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
2022-05-06 10:07:35	ga_ls8c_ard_3-2-1_098079_2022-05-06_final
2022-05-10 09:44:30	ga_ls8c_ard_3-2-1_094083_2022-05-10_final
2022-05-10 11:21:23	ga_ls8c_ard_3-2-1_110078_2022-05-10_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-21 11:04:06	ga_ls8c_ard_3-2-1_107081_2022-05-21_final
2022-05-24 09:54:55	ga_ls8c_ard_3-2-1_096078_2022-05-24_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-11 09:43:57	ga_ls8c_ard_3-2-1_094081_2022-06-11_final
2022-06-15 09:19:16	ga_ls8c_ard_3-2-1_090081_2022-06-14_final
2022-06-19 10:31:04	ga_ls8c_ard_3-2-1_102075_2022-06-19_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-21 11:58:48	ga_ls8c_ard_3-2-1_116078_2022-06-21_final
2022-06-23 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-06-23_final
2022-06-29 09:32:30	ga_ls8c_ard_3-2-1_092083_2022-06-29_final
2022-06-30 10:09:46	ga_ls8c_ard_3-2-1_099068_2022-06-30_final
2022-07-08 09:23:55	ga_ls8c_ard_3-2-1_091077_2022-07-07_final
2022-07-08 11:04:00	ga_ls8c_ard_3-2-1_107080_2022-07-08_final
2022-07-13 09:40:51	ga_ls8c_ard_3-2-1_094073_2022-07-13_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-18 09:59:01	ga_ls8c_ard_3-2-1_097072_2022-07-18_final
2022-07-20 09:47:29	ga_ls8c_ard_3-2-1_095074_2022-07-20_final
2022-07-24 11:03:18	ga_ls8c_ard_3-2-1_107078_2022-07-24_final
2022-08-04 10:42:52	ga_ls8c_ard_3-2-1_104073_2022-08-04_final
2022-08-08 10:20:35	ga_ls8c_ard_3-2-1_100079_2022-08-08_final
2022-08-09 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-08-08_final
2022-08-14 09:45:32	ga_ls8c_ard_3-2-1_094084_2022-08-14_final
2022-08-20 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-08-19_final
2022-08-23 11:16:39	ga_ls8c_ard_3-2-1_109080_2022-08-23_final
2022-08-24 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-08-24_final
2022-09-03 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-09-03_final
2022-09-07 10:32:14	ga_ls8c_ard_3-2-1_102077_2022-09-07_final
2022-09-18 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-09-18_final
2022-09-18 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-09-18_final
2022-09-19 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-09-18_final
2022-09-23 10:31:31	ga_ls8c_ard_3-2-1_102075_2022-09-23_final
2022-10-03 11:06:10	ga_ls8c_ard_3-2-1_108069_2022-10-03_final
2022-10-03 11:06:58	ga_ls8c_ard_3-2-1_108071_2022-10-03_final
2022-10-06 09:59:22	ga_ls8c_ard_3-2-1_097072_2022-10-06_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-14 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-10-14_final
2022-10-16 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-10-16_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-17 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-10-17_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-10-31 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-10-31_final
2022-11-02 09:43:40	ga_ls8c_ard_3-2-1_094079_2022-11-02_final
2022-11-20 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-11-20_final
2022-11-23 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-11-23_final
2022-11-24 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-11-24_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-27 11:30:05	ga_ls8c_ard_3-2-1_111083_2022-12-27_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-21 09:42:08	ga_ls8c_ard_3-2-1_094076_2023-01-21_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_final
2023-03-12 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-03-12_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-03-15_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-03-23 10:48:27	ga_ls8c_ard_3-2-1_105073_2023-03-23_final
2023-03-28 09:29:17	ga_ls8c_ard_3-2-1_092076_2023-03-27_final
2023-04-09 09:52:11	ga_ls8c_ard_3-2-1_096072_2023-04-09_final
2023-04-18 11:27:12	ga_ls8c_ard_3-2-1_111078_2023-04-18_final
2023-04-19 10:31:10	ga_ls8c_ard_3-2-1_102077_2023-04-19_final
2023-04-20 11:16:25	ga_ls8c_ard_3-2-1_109082_2023-04-20_final
2023-04-24 10:48:55	ga_ls8c_ard_3-2-1_105075_2023-04-24_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_final
2023-05-28 10:33:58	ga_ls8c_ard_3-2-1_103069_2023-05-28_final
2023-06-10 11:44:27	ga_ls8c_ard_3-2-1_114075_2023-06-10_final
2023-06-11 10:49:38	ga_ls8c_ard_3-2-1_105077_2023-06-11_final
2023-06-20 09:07:00	ga_ls8c_ard_3-2-1_088083_2023-06-19_final
2023-06-23 11:12:24	ga_ls8c_ard_3-2-1_109072_2023-06-23_final
2023-06-27 10:46:33	ga_ls8c_ard_3-2-1_105069_2023-06-27_final
2023-07-02 11:11:09	ga_ls8c_ard_3-2-1_108084_2023-07-02_final
2023-07-16 09:45:31	ga_ls8c_ard_3-2-1_094086_2023-07-16_final
2023-07-23 11:26:13	ga_ls8c_ard_3-2-1_111075_2023-07-23_final
2023-07-25 11:11:54	ga_ls8c_ard_3-2-1_109070_2023-07-25_final
2023-07-25 11:13:06	ga_ls8c_ard_3-2-1_109073_2023-07-25_final
2023-07-27 11:00:22	ga_ls8c_ard_3-2-1_107072_2023-07-27_final
2023-08-05 09:19:21	ga_ls8c_ard_3-2-1_090082_2023-08-04_final
2023-08-14 09:12:25	ga_ls8c_ard_3-2-1_089080_2023-08-13_final
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_final
2023-09-09 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-09-09_final
2023-09-14 10:09:23	ga_ls8c_ard_3-2-1_098083_2023-09-14_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