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
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-19 11:04:23	ga_ls8c_ard_3-2-1_107082_2022-04-19_final
2022-04-21 09:13:56	ga_ls8c_ard_3-2-1_089084_2022-04-20_final
2022-05-10 09:46:06	ga_ls8c_ard_3-2-1_094087_2022-05-10_final
2022-05-13 11:52:43	ga_ls8c_ard_3-2-1_115079_2022-05-13_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-05-26 09:46:08	ga_ls8c_ard_3-2-1_094087_2022-05-26_final
2022-05-30 10:58:20	ga_ls8c_ard_3-2-1_106082_2022-05-30_final
2022-06-06 11:02:38	ga_ls8c_ard_3-2-1_107077_2022-06-06_final
2022-06-08 09:11:24	ga_ls8c_ard_3-2-1_089077_2022-06-07_final
2022-06-09 09:58:16	ga_ls8c_ard_3-2-1_096086_2022-06-09_final
2022-06-09 11:32:46	ga_ls8c_ard_3-2-1_112075_2022-06-09_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-22 11:02:47	ga_ls8c_ard_3-2-1_107077_2022-06-22_final
2022-06-22 11:04:47	ga_ls8c_ard_3-2-1_107082_2022-06-22_final
2022-06-27 11:20:09	ga_ls8c_ard_3-2-1_110074_2022-06-27_final
2022-07-20 09:46:17	ga_ls8c_ard_3-2-1_095071_2022-07-20_final
2022-07-22 11:16:26	ga_ls8c_ard_3-2-1_109080_2022-07-22_final
2022-07-26 09:14:04	ga_ls8c_ard_3-2-1_089083_2022-07-25_final
2022-08-14 09:45:56	ga_ls8c_ard_3-2-1_094085_2022-08-14_final
2022-08-18 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-08-18_final
2022-08-23 11:18:15	ga_ls8c_ard_3-2-1_109084_2022-08-23_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-05 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-09-05_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-15 11:23:20	ga_ls8c_ard_3-2-1_110081_2022-09-15_final
2022-09-19 10:56:14	ga_ls8c_ard_3-2-1_106075_2022-09-19_final
2022-09-22 11:30:44	ga_ls8c_ard_3-2-1_111084_2022-09-22_final
2022-09-23 10:33:54	ga_ls8c_ard_3-2-1_102081_2022-09-23_final
2022-09-24 09:37:29	ga_ls8c_ard_3-2-1_093079_2022-09-24_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-15 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-10-15_final
2022-10-20 10:16:05	ga_ls8c_ard_3-2-1_099083_2022-10-20_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-04 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-11-04_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-12-01 10:47:34	ga_ls8c_ard_3-2-1_105069_2022-12-01_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-07 11:53:21	ga_ls8c_ard_3-2-1_115079_2022-12-07_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2023-01-07 11:07:57	ga_ls8c_ard_3-2-1_108074_2023-01-07_final
2023-01-10 09:57:57	ga_ls8c_ard_3-2-1_097069_2023-01-10_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-24 10:13:28	ga_ls8c_ard_3-2-1_099077_2023-01-24_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-02-09 10:12:16	ga_ls8c_ard_3-2-1_099074_2023-02-09_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-26 10:54:50	ga_ls8c_ard_3-2-1_106073_2023-02-26_final
2023-03-03 11:14:10	ga_ls8c_ard_3-2-1_109075_2023-03-03_final
2023-03-10 09:45:47	ga_ls8c_ard_3-2-1_094086_2023-03-10_final
2023-03-12 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-03-12_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-31 10:03:44	ga_ls8c_ard_3-2-1_097085_2023-03-31_final
2023-04-09 09:56:11	ga_ls8c_ard_3-2-1_096082_2023-04-09_final
2023-04-15 10:53:32	ga_ls8c_ard_3-2-1_106071_2023-04-15_final
2023-04-16 10:03:06	ga_ls8c_ard_3-2-1_097084_2023-04-16_final
2023-04-20 09:36:44	ga_ls8c_ard_3-2-1_093080_2023-04-20_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-08 09:21:51	ga_ls8c_ard_3-2-1_091074_2023-05-07_final
2023-05-19 10:44:05	ga_ls8c_ard_3-2-1_104079_2023-05-19_final
2023-05-21 10:27:45	ga_ls8c_ard_3-2-1_102069_2023-05-21_final
2023-05-22 11:13:25	ga_ls8c_ard_3-2-1_109075_2023-05-22_final
2023-05-29 11:19:13	ga_ls8c_ard_3-2-1_110074_2023-05-29_final
2023-06-11 10:49:38	ga_ls8c_ard_3-2-1_105077_2023-06-11_final
2023-06-20 10:45:29	ga_ls8c_ard_3-2-1_104082_2023-06-20_final
2023-06-25 11:02:04	ga_ls8c_ard_3-2-1_107077_2023-06-25_final
2023-07-05 09:56:49	ga_ls8c_ard_3-2-1_097068_2023-07-05_final
2023-07-06 10:45:17	ga_ls8c_ard_3-2-1_104081_2023-07-06_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-11 11:02:15	ga_ls8c_ard_3-2-1_107077_2023-07-11_final
2023-07-13 09:11:49	ga_ls8c_ard_3-2-1_089079_2023-07-12_final
2023-07-18 09:30:45	ga_ls8c_ard_3-2-1_092080_2023-07-18_final
2023-08-08 11:28:20	ga_ls8c_ard_3-2-1_111080_2023-08-08_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-02 11:23:29	ga_ls8c_ard_3-2-1_110083_2023-09-02_final
2023-09-21 11:52:52	ga_ls8c_ard_3-2-1_115079_2023-09-21_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-02 11:31:59	ga_ls8c_ard_3-2-1_112073_2023-10-02_final
2023-10-11 09:52:09	ga_ls8c_ard_3-2-1_095086_2023-10-11_final
2023-10-16 10:10:18	ga_ls8c_ard_3-2-1_098085_2023-10-16_final
2023-10-20 09:45:33	ga_ls8c_ard_3-2-1_094085_2023-10-20_final
2023-10-25 09:58:10	ga_ls8c_ard_3-2-1_097070_2023-10-25_final
2023-10-30 10:19:07	ga_ls8c_ard_3-2-1_100076_2023-10-30_final
2023-11-05 09:44:25	ga_ls8c_ard_3-2-1_094082_2023-11-05_final
2023-11-13 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-11-13_final
2023-11-21 11:18:33	ga_ls8c_ard_3-2-1_110070_2023-11-21_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