c_ard_3-2-1_115074_2022-04-27_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-05-02 10:30:40	ga_ls8c_ard_3-2-1_102075_2022-05-02_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-06 10:04:48	ga_ls8c_ard_3-2-1_098072_2022-05-06_final
2022-05-06 10:06:47	ga_ls8c_ard_3-2-1_098077_2022-05-06_final
2022-05-08 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-05-08_final
2022-05-15 10:01:53	ga_ls8c_ard_3-2-1_097080_2022-05-15_final
2022-05-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-05-18_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-05-21 09:21:38	ga_ls8c_ard_3-2-1_091072_2022-05-20_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-06-04 09:38:04	ga_ls8c_ard_3-2-1_093082_2022-06-04_final
2022-06-11 09:43:33	ga_ls8c_ard_3-2-1_094080_2022-06-11_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-18 11:29:52	ga_ls8c_ard_3-2-1_111083_2022-06-18_final
2022-06-21 10:17:31	ga_ls8c_ard_3-2-1_100072_2022-06-21_final
2022-06-21 10:19:07	ga_ls8c_ard_3-2-1_100076_2022-06-21_final
2022-06-27 09:44:27	ga_ls8c_ard_3-2-1_094082_2022-06-27_final
2022-06-29 09:30:54	ga_ls8c_ard_3-2-1_092079_2022-06-29_final
2022-07-08 09:26:19	ga_ls8c_ard_3-2-1_091083_2022-07-07_final
2022-07-10 09:13:09	ga_ls8c_ard_3-2-1_089081_2022-07-09_final
2022-07-21 10:31:10	ga_ls8c_ard_3-2-1_102075_2022-07-21_final
2022-07-22 09:39:32	ga_ls8c_ard_3-2-1_093085_2022-07-22_final
2022-07-22 11:17:14	ga_ls8c_ard_3-2-1_109082_2022-07-22_final
2022-07-23 10:21:13	ga_ls8c_ard_3-2-1_100081_2022-07-23_final
2022-07-24 11:00:30	ga_ls8c_ard_3-2-1_107071_2022-07-24_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-07 09:35:19	ga_ls8c_ard_3-2-1_093074_2022-08-07_final
2022-08-10 10:05:26	ga_ls8c_ard_3-2-1_098072_2022-08-10_final
2022-08-23 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-08-23_final
2022-09-04 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-09-04_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-12 10:49:13	ga_ls8c_ard_3-2-1_105073_2022-09-12_final
2022-09-24 11:13:59	ga_ls8c_ard_3-2-1_109073_2022-09-24_final
2022-10-05 10:55:47	ga_ls8c_ard_3-2-1_106074_2022-10-05_final
2022-10-11 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-10-11_final
2022-10-11 10:20:14	ga_ls8c_ard_3-2-1_100078_2022-10-11_final
2022-10-11 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-10-11_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-28 09:26:42	ga_ls8c_ard_3-2-1_091083_2022-10-27_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-08 10:44:15	ga_ls8c_ard_3-2-1_104076_2022-11-08_final
2022-11-19 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-11-19_final
2022-11-20 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-11-20_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-11 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-12-11_final
2022-12-13 11:17:49	ga_ls8c_ard_3-2-1_109083_2022-12-13_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-15 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-12-15_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-08 10:16:19	ga_ls8c_ard_3-2-1_099084_2023-01-08_final
2023-01-09 09:19:29	ga_ls8c_ard_3-2-1_090081_2023-01-08_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-04 09:57:21	ga_ls8c_ard_3-2-1_096083_2023-02-04_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-05 10:37:01	ga_ls8c_ard_3-2-1_103074_2023-02-05_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-22 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-02-22_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-05 11:04:59	ga_ls8c_ard_3-2-1_107083_2023-03-05_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-04-02 09:51:45	ga_ls8c_ard_3-2-1_095086_2023-04-02_final
2023-04-03 10:29:00	ga_ls8c_ard_3-2-1_102071_2023-04-03_final
2023-04-06 10:59:51	ga_ls8c_ard_3-2-1_107071_2023-04-06_final
2023-04-13 11:11:06	ga_ls8c_ard_3-2-1_108084_2023-04-13_final
2023-04-15 09:20:38	ga_ls8c_ard_3-2-1_090086_2023-04-14_final
2023-04-15 10:54:44	ga_ls8c_ard_3-2-1_106074_2023-04-15_final
2023-04-16 10:00:18	ga_ls8c_ard_3-2-1_097077_2023-04-16_final
2023-04-16 10:03:06	ga_ls8c_ard_3-2-1_097084_2023-04-16_final
2023-04-19 10:29:35	ga_ls8c_ard_3-2-1_102073_2023-04-19_final
2023-04-24 09:12:50	ga_ls8c_ard_3-2-1_089082_2023-04-23_final
2023-04-27 09:40:08	ga_ls8c_ard_3-2-1_094073_2023-04-27_final
2023-05-06 11:12:44	ga_ls8c_ard_3-2-1_109073_2023-05-06_final
2023-05-06 11:15:56	ga_ls8c_ard_3-2-1_109081_2023-05-06_final
2023-05-06 11:16:20	ga_ls8c_ard_3-2-1_109082_2023-05-06_final
2023-05-09 10:09:29	ga_ls8c_ard_3-2-1_098085_2023-05-09_final
2023-05-13 09:44:18	ga_ls8c_ard_3-2-1_094084_2023-05-13_final
2023-05-17 09:19:33	ga_ls8c_ard_3-2-1_090084_2023-05-16_final
2023-05-18 10:01:13	ga_ls8c_ard_3-2-1_097080_2023-05-18_final
2023-05-18 11:40:54	ga_ls8c_ard_3-2-1_113082_2023-05-18_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